DECIDE-PartB-v1-1
EUROPEAN COMMISSION
7 TH F RAMEWORK P ROGRAMME
P ROPOSAL A CRONYM :
C
APACITIES
R
ESEARCH
I
NFRASTRUCTURES
C
ALL
I
DENTIFIER
: FP7-INFRASTRUCTURES-2010-2
P ROPOSAL F ULL T ITLE :
DIAGNOSTIC ENHANCEMENT OF CONFIDENCE BY AN
INTERNATIONAL DISTRIBUTED ENVIRONMENT
DECIDE
1
8
9
6
7
4
5
2
3
10
11
12
13
T YPE OF F UNDING S CHEME :
Combination of Collaborative Projects and Coordination and Support
Actions: (CP-CSA)
W ORKPROGRAMME T OPICS
A DDRESSED :
N
AME OF
C
OORDINATING
P ERSON :
C OORDINATING
I NSTITUTION :
Participant no.
INFRA-2010-1.2.3: V IRTUAL R ESEARCH C OMMUNITIES
L AURA L EONE
GARR
Participant Organisation name Country
GARR (Coordinator)
C ONSIGLIO N AZIONALE DELLE R ICERCHE
C
ONSORZIO
C
OMETA
F ATEBENE F RATELLI
S
AN
R
AFFAELE
H
OSPITAL
U NIVERSITY OF G ENOVA
U NIVERSITY OF F OGGIA
I STITUTO DI R ICERCA D IAGNOSTICA N UCLEARE
M AAT GKNOWLEDGE
I MPERIAL C OLLEGE L ONDON
D EPARTMENT OF B IOMEDICAL P HYSICS , U NIVERSITY OF W ARSAW
U NIVERSITY OF F OGGIA
E UROPEAN C ONSORTIUM FOR A LZHEIMER D ISEASE
I TALY
I TALY
I
TALY
I TALY
I
TALY
I TALY
I TALY
I TALY
F RANCE
UK
P OLAND
I TALY
F RANCE
PROPOSAL SUMMARY PAGE
DECIDE
Abstract
The field of medical imaging has developed enormously in the past 20 years. Image databases made of thousands of images are now available that can be used as a reference for individual diagnosis, and sophisticated algorithms can extract information from medical images that cannot be appreciated by the naked eye. The field of neurodegenerative disorders can especially benefit from these acquisitions. Neuroscientists have recently learned that highly prevalent and burdensome chronic brain diseases such as Alzheimer’s and other neurodegenerative and neuro developmental disorders can be diagnosed early with image-based markers of structural and functional brain changes, allowing early pharmacological or rehabilitative interventions. Aim of this project is to provide clinical neurologists with neuroimaging applications that can make use of large reference databases and advanced algorithms to detect disease markers in individual patients based on structural MR, metabolic and receptor Positron Emission Tomography (PET), perfusion Single Photon Emission Tomography (SPECT), and electroencephalographic (EEG) images.
Applications will be provided to meet the needs of neurologists for earlier and more accurate diagnosis that use validated quantitative assessment of structural and functional brain images, such as (non exhaustive list): (i) voxel based statistical analysis of 18F-FDG PET and Tc99-ECD
SPET for the diagnosis of neurodegenerative diseases, (ii) pattern recognition analysis of 18F-
DOPA PET for the classification of schizophrenic patients and of structural MR scans for the diagnosis of neurodegenerative diseases, and (iii) segmentation techniques of MRI images for the extraction of hippocampal volume for the diagnosis of Alzheimer’s disease. Large sets of validated reference images of normal persons will be exposed to clinical users. Computer-aided applications will be developed and implemented into a Grid middleware, taking advantage of the
Grid to: (i) provide authorized and secure access to largely distributed database for healthy subject data, (ii) supply efficiently intensive computationally processes as those required be the above applications, and (iii) allow clinical images to reside locally and comply with the strict clinical data sharing policies of most hospitals.
The impact of the project will be on a large scale, by enabling doctors from local hospitals not owning large sets of images from normal patients and access to sophisticated algorithms to carry out analyses remotely and efficiently by the use a centralized web-Grid service.
I NDEX
Scientific and/or technological excellence, relevant to the topics addressed by the call 5
Progress beyond the State-of-the-art GARR (Mario)+ partners ................................ 5
Grid enabled applications and existing communities ........................................ 10
NA1 – Management of the CP-CSA Project [GARR, Laura Leone]
NA2 – Standardization, Liaison and International Cooperation FBF
Trans-national Access and/or Service Activities, and associated work plan ......... 28
– Design, exposure of and access to the reference databases IC
JRA1 – Porting of the diagnostic algorithms UGDIST
....................................... 35
– Design of the Diagnostic Services CNR
............................................... 43
– User Validation and Testing EADC
...................................................... 50
Consortium GARR – GARR (Coordinator)
........................................................ 67
Section 1.
S CIENTIFIC AND / OR TECHNOLOGICAL EXCELLENCE ,
RELEVANT TO THE TOPICS ADDRESSED BY THE CALL
[Recommended length for the whole of Section 1 – forty pages, not including the tables]
1.1
Concept and objectives
[Explain the concept of your project. What are the main ideas that led you to propose this work?
Describe in detail the S&T objectives. Show how they relate to the topics addressed by the call. The objectives should be those achievable within the project, not through subsequent development. They should be stated in a measurable and verifiable form, including through the milestones that will be indicated under section 1.3 below.]
Enhancement of confidence is…
1.1.1
Objectives
The main objectives addressed by the DECIDE Project are the following:
O1.
Create an open e-Infrastructure aimed at offering to Neurologist …
O2.
Provide a large amount of medical cases for statistics…
O3.
Ease the access to medical data…
O4.
Create an integrated tool for physicians…
1.2
Progress beyond the State-of-the-art GARR (Mario)+ partners
[Describe the state-of-the-art in the area concerned, and the advance that the proposed project would bring about. If applicable, refer to the results of any patent search you might have carried out.]
1.2.1
Enabling e Infrastructures
Research and Education Networks (GARR and the NRENs, GEANT)
Communication Networks
GEANT, GARR, NREN
Underlying Grid infrastructure: architecture and services of COMETA e-Infrastructure
1.2.1.1.1
Architecture
The Sicilian e-Infrastructure of the Consorzio COMETA is made of 7 “production sites” distributed in the three main cities of Catania, Messina and Palermo and located inside the campuses of the local Universities.
Five out of the seven total sites are located inside the campus of the University of Catania and are listed below:
1) Site Name: COMETA-INAF-CATANIA The site is hosted by the Astrophysical
Observatory of the Italian National Institute for Astrophysics (INAF);
2) Site Name: COMETA-INFN-CATANIA – The site is physically located inside the
Department of Physics and Astronomy of the University of Catania and it is operated by staff of the “Sezione di Catania” of the Italian National Institute of Nuclear Physics (INFN);
3) Site Name: COMETA-INFNLNS-CATANIA – The site is hosted by the “Laboratori
Nazionali del Sud” of the Italian National Institute of Nuclear Physics (INFN);
4) Site Name: COMETA-UNICT-DIIT-CATANIA – The site is hosted by the Faculty of
Engineering of the University of Catania.
5) Site Name: COMETA-UNICT-DMI-CATANIA – The site is hosted by the Department of
Mathematics and Informatics of the University of Catania.
The site operational at the University of Messina is:
1) Site Name: COMETA-INGEGNERIA-MESSINA – The site is hosted by the Faculty of
Engineering of the University of Messina.
The site operational at the University of Palermo is:
2) Site Name: COMETA-UNIPA-PALERMO
– The site is hosted by the Department of
Physical and Astrophysical Sciences of the University of Palermo.
The computing infrastructure is based on IBM Blade Centre H chassis each containing up to 14
IBM LS21 “blades” interconnected both with a double Gigabit Ethernet network, for normal communications with redundancy and load balancing, and a CISCO Topspin Infiniband-4X network, required to provide the COMETA Grid with HPC functionalities. The infrastructure is built with identical hardware and software at all sites. This choice was made un purpose to allow for the maximum interoperability and realizes a homogeneous environment which is a fundamental condition for an HPC Grid environment able to run distributed parallel jobs of applications adopting the MPI paradigm.
Each “blade” is equipped with 2 AMD Opteron 2218 rev. F dual-core processors with a clock rate of 2,6 GHz able to natively execute x86 32 and 64 bits binary code. Each processor has 2 GB of
DDR2 RAM at 667 MHz (8 GB in total per “blade”) and it is equipped with a direct communication channel to the other processor on the same motherboard. The memory controller is integrated onboard.
The following table shows the share of the computing power among the seven sites of the Sicilian e-Infrastructure:
Site Name
COMETA-INAF-CATANIA
No. of blades
74
No. of
Cores
296
Total
RAM
(GB)
592
Aggregated
SPECint
3352
*
Aggregated
SPECfp
**
3293
COMETA-INFN-CATANIA
COMETA-INFNLNS-CATANIA
COMETA-UNICT-DIIT-CATANIA
71
28
44
284
112
176
568
224
352
3216
1268
1993
3160
1246
1958
COMETA-UNICT-DMI-CATANIA 34
COMETA-INGEGNERIA-MESSINA 68
COMETA-UNIPA-PALERMO 154
136
272
616
272
544
1232
1540
3080
6976
1513
3026
6853
TOTAL 473 1892 3784 21427 21049
(*) SPECint2006_rate_base for 1 LS21 Blade Server = 45.3.
(**) SPECfp2006_rate_base for 1 LS21 Blade Server = 44.5.
The storage infrastructure is based on IBM DS 4200 Storage Systems that provide high features of redundancy, management and reliability. In fact, a DS 4200 Storage System supports several types of RAID and has an intrinsic redundancy of all critical components (fan, power, controller) to assure maximum reliability. It allows expansions up to 56 TB each with SATA disks. Each Storage
System is managed by two IBM x3655 servers that “export” the GPFS pool to all computing nodes.
The following table shows the configuration of the Storage Elements at the 7 sites of the COMETA
Grid infrastructure.
Site Name
COMETA-INAF-CATANIA
COMETA-INFN-CATANIA
COMETA-INFNLNS-CATANIA
COMETA-UNICT-DIIT-CATANIA
COMETA-UNICT-DMI-CATANIA
COMETA-INGEGNERIA-MESSINA
COMETA-UNIPA-PALERMO
No. of
HDs
*
24
126
44
32
40
30
44
Raw disk space (TB)
12
99
15
24
30
19
22
TOTAL 340
(*) Disks have sizes both of 500 and 750 GB each.
221
1.2.1.1.2
Grid Services
As explained in the section concerning WP3, one of the goals of SISSI is to maintain and operate at a production quality level both the central and the site-specific Grid services deployed on the
COMETA e-Infrastructure. All these services are listed here:
Central Grid services: o Global Information Index (GIIS/BDII); o Workload Management System (WMS); o Logging and Book-keeping (LB); o Logical File Catalogue (LFC); o Metadata Catalogue (AMGA); o File Transfer Service (FTS); o Central Accounting System (HLRMON); o MyProxy Server (MYPROXY);
Site-specific Grid services: o Computing Element (CE); o Storage Element (SE); o User Interface (UI); o Worker Nodes (WNs); o Local Information Index (GRIS); o Local Accounting System (HLR); and briefly explained in the following sub-sections.
1.2.1.1.3
Global Information Index (BDII)
The BDII is a Grid service that periodically queries a list of GRISes (see below) and executes the information providers listed in its configuration file, if any. A Virtual Organisation (VO) can configure its BDIIs to query only those sites that are relevant to the VO.
In order to improve the scalability and have a better performance, the BDII uses two databases, one read-only and one write-only, which are switched when an update is completed As expected, an increase in the number of sites leads to a proportional increase in the time needed to update the database, and to less up-to-date information, but not to a degradation in the response time of the
Information Index. All sites are queried in parallel, but the database has to be updated sequentially.
1.2.1.1.4
Workload Management System (WMS)
The Workload Management System is the most important gLite service. It finds the best resource in order to match the requirements of a job (match-making process). Within a Grid infrastructure, this service accomplishes the tasks listed below:
Resource discovery by identifying a list of authorized machines that can be used by a given user;
Selection of resources that are expected to meet the time or cost constraints imposed by the user such as starting time, the usage duration, the amount of memory or storage required, etc.;
Job scheduling by mapping pending jobs to specific physical resources, trying to minimize the cost function specified by the user;
Job monitoring and migration which can be considered as an efficient way to guarantee that the submitted jobs are completed and the user restrictions are met.
The WMS relies on the BDII for resource discovery.
1.2.1.1.5
Logging and Book-keeping (LB)
This Grid service complements the WMS and its function is to log all the information for each job.
It is usually queried by the User Interface when a user wants to inspect the status of his/her jobs.
1.2.1.1.6
Logical File Catalogue (LFC)
This gLite service maps Logical File Names (LFNs) onto Physical File Names (PFNs), i.e. the
“high level” names given by users to their files distributed on the Grid with the physical locations of those files (including eventual replicas) on the Storage Elements (see below).
1.2.1.1.7
Metadata Catalogue (AMGA)
The AMGA metadata catalogue manages metadata associated to Logical Files whose corresponding
Physical Files are located on Storage Elements distributed on a Grid infrastructure.
1.2.1.1.8
File Transfer Service (FTS)
The File Transfer Service (FTS) is a gLite service that allows for asynchronous transfers of large data-sets (up to PetaBytes) across Grid Storage Elements in a fault tolerant way.
1.2.1.1.9
Central Accounting SysteM (HLRMON)
HLRMON is basically a web server that publishes the accounting values collected from local site
HLRs and allows for different “views”.
1.2.1.1.10
MyProxy Server (MYPROXY)
The MyProxy service allows users to store special credentials that can be used to delegate proxies to themselves or to other Grid services (e.g., the WMS) when they want to access grid portals or to run very long jobs.
1.2.1.1.11
Computing Element (CE)
A Computing Element is a queue of a Local Resource Management System that is “seen” by the
WMS as a computing resource where users’ jobs can be submitted.
1.2.1.1.12
Storage Element (SE)
A Storage Element is portion of storage space that can “seen” by users as a “disk” to which data can be stored.
1.2.1.1.13
User Interface (UI)
The User Interface is the “gateway” to a Grid infrastructure and it the gLite service used by users to submit/monitor/retrieve their jobs and to manage their data.
1.2.1.1.14
Worker Nodes (WNs)
The Worker Nodes are the computing nodes of a Grid Infrastructure. They are “grouped” in queues that are “published” by a site as Computing Elements.
1.2.1.1.15
Local Information Index (GRIS)
This service collects periodically the information about the status of a site CE/SE (number of total/busy CPUs, number of running/waiting jobs, total/available disk space, etc.) and publishes it on the BDII.
1.2.1.1.16
Local Accounting System (HLR)
This services collects accounting data for jobs and disk occupancy at a site level on a “per job”/”per user” basis and publishes them on the central HLRMON.
1.2.1.1.17
Virtual Organisation Service (VOMS)
The Virtual Organisation Membership Service (VOMS) is a Grid service that provides information on the user's relationship with his/her Virtual Organisation: groups, roles and capabilities. It is basically a simple account database which serves the information in a special format (VOMS credential). Data are stored in a ORACLE/MySQL database and a failover is implemented using the generic database replication mechanism in a master/slave configuration.
1.2.1.1.18
Monitoring Services
1.2.1.1.18.1
GStat
The Information Index (BDII) provides information about the Grid resources and their status. This information is essential for the operation of the whole Grid. GStat is a monitoring tool based on
Python scripts. GStat validates the accessibility of the BDII on a per-site basis and performs internal consistency checks of the published information. This test is performed every few minutes and the results are made available on a web page.
1.2.1.1.18.2
SAM
The Service Availability Monitoring (SAM) aims to provide a site independent, centralized and uniform monitoring tool for all Grid services. It is the main source of monitoring information for high-level Grid operations and is being used in the validation of sites and services with calculation of availability metrics. The main functions of the SAM are to monitor SEs, LFC, FTS, CEs, WMS, l
BDII, GRISes, MyProxy, and VOMS services. SAM consists of two packages:
• SAM Client – runs on a monitoring site UI and submits various job packages to the Grid and monitors their execution. Every change of status is sent to the SAM Server;
•
SAM Server – receives and stores the information sent from the SAM Client and presents it in a dynamic website.
SAM relies on the standard job submission mechanism on a single UI. The tests are in fact different scripts intended for execution on WNs of every monitored site in order to test various Grid functionalities. When the SAM test package is started, all specified scripts are packed in a single job description and are submitted to a list of specified CEs. The administrator is able to choose some predefined testing scripts, and also define new ones, all of which will be packaged together for the
SAM execution.
After each test script runs on the WN, the results are published directly to the SAM Server using a web service. It is done in this way in order to be able to have partial results from the tests even when the job fails to finish after a successful submission. The contacted web service on the SAM
Server stores the results in a local ORACLE/MySQL database. During the time of the test run or after the test has finished, the SAM administrator can publish intermediate or final results on the
SAM website.
1.2.2
Grid enabled applications and existing communities
CIVET, …..NEUGRID….HEALTHGRID…
NEUGRID - CIVET application
NEUGRID and Civet are related to the early diagnosis of the Alzheimer disease
Porting applications on the Grid and new communities
Whatever fits in here…
SPM Applications
Although
18
FDG-PET has been used to study neurodegenerative disease for over two decades, its diagnostic potential has not been fully exploited. Most studies have been devoted to understand the biology of dementia and are inadequate to assess or demonstrate clinical utility (Gill et al.
, 2003).
The evaluation of a diagnostic test relies upon individual, rather than group differences from a reference population and is assessed with statistical measures such as sensitivity, specificity, predictive value, and likelihood ratio. These measures apply in fact to a single diagnostic comparison. Nowadays, simple visual inspection of the brain scans obtained by PET are no longer acceptable for diagnostic purposes because of the potential lack of crucial information and often misleading results. Unbiased methods for the detection of functional abnormalities in subjects with neurodegenerative disease are nowadays mandatory. The automatic detection of abnormal brain metabolism on individual PET scans requires appropriate reference data sets, spatial normalization of scans, statistical algorithms (to compare the voxels in scan data with normal reference data), and suitable display of the results.
Signorini et al. (1999) demonstrated that this can be achieved by adapting the Statistical Parametric
Mapping (SPM) software package that was developed at the Wellcome Institute, London, U.K., originally for analysis of activation studies. Noteworthy, the sum of abnormal t-values in regions that are typically hypometabolic in AD has been used as an indicator with 93% accuracy (Herholz et al. 2002). The same accuracy was achieved even without image reconstruction by a special pattern extraction technique from PET sinograms (Sayeed et al. 2002). Furthermore, several discrimination functions combined with principal component analysis or partial least-squares have
been proposed and tested for discrimination between AD and FTD in a sample of 48 patients with autopsy-confirmed diagnosis and achieved accuracies between 80% and 90% (Higdon et al.2004).
Furthermore, discriminant functions derived by multiple regression analysis of regional data achieved a 87% correct identification of AD patients versus controls, and a neural network classification method arrived at 90% accuracy, however, showing less accuracy than the above mentioned SPM method.
In addition to SPM, other methods and software packages have been developed and made available providing support for voxel-based approaches. As an example, a commercial software package, 3D-
SSP or NEUROSTAT, has been used successfully to identify metabolic alterations in dementia and mild cognitive impairment (MCI) (Ishii 2001, 2003, Drzezga 2003). These methods are based upon the detection of abnormal voxels or upon automatic recognition of the typical anatomical distribution of metabolic abnormalities in AD and not on a comparison with normal subjects. Thus users should take care to check the validity of their results with a comparison with normal reference data.
Noteworthy, a recent study demonstrated that accuracy and confidence (Foster et al.,
18
FDG-PET significantly increases diagnostic
18
FDG-PET Improves Accuracy in Distinguishing
Frontotemporal Dementia and Alzheimer's Disease. Brain, in press). This paper shows the utility of
18
FDG-PET in distinguishing between AD and FTD using data from patients with neuropathologically confirmed diagnoses. In detail, the authors compared the inter-rater reliability, test characteristics, and diagnostic accuracy of three clinical methods of assessments derived from medical records, and two methods of displaying 18 FDG-PET data. After having selected the best method of displaying
18
FDG-PET data for interpretation, they evaluated whether
18
FDG-PET might provide any diagnostic benefits when it is added to the patient’s clinical history and examination.
The Voxel-based interpretation of 18 FDG-PET images was superior to clinical assessment and had also the best inter-rater reliability and diagnostic accuracy of 89.6%. It also had the highest specificity (97.6%) and sensitivity (86%), and positive likelihood ratio for FTD. The authors conclude that
18
FDG-PET voxel-based analysis is valuable in differentiating AD and FTD, particularly when findings in a clinical evaluation are not definitive and physicians are not already highly confident with their clinical diagnosis. This work demonstrates the addition of
18
FDG-PET to clinical summaries to increase diagnostic accuracy and confidence for both AD and FTD.
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Dougall N, Nobili F, Ebmeier KP for the European Commission Framework 4: “SPECT in dementia”,
BMH4 98 3130. Predicting the accuracy of a diagnosis of Alzheimer's disease with 99mTc HMPAO single photon emission computed tomography. Psychiatry Res 2004; 131/2:157-168.
The IBFM-CNR unit has already developed and implemented a national centralized web SPM service, “GriSPM” specifically designed for the remote processing of clinical SPECT and PET neurological images [1-4]. The proposed SPM service was implemented as an open-to-authorized user, Grid-based web service including: (a) remote access to Grid-distributed databases of SPECT and PET images of normal subjects numerically appropriate for statistical analysis, and (b) a noncommercial, free, Grid-distributed computationally efficient SPM version, tailored for the analysis of brain images in neurological diseases (GriSPM). A Grid distributed database was configured providing access to SPECT/PET images of normal subjects at different hospitals/centres selected as Grid Repository Nodes. Two databases of normal images (SPECT and PET) provided by the Nuclear Medicine Department of San Raffaele Scientific Institute (HSR), Milan (Italy), are available on the Grid Repository Node of DIST – Genoa University. The normal subjects comprised
19 volunteers (10 men, 9 women; age range 21–75 years) and 21 volunteers (11 men, 10 women, age range 21–74 years) recruited for SPECT and PET, respectively. Volunteers were cognitively evaluated by experts using neuropsychological batteries and gave their informed consent to participate in the study. SPECT scans were performed using a Millennium VG SPECT system
(General Electric) with a scan time of 25 min, 30 min after injection of 99mTc-ECD (0.4 mCi/kg patient weight) as required by a conventional neurological acquisition protocol. SPECT acquisition parameters were: low-energy high-resolution collimator, 20 cm rotation range, 120 projections,
128×128 acquisition matrix. SPECT images were reconstructed using a filtered back-projection algorithm: zoom 1.5, filter x,y,z Butterworth (0.5–10) into an image volume of 128×128 (max 70) voxels, 2.94×2.94×2 mm pixel size. PET scans were performed using a 3-D PET Discovery LS system (General Electric) with a scan time of 15 min, 45 min after injection of 18F-FDG (1 mCi/10 kg patient weight) as required by a conventional neurological acquisition protocol. PET images were reconstructed using a 3-D reprojection algorithm (Axial filter: ramp 8.5) into an image volume of 128×128×35 voxels, 2.5×2.5×4.25 mm voxel size, over a field of view of 25×25×14.5 cm.
GriSPM was validated by physicians and physicists with SPM expertise at HSR (user site). GriSPM software was validated by comparing the results of the original SPM and of GriSPM. Evaluators agreed on the consistency of the two methods in showing comparable statistical t maps in each
patient. Chi-squared statistical comparisons between original SPM and GriSPM maps showed excellent agreement for all SPECT and PET patients. Evaluators tested the performance of the
GriSPM service in terms of ease of use and quality of results (score 1, low; 2, medium; 3, high). All users gave maximum scores (3) to the GriSPM service for easy of use and quality of results. The
GriSPM service is available together with the Gridbased databases of both SPECT and PET images of normal subjects online at www.neuroinf.it
(user “Doctor”, section “Statistical analysis of SPECT and PET images”). Authorized users upload SPECT/PET neurological studies to the site and perform SPM analysis through the browser on the Grid-based website.
1) S. Scaglione, I. Castiglioni, E. Molinari, F. Cesari, A. Schenone, M. C. Gilardi, F. Beltrame.
Neuroinformatics portal as knowledge repository and e-service for neuroapplication and data mining. Proceedings of Mediterranean Conference on Medical and Biological
Engineering (MEDICON), Ischia, 2004.
2) Cesari F, Molinari E, La fortuna C, Abutalevi J, Castiglioni I, Perani D, et al. An Italian portal of neuroinformatics: www.neuroinf.it
. Q J Nucl Med 2004;48(3):157. Eur J Nucl Med
Mol Imaging (2009) 36:1193–1195
3) S. Bagnasco, F. Beltrame, B. Canesi, I. Castiglioni, P. Cerello, S. C. Cheran, M. C. Gilardi,
E. Torres Lopez, E. Molinari, A. Schenone, L. Torterolo. Early diagnosis of Alzheimer's disease using a grid implementation of statistical parametric mapping analysis.
in Stud.
Health. Technol. Inform., edited by V. Hernandez, I. Blanquer, T. Solomonides, V. Breton and Y. Legre’, 2006; 120: 69-81.
4) I. Castiglioni, B. Canesi, A. Schenone, D. Perani, M.C. Gilardi. A Grid-based SPM service
(GriSPM) for SPECT and PET neurological studies . Eur. J. Nucl. Med. Mol. Imag., 2009;
36: 1193-1195.
.
EEG Applications
1.2.3
Training and tutoring
Collaboration with other initiatives in EGEE and ICEAGE, etc.
1.3
Methodology to achieve the objectives of the project, in particular the provision of integrated services
1.4
Networking Activities and associated work plan
[A detailed work plan should be presented, broken down into activities which should follow the logical phases of the implementation of the project's Networking Activities, and include consortium management and assessment of progress and results. (Please note that your overall approach to management will be described later, in section
2).
Please present your plans as follows1:
1
The first WP under this section should address the management related activities of the project and the costs relevant
Describe the overall strategy of the work plan.
Show the timing of the different WPs and their components (Gantt chart or similar).
Provide a detailed work description broken down into activities:
Activity list (please use table 1.3a);
Deliverables list (please use table 1.3b);
Description of each activity, and summary (please use table 1.3c)
Summary effort table (please use table 1.3d)
List of milestones (please use table 1.3e)
Provide a graphical presentation of the components showing their interdependencies (Pert diagram or similar)
Notes:
The number of activities used must be appropriate to the complexity of the work and the overall value of the proposed project. The planning should be sufficiently detailed to justify the proposed effort and allow progress monitoring by the Commission.
Any significant risks should be identified, and contingency plans described.]
1.4.1
NA1 – Management of the CP-CSA Project
[GARR, Laura Leone]
Efficient management ..
Tasks
1.4.1.1.1
TNA1.1 – Administrative Management of the Project
GARR
The structure will take into account the specific needs of a CP-CSA project. The management structure and procedures are described in…
1.4.1.1.2
TNA1.2 – Technical Management of the Project
FBF
For managing the Technical Activities a lightweight structure could be the following:
A Technical Board (TB): made up by the managers of all the activities (JRA, NA, SA).
A Technical Manager (TM): proposed by the PD and nominated by the PMB, will chair the
TB and deal with the day by day technical discussions curing the coherence of all the technical actions in the view of the project’s objectives. It should be one of the members of the EMB.
1.4.1.1.3
TNA1.3 – Quality Assurance
MAAT
Quality Assurance will be a crucial component…
..
..
Deliverables and Milestones
Del. No.
NA1.1
NA1.2
NA1.3
NA1.4
Table 1 - List of Deliverables of NA1
Deliverable name Nature
Kick-Off Meeting
Quality Assurance procedures
First Year Report
Final Report
Meeting
Document
Report
Report
Dissemination level
PU/CO
PU
CO
CO
Delivery date
(proj. month)
1
12
24 to this WP should be reported in the "Management" column of the appropriate A-form. The remaining costs should be reported under the “Co-ordination” column of the appropriate A-form.
Milestone
Number
M1.1
M1.2
Milestone
Name
Kick-Off meeting
Budget Plan assessment
Table 2 - List of Milestones of NA1
Activity(ies)
Involved ?
Meeting
Assessment of costs and work
PM1
PM15
Expected
Date
Resources
Table 3 - Staff effort of NA1
Participant number
1
2
Participant short name
GARR
FbF
Total person months
..
..
Quality metrics
Risk analysis and contingency plans
Means of verification
Quarterly Report
Quarterly Report
1.4.2
NA2 – Standardization, Liaison and International Cooperation
FBF
This activity will deal with standardization… ….
International research collaboration is a rapidly growing component of core research activity for all countries. It is driven by a consonance between top-down and bottom-up objectives. The consortium of the DECIDE project aims at encouraging international collaboration both at a research and a policy level because it thinks it could provide access to a wider range of resources and facilities and enables researchers both to participate in networks of cutting-edge and innovative activities and to move further and faster by working with other leading people in their field.
Objectives and expected outcomes
Tasks
Activities are organized into five main tasks.
TNA2.1 – Harmonization to EGI standards
TNA2.2 – Medical data collection
TNA2.3 – Scientific International Collaboration , dealing with the research, the identification and the involvement of International Partners with interest and expertise in areas relative to the project.
(CNR)
TNA2.4 – Geant Collaboration and support to provide networking infrastructure
TNA2.5 – Development assistance to patients communities in less advance regions
…
In the following paragraph, a detailed description of the Workplan for each task is given.
1.4.2.1.1
TNA2.1 – Harmonization to EGI standards
COMETA
Whatever ..
1.4.2.1.2
TNA2.2 – Medical Data Collection
IC?
Indeed…
1.4.2.1.3
TNA2.3 – Scientific International Collaboration
CNR
This task aims at promoting and activating collaboration programs with Scientific International Partners. The object of this task fits well with the
Lisbon Strategy of the European Community and is strategic as it contributes to some of the highest impact activity by inducing to open the European research efforts of the DECIDE project to the rest of the world and to develop extensive programmes of international scientific and technological cooperation. To this purpose several actions and strategies will be carried out by the consortium.
To open the project to the international scientific partners already collaborating with partners the consortium , taking the advantage of the large and interdisciplinary
composition of the consortium and of the already formalized collaborations. Among the potential institutions which might have interest in the project: The Center for Mind and
Brain, University of California, Davis (USA); The Center for Cognitive Neuroscience, Duke
University, North Carolina (USA); The Department of Cognitive Neuroscience, UCSD, San
Diego, California, USA; The Department of Brain and Cognitive Neuroscience,
Massachusetts Institute of Technology, Cambridge, Massachussets, USA; The International
School for Advanced Studies (ISAS), Neurocognitive Science Section, Trieste (Italy); …
To open the project to international scientific groups as new potential collaborations with the consortium . This activity will be covered in close collaboration with the TNA3.1
(Dissemination), for scientific cooperation across the interdisciplinary area of the projects, and in close collaboration with TNA3.3 (Outreach to the Medical Community) for the medical area in particular. As an example the project might open to other e-services (with the purpose to enrich DECIDE with other diagnostic algorithms and with other reference database on Grid repositories) and other clinical end users (with the purpose of a more complete validation and of an enlargement of the clinical database). Actions developed within this task, in cooperation with TNA3.1 and TNA3.3, will represent effective chances for fruitful contacts with potential scientific partners. International collaborations will be favored through the DECIDE website, by making collaborative tools for multi-centric cooperation available. Calls for international collaborations might also be set up, on specific topics and when considered appropriate. These collaborations will be selected according to criteria which will depend on the specific purpose of the call.
To link the DECIDE project to international projects.
This activity will be responsible to create synergies between the DECIDE project and other international projects. To note, partners of the consortium are already involved in several EU and non EU funded projects which might be of interest for the DECIDE [NeuGRID (www.neugrid.eu),
ADDNEUROMED (www.innomed-addneuromed.com/), ADNI
(http://www.loni.ucla.edu/ADNI/), CBRAIN (http://cbrain.mcgill.ca/), EADC
(http://eadc.alzheimer-europe.org/), LONI (http://www.loni.ucla.edu/), Brain Tuning
(http://www.braintuning.fi/), … ]. Sharing of aims and contents of akin projects represent powerful stimulus for the enlarging of the DECIDE scenario with respect to both scientific and impact point of view.
To adhere to international bilateral cooperation programmes (exchange of researchers) .
Some partners of the consortium participate into specific bilateral projects between
European and non European Nations with the purpose to promote the exchange of researchers between the different countries. Among these programmes: “Methodical and computation improvements in order to optimize hybrid SPECT CT Imaging” (Italy-
Unghery); … Opening the project to such international collaborations might contribute both in terms of dissemination and training.
To involve international research professionals within the project Senior researchers might contribute to the project with their expertise and their personal research. Young investigators might actively contribute to the project by their specific skills.
1.4.2.1.4
TNA2.4 - Geant Collaboration and support to provide networking infrastructure
GARR
Blab…
1.4.2.1.5
Task NA2.5 Development assistance to patients communities in less advanced regions
FBF or CNR
Blab…
Deliverables and Milestones
Del. No.
D2.1
D2.2
D2.3
D2.4
D2.5
Table 4 - List of Deliverables of NA2
Deliverable name
..
..
..
..
..
Nature
Other
Other+report
Report
Other
Report
Dissemination level
Public
Public
Public
Public
Public
Delivery date
(proj. month)
PM..
PM..
PM5, PM15
PM6
PM10, PM20,
PM30
Milestone
Number
MNA2.1
MNA2.2
MNA2.3
MNA2.4
MNA2.6
MNA2.5
Milestone
Name
Project website available
..
..
..
..
..
Table 5 - List of Milestones of NA2
Activity(ies)
Involved ?
Design and implementation of the first version of the website
Design and implementation of the complete website; installation, configuration and customization of tools
Design, content editing, production of multi-lingual project dissemination materials
Organization and delivery of international dissemination event
Revision, update and enhancement of existing dissemination materials
Organization and delivery of international dissemination event
Expected
Date
PM1
PM4
PM6
PM10
PM15
PM20
Means of verification
Website online and working
Full version of the website available; online tools operating.
Basic set of multilingual dissemination materials available to partners
The event takes place
New/updated materials available
The event takes place
Resources
Table 6 - Staff effort of NA2
Participant number
Participant short name
GARR
COMETA
MAAT-C
..
..
..
Other partners ..
Total person months
..
..
The main partners involved so far in the activity are:
GARR, which will lead the activity and provide effort mainly on the following: coordination of underlying network layer
COMETA providing computing and storage
…
Yes..
Quality metrics
Quality metrics in this context are multi-folded and involve quantitative and qualitative indicators. the collected information may be analyzed in order to improve it whenever possible:
Usage statistics for the website and collaborative tools;
Number and provenance of attendees for the international and national/local events;
Number and variety of dissemination materials given out during dissemination events and other appropriate occasions.
Number of issued press releases and their follow up;
Number and quality of press cuttings mentioning the project and its activities;
Number of conferences, meetings, workshops, exhibitions and other events where DECIDE is represented.
Number of relevant contacts collected amongst different audiences (press, potential users, politicians, companies, sponsors).
Risk analysis and contingency plans
The major risk envisaged for dissemination activities is the lack of a pool of (potentially) interested people large enough to ensure the success of the events.
Risks will be envisaged the direct intervention of the Project Office and/or the organizing partner to solve this kind of issues.
NA3 – Dissemination, Training and Outreach (Activity Leader: COMETA)
The activities in this work package are strategic to ensure the visibility of the DECIDE project and achievements, as well as of the services offered, to the medical community in its framework. This visibility is in turn important for stimulating the adoption and use of the DECIDE infrastructure and diagnostic service (outreach towards potential users), and for ensuring its longer-term sustainability
(dissemination to decision makers and the general public).
This WP will set out the overall Dissemination, Training & Outreach plan, monitor its progresses, assess the results and propose corrective measures if needed. To achieve this objective, the NA3 team will work in close collaboration with the project management and the PO.
This activity will disseminate the project results and provide targeted training to potential users.
Specific activities to promote the infrastructure and its benefits to the Medical community are also envisaged.
Several target audiences will be addressed within the scope of NA3: a) The (prospective) users, in order to reach a critical mass using and exploiting the DECIDE diagnostic service;
b) IT professionals, experts in Medical Physics, Mathematicians who deal with diagnostic algorithms, in order to multiply the centers of expertise and further expand the DECIDE diagnostic service with other applications; c) Press, the Scientific community at large and the general public in order to create interest and consensus on the results and indirectly facilitate the sustainability of the initiative beyond the project lifetime; d) Governments, national/international funding agencies and private companies, to create awareness and seek possible sources of funding to sustain the DECIDE diagnostic service in the longer term.
Activities are organised into three main tasks:
TNA3.1 – Dissemination, dealing with the dissemination of the project results to the neurological community, as well as the wider R&E community and the general public.
Decision makers and possible sources of complementary/alternative funding will be as well targeted in order to seek possible to ensure sustainability to the initiative.
TNA3.2 – Training , which will deliver targeted training activities to end-users, grid administrators and application developers, thus enabling them to make the best use of the DECIDE e-Infrastructure. The main aim of this task will be to facilitate the adoption of the DECIDE services and applications by clinicians.
TNA3.3 – Outreach to the Medical Community , responsible for the promotion of the DECIDE infrastructure and applications to the Medical Community, through targeted outreach events and materials. The task will identify and address new potential users in the target community and will act in close coordination with TNA3.2 to induce new users to adopt the DECIDE suite.
In the following paragraphs, a detailed description of the work plan foreseen for each task is provided.
1.4.2.1.6
TNA3.1 – Dissemination
A preliminary work will identify key concept and messages for DECIDE. During this phase a consistent look-and-feel for all materials will be elaborated as well.
The task will be as well responsible for the following actions:
Design, set-up and management of the website and collaborative tools. The DECIDE website is one of the major media for disseminating the project, and the virtual place where project partners, users and potential users may find information on the status of the works, reference materials etc. The main website will be enriched and complemented by a number of dynamic tools, which are intended to build, widen and support the DECIDE user community. These will include: collaborative wiki, online calendar, CMS with user profiling functionalities, thematic lists or forums, project document repository, user support system, including a knowledge base for common issues.
Production of dissemination material: during the project lifetime, a number of dissemination materials will be produces. The list of possible items covers (but is not limited
to): one or more project information sheet or booklet; one or more project posters; the collection and publication of success stories (leaflets, mini-interviews); general project presentations (ppt, html etc) to be customized; banners and other materials to be used in exhibitions.
Organization of DECIDE conferences: one conference per year will be organised in order to disseminate the project. Conference organization activities will include both logistics
(venue, transportation, accommodation, facilities, added-value services for the attendees), the design of the programme and the speakers’ management, inviting appropriate speakers/demonstrators; fund raising activities (sponsorships etc) may be also envisaged to help securing an adequate budget for the conference.
Participation to conferences and external events: this subtask will take care of identify external events where the project can be represented and ensure an appropriate participation.
Given the multi-layer approach carried out in DECIDE, both e-Infrastructures-related events and scientific ones addressing the neurological community are relevant. The latter type of dissemination, which focuses much more on scientific content, will be covered in collaboration with the TNA3.3.
Press relations: press releases, media briefings and/or other press relations (individual interviews etc) will be organized in order to announce major achievements in the project’s life. The objective of this action is to ensure the publishing of general articles on newsletters, portals, newspapers, magazines, etc; the publication of scientific papers will be also monitored, but it is out of the scope of this activity (see above).
TNA3.1 will begin with the project itself and go on for the whole duration of the project, with peaks of activity in the first months (identification of key messages, draft of the strategic plan, creation of the project’s look&feel, design and implementation of the public website) and others to coincide with the organization of the two largest events. It will mainly involve expert editors and technical writers, event managers, PR personnel to maintain press relations. Professional artwork (in-house or outsourced) and system support for the implementation of the website and online collaborative tools will be needed as well.
1.4.2.1.7
TNA3.2 – Training
The knowledge dissemination process guided by the training activities is very important to ensure that all users can acquire enough expertise to properly use the available infrastructure and can fully understand the characteristics of the services offered. The training courses will be addressed to several types of audiences - users, applications developers and system administrators - with different levels and areas of knowledge, ranging from novice to advanced. The training events will be divided into:
Training for grid administrators , where the attendee will learn how to manage a site or a set of services, how to know in depth the middleware internals and the way to deal with the most common technical problems and solve it and of course how to maintain the e-
Infrastructure behind the offered services. To the training courses will be accepted also
people not directly involved in the project but interested in learning how to contribute to the
DECIDE community
Training for application developers, where application developers and experts work in close collaboration with tutors to interface their applications with the services and run them on DECIDE infrastructure. These kind of events will be of the uppermost more important to speed up the process of application porting or new applications developing by the various scientific communities.
Training for end-users , where will provide to them a comprehensive introduction on the usage of the infrastructure’s service and all the required steps required to actually make use of its capabilities. In these events, the technical notions on the infrastructure will be contained to their minimum, given more space as possible to the services usage and mostly in practical way with focused hands-on sessions.
To fulfill these goals the task will work on:
The training material to be used, adapting existing material made available from other projects where possible, developing completely new material elsewhere and maintaining the material permanently update
The planning of training events (in cooperation with SA, JRA, NA activity), for the realisation of technical roadmap and to design a sustainable working model for the propagation of the project’s benefits within Medical communities
The organization of training events to ensure large and successful participation (in joint collaboration with NA3.1 team), placing attention to the location and to the instrumentation needed .
TNA3.2 will begin with the project itself and go on for the whole duration of the project. In the first
6 months of the projects the activity will be focused on the training of the grid administrators and of the application developers.
After the activity will be focused on developing training material for the users and in providing them the needed training. Some of the users will be involved in training themselves as trainers to support the project in quickly spreading the knowledge and the updates through the community formed around the project.
In this second phase, that will last till the end of the project lifetime, some more training for grid administrator and applications developers will be provided just to spread knowledge of the updates and to form other people interested, from the project and outside.
1.4.2.1.8
TNA3.3 – Outreach
This task will deal with all the activities related to promote the DECIDE infrastructure, its service and applications to the Medical Community. To achieve these purpose we plan the following activities:
1.
Organization of thematic workshops/User Forum, where success stories, use cases of applications that make use of the DEDICE services and its applications will be showed, demonstrating how medical users can take advantage of the infrastructure in their everyday work and how this could represent a plus in their scientific activities. Users already involved
can use this events to advertise and show case their activities and results, with presentations, posters or demonstrations.
2.
Creation of a Digital Libraries for applications, publications and works, where all the documents, such as publications, articles, posters, short papers, produced by the user communities can be collected and browsed by anyone. This could represent a good source of inspiration for new users.
3.
Targeted meetings on-site, where experts of the infrastructures and applications can meet face-to-face a specific community to show them how the DECIDE suite can improve their activities.
The number of workshops will determined by the community interests and limited by the organization expenses, but at least two events per year will be guaranteed.
Table 7 - List of Deliverables of NA3
Del. No.
D3.1
D3.2
Deliverable name Nature
Other
Other
Dissemination level
Public
Public
Delivery date
(project month)
PM1
PM3
D3.3
D3.4
D3.5
D3.6
D3.7
D3.8
D3.9
Project presentation
Project website and collaborative tools
Dissemination plan
Project press kit
Report on dissemination activity
Training plan
Report on dissemination activity
Outreach Digital
Repository
Report on outreach activies
Report
Other
Report
Report
Report
Report
Report
Public
Public
Public
Public
Public
Public
Public
PM3, revPM12
PM6
PM12, PM24
PM3,rev PM12
PM12, PM24
PM3
PM12, PM24
Milestone
Number
MNA3.1
MNA3.2
MNA3.3
MNA3.4
Milestone
Name
Project website available
Full public website and collaborative tools available
Table 8 – List of Milestones of NA3
Activity(ies)
Involved
Design and implementation of the first version of the website
Design and implementation of the complete website; installation, configuration and customization of tools
Expected
Date
PM1
PM3
Outreach digital library available
Installation, configuration and customization of the digital library
PM3
Press kit Design, content editing, PM6
Means of verification
Website online and working
Full version of the website available; online tools operating.
Digital Library frontend online and browsing/download/u pload of sample document
Initial set of project
MNA3.5
MNA3.6
MNA3.7
MNA3.8
MNA3.9
MNA3.10
MNA3.11
MNA3.12
MNA3.13 production of project dissemination materials
DECIDE
Workshop
1 st DECIDE conference
DECIDE User
Forum
Revision of dissemination materials
2 nd large dissemination event
Training material on collaborative tools available
Mini workshop on training the trainers
Use Cases and project application scenarios
Revision of training material
Organization and delivery of the first workshop event
Organization and delivery of international dissemination event
Organization and delivery of the first user community event
Revision, update and enhancement of existing dissemination materials
Organization and delivery of international dissemination event
Revision and update of existing training material with eventually new creation one
Organization and delivery of the first training event for traineers
Set of project applications integrated and available to describe and promote during training event for developers as use cases of application porting
Revision and update of existing training material with eventually new creation one
PM6
PM12
PM18
PM12
PM24
PM3
PM4
PM12
PM12
1.4.2.1.9
Resources dissemination materials available to partners
The event takes place
The event takes place
The event takes place
New/updated materials available
The event takes place
New or update training material available to users
The event takes palce
At least 5 use case application fully described
New or update training material available to users
Table 9- Staff Effort for NA3
The main partners involved in the activity are:
- COMETA, which will lead the work package and TNA3.2, and provide effort mainly on the following
- GARR, which will lead TNA3.1, and provide effort mainly on the following: coordination, web design, editing & management, content editing, event management.
TNA3.1 - The overall manpower needed for the task is estimated in at least 1 FTE. Travel and subcontract budget is as well required for the organization of conferences and participation to external ones.
Some of the low-level activities, such as the reception of delegates at conferences, etc may be outsourced in order to streamline the process.
Other resources to be made available by the responsible partner are a server to host online tools and services, plus appropriate software licenses for web developing, professional graphics, editing of multimedia materials etc.
1.4.2.1.10
Quality metrics
Quality metrics for evaluating the performance of dissemination are multi-folded and involve quantitative and qualitative indicators. Although the latter are not easily measurable, they include some key factors for the success of dissemination, which cannot be overlooked, such as the quality of content as well as its adherence and appropriateness to the target audience. These aspects will be ensured thanks to the appointment of staff expert in popularizing science and technology, and to a close collaboration with the Technical and Scientific Manager and the Technical Board. As to measurable indicators, the following will be used to evaluate the dissemination performance; the collected information may be analyzed in order to improve it whenever possible:
Usage statistics for the website and collaborative tools;
Number and provenance of conference attendees;
Number of dissemination materials produced;
Number of information/dissemination materials given out during events or downloaded from the web;
Number of issued press releases;
Number of publications, proceedings, posters, papers, demo produceced;
Number and quality of press cuttings mentioning the project and its activities;
Number of conferences, meetings, workshops, exhibitions and other events where DECIDE is represented.
Number of relevant contacts collected amongst different audiences (press, potential users, politicians, companies, sponsors).
Number of training materials produced
Number of training events delivered
Number of trained users
Rank achieved in the user’s evaluation of the training
Number and quality of scientific publications
One way of measuring in a quantitative way the success of NA3.2 training activity is to keep track of the number of participants enrolled in training events as well as the number of participant per· days delivered, i.e., i
n i
1
P i
D i
P
, where i
D
is the number of participants of the tutorial i and i is its duration (in days). The success thresholds are put at 400 participant · days by the end of the first year and 800 participant · days by the end of the project.
The average feedback evaluation given by the students at the end of each tutorial (in a scale from 1 to 6) will constitute another important metric. The gathered results will be analysed in order to guide course improvements. A summary statistics will be published as a key performance indicators every 6 months. The success threshold is put at an average rate of 4.5 out of 6.
1.5
Trans-national Access and/or Service Activities, and associated work plan
2
[A detailed work plan should be presented, broken down into activities (WPs) which should follow the logical phases of the implementation and provision of the project's Trans-national Access and/or Service Activities, and include assessment of progress and results.
Please present your plans as follows:
Describe the overall strategy of the work plan.
Show the timing of the different WPs and their components (Gantt chart or similar).
Provide a detailed work description broken down into activities:
• Activity list (please use table 1.3a);
• Deliverables list (please use table 1.3b);
• Description of each activity, and summary (please use table 1.3c)
• Summary effort table (please use table 1.3d)
• List of milestones (please use table 1.3e)
• Connectivity services cost table (if applicable, please use table 1.3f)
Provide a graphical presentation of the components showing their interdependencies (Pert diagram or similar)
Notes:
The number of activities used must be appropriate to the complexity of the work and the overall value of the proposed project. The planning should be sufficiently detailed to justify the proposed effort and allow progress monitoring by the Commission. Any significant risks should be identified, and contingency plans described.]
1.5.1
SA1 – Installation and Maintenance of the enabling network and grid infrastructure
MAAT
Objectives and expected outcomes
Tasks
1.5.1.1.1
TSA1.1 – Networking provision, operation and support
GARR
The DECIDE project infrastructure is made of different technical layer: network, GRID and application layer.
This activity, SA1.1, will deal with the network infrastructure layer. All partner sites involved in the project will be connected to an international infrastructure, partly already developed.
Thinking of the state-of-the-art of Scientific Research and Health Care Institutes (IRCCS) network in GARR infrastructure, the scope of SA1.1 activity will be the collection of new requirements in term of network connectivity and service. This action will produce in some cases the provision of new links and in other case an upgrade of existing link.
After collecting, from all the technical parties, the specific requirements, the analysis process will produce a list of new technologies and new features to implement in the network infrastructure.
It will be used software tools, already available in GARR network, in order to monitor and to collect network performance. This will represent a key feature in the provisioning process because it will be possible to check the real correspondence to the application requirements.
Scope of this task is also the harmonization of the operational activities in the national but also in the paneuropean network infrastructure. In fact SA1.1 is aimed to coordinate operational activities in order to apply in a time-effective way all available tools to manage network fault and to implement technical solution.
1.5.1.1.2
TSA1.2 – Grid infrastructure provision, operation and support
COMETA
2
Regarding Trans-national Access, an updated version of this Guide for Applicants will be made available at the time of the next call that will involve these activities and will address this more specifically.
1.5.1.1.3
TSA1.3 – GUI deployment and user support
UGDIST
1.5.1.1.4
TSA1.3 – Software Release Management
MAAT
Deliverables and Milestones
Del. No.
Table 10 - List of Deliverables of SA1
Deliverable name
Nature Dissemination level
Table 11 - List of Milestones of SA1
Milestone
Number
Resources
Milestone
Name
Activity(ies)
Involved ?
Expected
Date
Table 12 - Staff effort of SA1
Participant number
Participant short name
Total person months
Quality metrics
Delivery date
(proj. month)
Means of verification
Risk analysis and contingency plans
1.5.2
SA2 – Design, exposure of and access to the reference databases
IC
SA2 activity will define and design the relational MRI (TSA2.1), PET (TSA2.2), and EEG
(TSA2.3) reference database as a platform for the diagnostic/prognostic services (see JRA2 -
Design of the Diagnostic Service) to be used by the medical community involved in the assessment of elderly subjects with cognitive decline and suspect of Alzheimer’s disease (AD). The reference databases will be used by the following target users:
1.
Neurologists, acting at the beginning and at the end of the neurological diagnostic process, which meet patients presenting cognitive disorders, require laboratory tests, neuropsychological assessments as well as morphological and functional measurements and make their diagnosis by combining the response of all these tests;
2.
Doctors acting within the neurological diagnostic process, as radiologists, nuclear medicine doctors, neuro-physiologists which provide to neurologists diagnostic information indicative of the presence/absence of a neurological diseases;
3.
Scientists dealing with diagnostic algorithms as Physicists, Mathematicians, Engineerings, which provide to both neurologists and doctors at any step of the diagnostic process quantitative or semi quantitative information supporting the presence/absence of a neurological disease.
Objectives and expected outcomes
(a) Define and implement the relational EEG reference database to be targeted by data analysis software within the grid-based e-infrastructure (GRID). This will make the EEG reference database available for the diagnostic/prognostic service (see JRA2 - Design of the Diagnostic Service).
(b) Validate the access to the relational EEG reference database by remote qualified users for the extraction of EEG biomarkers and for the production of the relative reports. This will make the
EEG biomarkers available for the diagnostic/prognostic service.
Tasks
1.5.2.1.1
TSA1.1 – Structural MR reference database
FBF
1.5.2.1.2
TSA1.2 – PET/SPET reference database
CNR
1.5.2.1.3
TSA1.3 – EEG reference database
UNIFG
The Task SA2 implies the following ACTIVITIES:
(a) Revise the aging EEG literature to define the most promising standardized protocols and quality control procedures for the selection of the artifact free EEG epochs to be used as an input for the extraction of the EEG biomarkers, namely the EEG segments free from electrocardiographic, head or mouth movements, blinking, and saccadic artifacts.
(b) Design, implement, and validate a relational EEG reference database. The general design and technology of the EEG reference database will be those of the MRI and PET-FDG databases of this
SA2 activity.
(c) Upload EEG datasets of 100 normal elderly subjects (Nold), 100 amnesic mild cognitive impairment subjects (MCI), 100 mild AD subjects. The datasets will refer to artifact free EEG epochs recorded in a resting state eyes-closed condition, which will be taken from two databases:
the database of a project granted by Italian Ministry of Health 2007 ("Diagnosis of incipient
Alzheimer disease: Development of ADNI-based imaging markers for use by the National Health
System") as well as the EEG archive of the UNIFG research unit.
Deliverables and Milestones of the Task SA2.3 EEG reference database
Table 13 - List of Deliverables of of the Task SA2.3
Del. No. Deliverable name Nature
TSA2.3 Report
Dissemination level
Internet users
Delivery date
(proj. month)
6
TSA2.3
TSA2.3
Standardized protocols and quality control procedures for the selection of the artifact free EEG epochs
Design, implementation, and validation of the relational EEG reference database
Uploading of EEG datasets of Nold,
MCI, and AD subjects
Database
Database
Qualified
Internet users
(UE)
Qualified
Internet users
(UE)
12
12
Milestone
Number
TSA2.3
TSA2.3
Milestone
Name
Table 14 - List of Milestones of JRA2
Activity(ies)
Involved ?
Release of the standardized protocols and quality control procedures for the selection of the artifact free EEG epochs
TSA2.3
Completion of the design, implementation, and validation of the relational
EEG reference database
TSA2.3
6
12
Expected
Date
Means of verification
Evaluation of the report
Access to the relational EEG database
TSA2.3 Completion of the uploading of EEG datasets in Nold,
MCI, and AD subjects
TSA2.3 12
Resources
Table 15 - Staff effort of JRA2
Participant number
Participant short name
Total person months
5 CNR-
IBFM
UNIFG
Quality metrics
Risk analysis and contingency plans
UNIFG
Access to the relational EEG database
1.6
Joint Research Activities and associated work plan
[A detailed work plan should be presented, broken down into activities which should follow the logical phases of the implementation of the project's Joint Research Activities, and include assessment of progress and results.
Please present your plans as follows:
Describe the overall strategy of the work plan.
Show the timing of the different WPs and their components (Gantt chart or similar).
Provide a detailed work description broken down into activities:
• Activity list (please use table 1.3a);
• Deliverables list (please use table 1.3b);
• Description of each activity, and summary (please use table 1.3c)
• Summary effort table (please use table 1.3d)
• List of milestones (please use table 1.3e)
Provide a graphical presentation of the components showing their interdependencies (Pert diagram or similar)
Notes:
The number of activities used must be appropriate to the complexity of the work and the overall value of the proposed project. The planning should be sufficiently detailed to justify the proposed effort and allow progress monitoring by the Commission.
Any significant risks should be identified, and contingency plans described.]
1.6.1
JRA1 – Porting of the diagnostic algorithms
UGDIST
The Grid is a distributed computing infrastructure that enables resource sharing within dynamic virtual organizations. Grid environments can help increase efficiencies and reduce the cost of computing networks by decreasing data processing time, sharing distributed data resources, optimizing resources and distributing workloads, thus allowing users to access remote data and services, and achieve much faster results on large operations and at lower costs.
However, for the Grid to become a well accepted computing infrastructure in clinical scenarios, it is necessary to provide web based platforms accessible through portals, providing services, algorithms, and applications that help users to leverage Grid capacity in supporting highperformance distributed computing and data storage for solving their problems in a distributed way.
It is worth noting that the component parts of a Grid application need not be executing within a single machine, but may be geographically distributed, each running in the most suitable place. On the other hand, we have to consider users interacting not with a single machine, but with a diverse collection of machines. This leads to requirements for systems hiding the infrastructure from nontechnical users and a Grid service accounting system which enables users to employ distributed services or have their own services run on distributed hardware.
A number of issues both on the data management side and on the computational requirements side arise for the Grid porting of applications in the biomedical domain.
As regards data related issues, the primary concern when distributing medical data over a Grid is privacy. Medical applications often deal with data that are confidential and should only be accessible to the patient himself, the medical team involved in his health care, and, under some restrictions, for research purposes. Therefore, a medical Grid, opened to a large community of users, should enforce strict access right control.
Another particularity of medical data is their strong semantic content. Often, medical data are not understandable or of low interest if are not related to a context (patient medical record, acquisition parameters, etc.). Tools to manipulate metadata attached to the data should be provided within the
Grid environment.
Another requirement for a medical data management system is traceability. It should always be possible to know, for a given result where it originates from (which algorithm and which input data were used). Indeed, physicians often need to come back to the original data when studying a
processed image or signal. Conversely, for each input data can be of interest, for optimizing computations, to record which output has already been processed using different algorithms.
From a computational point of view, medical application usually require more than a middleware offering batch job submission services and data access. A medical procedure often involves not a single algorithm but a set of processings that can sometimes be executed concurrently. Processing pipelines are compound jobs composed of several elementary stages. Pipelines are of real interest when processing a large number of input data rather than a single input. Through pipelines, the user can describe once for all the chain of transformations that each element of the input dataset should undergo. Connections between services should be double-stranded, with both control and data channels. The control channel carries metadata, control, and diagnostics, and may be bi-directional; the latter may carry big data in parallel, asynchronous streams, and is designed for maximum throughput.
As a further issue, some data processing, simulation, and modeling algorithms are computationally very intensive and need a parallel implementation in order to get executed in a reasonable amount of time compatible with clinical practice constraints. On the other hand, tailored optimization methods are needed in order to allocate and schedule resources in a computational grid. Actually, many existing parallel algorithms for optimization are not “parallel enough” to exploit the full power of typical grid platforms. Novel parallel approaches could be studied in order to provide efficient solutions and improve the overall system performance.
Finally, interaction with the user may be needed for controlling an algorithm, to solve legal issues when dealing with medical data, or for the application itself . Data compression and high-bandwidth networks should ensure a limited response time which is mandatory for interactive usage. And effective user interfaces must be designed and developed to provide users with tools for evaluating results and for inserting their knowledge in the process.
Activities are organised into four main tasks:
TJRA1.1 – Voxel-based analysis of FDG PET/SPET images, dealing with the implementation on the Grid infrastructure of the application.
TJRA1.2 – Pattern recognition of FDOPA-PET , dealing with the implementation on the Grid infrastructure of the application.
TJRA1.3 – Hippocampal segmentation on structural MR , dealing with the implementation on the Grid infrastructure of the application.
1.6.1.1.1
TJRA1.4 – EEG Algorithms, dealing with the implementation on the Grid infrastructure of the application.
In the following paragraphs, a detailed description of the Workplan for each task is given.
1.6.1.1.2
TJRA1.1 – Voxel-based analysis of FDG PET/SPET images CNR
GriSPM is a modified version of SPM specifically designed for the SPM analysis of SPECT and
PET neurological images without the need for local acquisition of normal studies and free from the use of commercial software (Matlab).
The Grid data approach (“move code rather than data”) was used for the implementation of the proposed SPM software in order to: (1) keep clinical data in the proprietary hospitals/centres
(forcing applications to access patient data, by processing jobs without moving files on the net), and
(2) allow access to distributed computational resources. This approach addresses the security and
property issues relating to accessing clinical data and optimizes the performance of computational algorithms.
Functional architecture of GriSPM is described in Figure 1.
Figure 1
1.
The User can access the GriSPM through the browser of the web site, after registration.
2.
A Grid Management Node (a web server with Grid middleware, GMN) provides User
Authorization and Service Certification procedures (Authorization by verification of specific requisites, e.g. having attended proper GriSPM training courses; X509 Service Certification by MyProxy delegation mechanism).
3.
The Authorized User (log in, password) at the User Node uploads to GMN the SPECT/PET images of patients to be evaluated. Files are anonymized and archived on the GMN into a
User-accessible directory. Only under User permission, patient files are stored into a database of pathological subjects with neurological diseases (Patient database) for further follow-up evaluation.
4.
The Authorized User accepts or modifies image pre-processing (SPM normalization and smoothing) parameters. Pre-processing parameters are sent to GMN.
5.
GMN runs patient pre-processing procedure and creates pre-processed patient images.
6.
The Authorized User at the User Node, through the browser, selects a number of normal images suitable for the comparison of interest.
7.
A query for normal images is sent from GMN to distributed Grid Repository Nodes (GRN, e.g. different hospitals proprietary of normal images).
8.
Part of the software useful to compute statistical analysis is sent, with a Grid job submission, from GMN to different Grid Worker Nodes (GWN, Computers with Grid middleware).
9.
GWN compute statistical data needed for SPM analysis by reading (no copying) the Userselected normal images.
10.
GWN return statistical information to GMN.
11.
GMN runs SPM analysis using statistical information and produces SPM results.
12.
The Authorized User, at the User Node, through the browser, downloads results of SPM analysis.
1.6.1.1.3
TJRA1.2 – Pattern recognition of FDOPA-PET IC
Short description of the application with special attention paid to data management and computational requirements related to the porting of the application on the Grid infrastructure.
1.6.1.1.4
TJRA1.3 – Hippocampal segmentation on structural MR FBF
Short description of the application with special attention paid to data management and computational requirements related to the porting of the application on the Grid infrastructure.
1.6.1.1.5
TJRA1.4 – EEG Algorthms UNIFG (DPB-UW)
Short description of the application with special attention paid to data management and computational requirements related to the porting of the application on the Grid infrastructure.
Goal of the task will be elaboration of EEG processing algorithms and porting them to the Grid environment with the aim of detecting early symptoms of Alzheimer disease and distinguishing different forms of degenerative impairment.
Nerodegenerative diseases cause structural and functional changes in brain. The functional impairment is connected to the large degree with changes in connectivity and hence in propagation of EEG activity. It has been demonstrated in earlier works that (1) the conversion from mild cognitive impairment to Alzheimer disease (AD) may be predicted by the study of coherence together with EEG source power density (Rossini et al.2006), and (2) estimation of directed synchronization is helpful in the diagnosis of AD (Babiloni et al. 2009). This evidence indicates that algorithms estimating functional connectivity and EEG source power density are helpful for early diagnosis of neurodegenerative impairment. The measures estimating functional connectivity are spectral coherences and Directed Transfer Function, which may be calculated efficiently from the multivariate autoregressive model. In the framework of the approach ordinary, partial and multiple coherences may be found, which give information on the degree of synchronization in a small and a large scale. Directed Transfer Function (DTF) determines the propagation of EEG activity as a function of frequency and indicates the localization of the sources of activity ((Blinowska and
Kaminski, 2006). The advantage of the method in comparison to the other approaches is robustness in respect to noise – the correct pattern of transmissions may be found even in the presence of noise of the amplitude comparable with the signal itself. Non-normalised version of DTF is directly proportional to the degree of coupling between the relevant structures. The measures estimating
EEG source power density are obtained by the popular freeware low resolution brain electromagnetic tomography (LORETA) that can be downloaded from http://www.uzh.ch/keyinst/loreta.htm
. Grid porting of the above algorithms will give the access to the efficient and verified algorithms estimating synchronization and transmission in brain to the large community of users and will help in early diagnosis of neurodegenerate impairments.
Note that in this workpackage, the role of UNIFG can be contribute to the porting of LORETA in the neurogrid.
Standard operating procedures (SOPs) providing qEEG markers of AD such as power density and coherence of resting (eyes-closed) EEG cortical sources.
Cortical source analysis of EEG rhythms by LORETA
LORETA software as provided at http://www.unizh.ch/keyinst/NewLORETA/LORETA01.htm will be used for the estimation of cortical sources of EEG rhythms. LORETA is a functional imaging technique belonging to a family of linear inverse solution procedures modelling 3D distributions of
EEG sources, which has been successfully used in recent EEG studies on brain aging (Dierks et al.,
2000; Babiloni et al., 2004, 2006a,b,c,d,e, 2007, 2008a,b, 2009).
LORETA computes 3D linear solutions (LORETA solutions) for the EEG inverse problem within a
3-shell spherical head model including scalp, skull, and brain compartments. The brain compartment is restricted to the cortical gray matter/hippocampus of a head model co-registered to the Talairach probability brain atlas and digitized at the Brain Imaging Center of the Montreal
Neurological Institute. This compartment includes 2394 voxels (7 mm resolution), each voxel containing an equivalent current dipole. LORETA solutions consistof voxel current density values able to predict EEG spectral power density at scalp electrodes, independently of the electrode reference used. These solutions are normalized by dividing the LORETA current density values at each voxel for the power density value obtained averaging the LORETA current density values across all frequencies (0.5–40 Hz) and all 2394 voxels of the brain volume. After the normalization,
the solutions lost the original physical dimension and are represented by an arbitrary unit scale (for sake of brevity and clarity, we refer to this scale as LORETA current density). This procedure reduces inter-subjects variability and fits the LORETA solutions in a Gaussian distribution.
Solutions of the EEG inverse problem are under-determined and ill conditioned when the number of spatial samples (electrodes) is lower than that of the unknown variables (current density at each voxel). In order to properly address this problem, the cortical LORETA solutions predicting scalp
EEG spectral power density are regularized to estimate distributed rather than punctual EEG source patterns. In line with the low spatial resolution of the adopted technique, we use collapse the voxels of LORETA solutions at frontal, central, parietal, occipital, temporal, and limbic regions of the brain model coded into Talairach space. The Brodmann areas listed in following Table form each of these regions of interest (ROIs).
LORETA BRODMANN AREAS
INTO THE REGIONS OF INTEREST (ROIs)
Frontal 8, 9, 10, 11, 44, 45, 46, 47
Central
Parietal
Temporal
Occipital
1, 2, 3, 4, 6
5, 7, 30, 39, 40, 43
20, 21, 22, 37, 38, 41, 42
17, 18, 19
Limbic 31, 32, 33, 34, 35, 36
The SOPs for the estimation of the LORETA power density and coherence
A. The SOPs for the "power of resting (eyes-closed) EEG cortical sources": (1) The measures estimating EEG source power density are obtained by the popular freeware low resolution brain electromagnetic tomography (LORETA) that can be downloaded from http://www.uzh.ch/keyinst/loreta.htm
; (2) individual resting EEG dataset is given as an input to spectral analysis; voxel output values will be normalized across all voxels and all frequencies from
1 Hz to 40 Hz; (3) normalized voxel values will be averaged into the frequency bands of interest such as 2-4 Hz (delta), 4-8 Hz (theta), 8-10.5 Hz (alpha 1), 10.5-13 Hz (alpha 2), 13-20 Hz (beta 1),
20-35 Hz (beta), 35-40 Hz (gamma); (4) normalized voxel values will be averaged within cortical macroregions of interest (ROIs) such as frontal, Rolandic, parietal, temporal, and occipital; mean normalized sLORETA value for each lobe is marker for AD.
B. The SOPs for the "coherence of resting (eyes-closed) EEG cortical sources": (1) the individual resting EEG dataset is given as an input to the option coherence analysis of the LORETA software;
(2) the ROIs are left vs. right frontal and left vs. right parietal; (3) the coherence LORETA solutions for the paired regions of interest are averaged for the frequency bands of interest; (4) these solutions are normalized by hyperbolic arch-sin. The coherence sLORETA values between the frontal lobes and between the parietal lobes constitute the "inter-hemispherical coherence" markers for AD, whereas the coherence sLORETA values between the left frontal and parietal lobes and between the right frontal and parietal lobes constitute the "intrahemispherical coherence" markers for AD.
Quality control (QC) procedures validating the above markers of AD for resting state eyes-closed condition
A. ANCOVA (age, education, gender individual alpha frequency as covariates) will test the hypothesis that each AD marker shows significant differences between Nold and AD groups.
B. Spearman test will test the hypothesis that the EEG markers for AD (including MCI as preclinical stage) will be correlated with global cognition (MMSE), hippocampal atrophy (MRI), temporo-parietal hypo-metabolism (PET-FDG).
C. Discriminant analysis will indicate the specific AD markers having the maximum weight in the discrimination of AD individual patients from control subjects.
References
Babiloni C, Binetti G, Cassetta E, Cerboneschi D, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Lanuzza B, Miniussi
C, Moretti DV, Nobili .,Pascual-Marqui RD, Rodriguez G, Romani GL, Salinari S, Tecchio F, Vitali P, Zanetti O,
Zappasodi F, Rossini PM. Mapping Distributed Sources of Cortical Rhythms in Mild Alzheimers Disease. A Multi-
Centric EEG Study. NeuroImage 2004; 22(1):57-67.
Babiloni C, Binetti G, Cassarino A, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Galderisi S, Hirata K,
Lanuzza B, Miniussi C, Mucci A, Nobili F, Rodriguez G, Romani GL, and Rossini PM. Sources of cortical rhythms in adults during physiological aging: a multi-centric EEG study. Human Brain Mapping. 2006a, 27(2):162-72.
Babiloni C, Binetti G, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Hirata K, Lanuzza B,
Miniussi C, Moretti DV, Nobili F, Rodriguez G, Romani GL, Salinari S, and Rossini PM Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multi-centric study. Clin Neurophysiol. 2006b,
117(2):252-268
Babiloni C, Benussi L, Binetti G, Bosco P, Busonero G, Cesaretti S, Dal Forno G, Del Percio C, Ferri R, Frisoni G,
Ghidoni R, Rodriguez G, Squitti R, and Rossini PM Genotype (cystatin C) and EEG phenotype in Alzheimer disease and mild cognitive impairment: a multicentric study. Neuroimage. 2006c, 29(3):948-64.
Babiloni C, Benussi L, Binetti G, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Ghidoni R,
Miniussi C, Rodriguez G, Romani GL, Squitti R, Ventriglia MC and Rossini PM Apolipoprotein E and alpha brain rhythms in mild cognitive impairment: A multicentric EEG study . Ann Neurol. 2006d, 59(2):323-34.
Babiloni C, Frisoni G, Steriade M, Bresciani L, Binetti G, Del Percio C, Geroldi C, Miniussi C, Nobili F, Rodriguez G,
Zappasodi F, Carfagna T, Rossini PM. Frontal White Matter Volume and Delta EEG Sources Negatively Correlate In
Awake Subjects With Mild Cognitive Impairment and Alzheimer's Disease. Clin Neurophysiol. 2006e;117(5):1113-29.
Babiloni C, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Lanuzza B, Miniussi C, Moretti DV, Flavio
Nobili F, Pascual-Marqui RD, Rodriguez G, Romani GL, Salinari S, Zanetti O, Rossini PM. Donepezil effects on sources of cortical rhythms in mild Alzheimer’s disease: Responders vs. Non-Responders. Neuroimage. 2006f;
31(4):1650-65
Babiloni C, Cassetta E, Binetti G, Tombini M, Del Percio C, Ferreri F, Ferri R, Frisoni G, Lanuzza B, Nobili F, Parisi
L, Rodriguez G, Frigerio L, Gurzì M, Prestia A, Vernieri F, Eusebi F, Rossini PM. Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer's disease. Eur J Neurosci. 2007 Jun;25(12):3742-57.
Babiloni C, Visser PJ, Frisoni G, De Deyn PP, Bresciani L, Jelic V, Nagels G, Rodriguez G, Rossini PM, Vecchio F,
Colombo D, Verhey F, Wahlund LO, Nobili F. Cortical sources of resting EEG rhythms in mild cognitive impairment and subjective memory complaint. Neurobiol Aging. 2008a Nov 20.
Babiloni C, Pievani M, Vecchio F, Geroldi C, Eusebi F, Fracassi C, Fletcher E, De Carli C, Boccardi M, Rossini PM,
Frisoni GB. White-matter lesions along the cholinergic tracts are related to cortical sources of EEG rhythms in amnesic mild cognitive impairment. Hum Brain Mapp. 2008b Dec 18.
Babiloni C, Ferri R, Binetti G, Vecchio F, Frisoni GB, Lanuzza B, Miniussi C, Nobili F, Rodriguez G, Rundo F,
Cassarino A, Infarinato F, Cassetta E, Salinari S, Eusebi F, Rossini PM Directionality of EEG synchronization in
Alzheimer's disease subjects.. Neurobiol Aging. 2009 Jan;30(1):93-102. Epub 2007 Jun 15.
K.J. Blinowska, M. Kaminski. Multivariate Signal Analysis by Parametric Models In: Handbook of Time Series
Analysis. Eds. B Schelter, W. Winterhalder, J. Timmer, Wiley-VCH, 2006.
Rossini PM, Del Percio C, Pasqualetti P, Cassetta E, Binetti G, Dal Forno G, Ferreri F, Frisoni
G, Chiovenda P, Miniussi C, Parisi L, Tombini M, Vecchio F, Babiloni C., Conversion from mild cognitive impairment to Alzheimer's disease is predicted by sources and coherence of brain electroencephalography rhythms. Neuroscience. 2006 Dec;143(3):793-803. Epub 2006 Oct 13.
1.6.1.1.6
Deliverables and Milestones
Table 16 - List of Deliverables of JRA1
Del. No. Deliverable name
Nature Dissemination level
Delivery date
(proj. month)
Milestone
Number
Resources
Milestone
Name
Table 17 - List of Milestones of JRA1
Activity(ies)
Involved ?
Expected
Date
Means of verification
Table 18 - Staff effort of JRA1
Participant number
Participant short name
Total person months
Quality metrics
Risk analysis and contingency plans
1.6.2
JRA2 – Design of the Diagnostic Services
CNR
Two requisites will be considered for the design of the DECIDE diagnostic services: 1) the
“diagnostic” purpose, and 2) the “Service” purpose of the proposed applications. The first requisite is strategic to ensure the effective increase of diagnostic confidence of the proposed algorithms, the second requisite is crucial to ensure the usefulness, reliability and long-term sustainability of the proposed services.
In order to accomplish the two above requirements, the JRA2 activity will define and design the
DECIDE Diagnostic Services in order to fit the diagnostic and service requirements at the base of the project and taking into consideration a decision-making organization model able to answer to the needs of the different potential users within the medical community involved in the neurological diagnosis process (the target users). Such organization model should able to provide the target users at the different step of the diagnosis process with diagnostic services able to assist them in interpreting the results of their analysis dependently from their role, interests, expertise and purpose.
Several target users of the DECIDE diagnostic service will be addressed within the scope of JRA2:
Neurologists, acting at the beginning and at the end of the neurological diagnostic process, which meet patients presenting cognitive disorders, require laboratory tests, neuropsychological assessments as well as morphological and functional measurements and make their diagnosis by combining the response of all these tests;
Doctors acting within the neurological diagnostic process, as radiologists, nuclear medicine doctors, neuro-physiologists which provide to neurologists diagnostic information indicative of the presence/absence of a neurological diseases;
Scientists dealing with diagnostic algorithms as Physicists, Mathematicians, Engineerings, which provide to both neurologists and doctors at any step of the diagnostic process quantitative or semi quantitative information supporting the presence/absence of a neurological diseases.
Among these target users, different contexts will be considered in designing the organization model at the basis of the DECIDE diagnostic services :
Users with expertise on the comprehension and use of the proposed diagnostic algorithms, whose interest in the use of the DECIDE diagnostic service is to take advantage from the distributed computation and/or the distributed database and from the sharing of evaluations at an international level. This kind of user can be easily made autonomous in the use of the service.
Users with no expertise on the comprehension and use of the proposed diagnostic algorithms, whose interest in the use of the DECIDE diagnostic service is to have available information additional to those they are able to obtain from their data. In this case the possibility to make available external decision makers will be taken into account in the design of the service.
Objectives and expected outcomes
TJRA2.1 – Clinical requirements and procedural tuning
(a) Define and validate standardized protocols and quality control procedures for the storage, extraction of neuroimaging biomarkers of imaging data, and production of relative reports within a grid-based e-infrastructure (GRID) in the framework of a diagnostic/prognostic service for the personalized care of elderly subjects with cognitive impairment. This will make these pipelines available for the European public hospitals;
(b) To test the added benefit of combined neuroimaging biomarker for the personalized care of subjects with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). This will make it clear the guidelines for the use of these neuroimaging biomarkers in the European public hospitals;
Tasks
Activities are organized into five main tasks. The different tasks will evaluate, optimise, design, integrate and validate the proposed algorithms as Diagnostic e-Services.
TJRA2.1 – Clinical requirements and procedural tuning , dealing with the evaluation and the definition of the clinical requirements of the DECIDE diagnostic services and the tuning of the key procedures within the services in agreement with the different typology of target users and the different contexts crossing the deciding process of the neurological diagnosis. UNIFG -Babiloni
TJRA2.2 – Algorithm Evaluation and Optimization , dealing with the studying of the proposed algorithms from both procedural and architectural points of view, by evaluating the necessary/unnecessary interactions with users, input and output information, data and results, and tailoring the algorithms and results of the algorithms to the clinical requirements in order to be included in the DECIDE diagnostic services.
CNR- Castiglioni
TJRA2.3 – Algorithm and Database Architecture Design , dealing with the definition and design of the architecture of the algorithms as well as of the database for the DECIDE diagnostic service.
TJRA2.4 – Application Integration and Middleware Interfacing, dealing with the integration of the DECIDE applications into the Grid infrastructure and the interfacing with the reference Grid middleware. COMETA-Barbera, Calanducci
TJRA2.5 – Validation of the design diagnostic service , MAAT-Manset
In the following paragraph, a detailed description of the Workplan for each task is given.
1.6.2.1.1
TJRA2.1 –Clinical requirements and procedural tuning UNIFG - Babiloni
One major and critical obstacle to the personalized care of aged people with cognitive decline is the lack of fully qualified neuroimaging biomarkers for Alzheimer’s disease (AD). These biomarkers are supposed to act as
(a) Accurate diagnostics especially very early in the disease process;
(b) Predictors of disease progression including conversion from prodromal states;
(c) Correlates of disease process, perhaps even surrogates.
It is likely that different neuroimaging biomarkers will be necessary for these different potential uses. The most advanced neuroimaging biomarkers are obtained by structural magnetic resonance imaging (MRI) and functional positron emission tomography (PET-FDG). Other promising neuroimaging biomarkers are obtained by advanced EEG techniques, on the basis of more than 20 peer reviewed EEG papers in elderly subjects published by the researchers of this Consortium (see the EEG papers by Drs. Babiloni, Blinowska, and Frisoni). EEG biomarkers can be provided by low-cost and non-invasive EEG facilities available in all European neurological departments.
Keeping in mind this premises, TJRA2.1 aims to
(a) Establish an innovative organization of the diagnostic/prognostic service for combinatorial analyses leading to multimodal neuroimaging biomarkers for early diagnosis, prediction of progression, and monitoring of therapy for AD.
(b) Define and validate standardized procedures extracting neuroimaging biomarkers alone and in combination with other biomarker modalities with a view to establishing their clinical utility.
The organization of the diagnostic/prognostic AD service would include the definition and validation of standardized protocols and quality control procedures for the following ACTIVITIES:
(a) The recording of structural magnetic resonance imaging (MRI) for the evaluation of cortical and hippocampus atrophy and vascular lesion;
(b) The recording of PET-FDG and EEG in the condition of resting state for the evaluation of regional cerebral blood flow and neurophysiologic mechanisms of neural synchronization, respectively;
(c) The storage of the MRI, PET-FDG, and EEG within our infrastructure (GRID);
(d) The qualification of remote clients having access to the stored software and neuroimaging data within the grid;
(e) The visualization and (semi)quantitative analysis of the stored imaging data by the remote qualified experts -i.e. extraction of the neuroimaging biomarkers-. This could be performed by either qualified experts of public/private hospitals or by qualified experts of SMEs. These SMEs could establish contracts with the hospitals having no human resources for the extraction of neuroimaging markers with the advanced techniques of the present project. The design of the service aims at promoting the development of European economy in the strategic biomedical context and at exploiting the use of the diagnostic/prognostic potential of validated neuroimaging biomarkers by clinicians of small hospitals with no internal human resources for such a task.
(f) The production of the report on the neuroimaging biomarkers by the remote qualified experts;
(g) The access to this report by clinicians for the personalized care of the examined elderly subjects with cognitive decline (early diagnosis, prognosis, and therapy monitoring).
We aim to achieve the objectives by utilizing individual neuroimaging datasets taken from the databases of a project granted by Italian Ministry of Health 2007 ("Diagnosis of incipient
Alzheimer disease: Development of ADNI-based imaging markers for use by the National Health
System"). We will add considerable value to this previous study by combining neuroimaging biomarlers and defining its proper combination for the personalized care of elderly subjects with cognitive decline.
1.6.2.1.2
TJRA2.2 – Algorithm Evaluation and Optimization CNR, Castiglioni
1.6.2.1.3
TJRA2.3 – Algorithm and Database Architecture Design UGDIST, Schenone
Benefits expected from Grids in the medical imaging domain go beyond the promise of large computing power and data storage space. Indeed, Grids allow the creation of large scale distributed datasets, enforcing the use of common standards, and permitting the medical communities to share computing resources and algorithms. Grids can play a federative role providing a logical extension to regional health networks by allowing distant sites to collaborate and exchange their data for specific research purposes.
The use of distributed computing resources running suitable applications on networks of federated research centers is often needed due to difficulties in finding relationships among heterogeneous data sets of large-scale initiatives. To widen the range of such analysis tools, the access to geographically distributed services has begun to be a suitable resource in the biomedical field, but has to be correctly managed.
Designing optimized algorithms to successfully run on the Grid infrastructure will give a contribution to these computational issues. To further improve the results of studies and protocols, tools and data have to be managed through predefined functional sequences of acquisition and analysis. This can be accomplished by transparently managing complex workflows over such sequences and by enabling automatic enactors of such workflows within the heterogeneous software environment on clinical networks.
On one hand, grids constitute a powerful means for solving challenging optimization problems and running complex simulation models. On the other hand, in order to allocate and schedule resources in a computational grid, there is need for customized optimization methods. Actually, many existing parallel algorithms for optimization should be improved to exploit the full power of typical grid platforms. Moreover, with the goal of providing efficient solutions and improving the overall system performance novel parallel approaches could be studied.
As regards data collection issues, the ability to deploy Grid infrastructure and services across organizational boundaries (rapidly, reliably, and scalably) is critical for the success of large-scale service-based distributed applications. These critical requirements can be faced through suitable authorization and certification policies as well as through advanced tools for accessing distributed data in very sensitive clinical environments.
On one hand, computing sites and medical centers are usually geographically distributed and this often requires transfer and replication of huge sets of sensible data. From another point of view, contributions should address issues related to the understanding of large amount of heterogeneous data files. Moreover, significant metadata can be associated to patient data and suitable data structures and tools must be provided to hide the metadata management from users.
This task is planned to design distributed data architectures able to:
Allow transparent access to files, independently to the physical location. This can be obtained using, for example, logical file names, which are entities with globally unique names that may have one or more physical instances;
Design replication and federation data strategies in order to offer high data availability, low bandwidth consumption, increased fault tolerance, and improved scalability of the overall system;
Allow an effective management of metadata carrying information about annotations, parameters, acquisition procedures, medical history and any other information to be processed within the applications.
Implement new mechanisms for accessing and retrieve information about data stored in storage systems. A possibility is to exploit metadata that describes the content and the structure of data for mining clinical datasets through methods of computational intelligence.
The metadata may describe the information content represented by the file, the circumstances under which the data was obtained, and/or other information useful to applications that process the data.
1.6.2.1.4
TJRA2.4 – Application Integration and Middleware Interfacing COMETA
1.6.2.1.5
TJRA2.5 – Global validation MAAT
1.6.2.1.6
Deliverables and Milestones
Del. No. Deliverable name Nature
TJRA2.1
TJRA2.1
TJRA2.1
TJRA2.1
TJRA2.1
TJRA2.1
Standardized protocols and quality control procedures for the MRI, PET,
EEG recordings and upload of the data in the grid
Standardized protocols and quality control procedures for the qualification of remote clients having access to the stored software and neuroimaging data in the grid
Standardized protocols and quality control procedures for the. extraction of the neuroimaging biomarkers
Standardized protocols and quality control procedures for the production of and access to the report with the indication of the neuroimaging biomarkers
Upload of the patients’ MRI, PET,
EEG data in the grid
Qualification of personnel to the use of the grid software for the extraction of the neuroimaging biomarkers and for the production of the
Report
Report
Report
Report
Database
Formation
Dissemination level
Internet users
Delivery date
(proj. month)
6
Internet users
Internet users
Internet users
Qualified
Internet users
(UE)
Qualified
Internet users
(UE)
6
6
6
12
18
TJRA2.1
TJRA2.1 reports
Extraction of the neuroimaging biomarkers and production of the reports from the data of a previous Italian neuroimaging project
Neuroimaging biomarkers
Report Final report on the diagnostic/prognostic service (caveats, costs, results, impact on the clinical practice)
Qualified
Internet users
(UE)
Internet users
Table 19 - List of Milestones of JRA2
Milestone
Number
TJRA2.1
TJRA2.1
Milestone
Name
Activity(ies)
Involved ?
Release of the standardized protocols and quality control procedures for the
MRI, PET, EEG recordings, the upload of the data in the grid, the qualification of remote clients, the extraction of the neuroimaging biomarkers, and production of the reports
TJRA2.1
Completed qualification of the personnel to the use of the grid software for the extraction neuroimaging of biomarkers and for the production of the relative reports
TJRA2.1
6
18
Expected
Date
34
36
Means of verification
Evaluation of the report
Interview of the qualified personnel
TJRA2.1
TJRA2.1
TJRA2.1
Uploaded patients’ MRI,
PET, EEG data in the grid
TJRA2.1
Production of the neuroimaging biomarkers and relative reports from the data of a previous Italian neuroimaging project
TJRA2.1
Release of the report on the impact of the neuroimaging biomarkers on the early diagnosis and prognosis of
MCI and AD subjects
TJRA2.1
20
34
36
Resources
Table 20 - Staff effort of JRA2
Participant number
5
Participant short name
CNR-IBFM
UNIFG
Total person months
Quality metrics
Risk analysis and contingency plans
Evaluation of the database
Evaluation of the reports
Evaluation of the report
1.6.3
JRA3 – User Validation and Testing
EADC
Objectives and expected outcomes
Tasks
1.6.3.1.1
TJRA3.1 – Alpha and Beta testing HSR
1.6.3.1.2
TJRA3.2 – Interface Usability Assessment EADC
1.6.3.1.3
Deliverables and Milestones
Table 21 - List of Deliverables of JRA2
Del. No. Deliverable name
Nature Dissemination level
Milestone
Number
Milestone
Name
Table 22 - List of Milestones of JRA2
Activity(ies)
Involved ?
Expected
Date
Resources
Table 23 - Staff effort of JRA2
Participant number
Participant short name
Total person months
Delivery date
(proj. month)
Means of verification
Quality metrics
Risk analysis and contingency plans
NA2
NA3
SA1
SA2
JRA1
JRA2
JRA3
Table 1.3.a – List of Activities
Activity
N° 3
NA1
Activity title Type of activity 4
Activity list
Lead participant
N° 5
Lead participant short name
TOTAL
Person months 6
Start month 7
End month 8
3 Activity number: WP 1 – WP n.
4
Please indicate one activity per item:
RTD = Research and technological development; COORD = Co-ordination; SUPP = Support;
MGT = Management of the consortium; SVC = Service activities.
5 Number of the participant leading the work in this Activity.
6 The total number of person-months allocated to each Activity.
7 Measured in months from the project start date (month 1).
Table 1.3b: Deliverables List
Del. No.
8
List of Deliverables
Activity no. Nature 9 Deliverable name
Dissemination level 10
Delivery date 11
(proj. month)
8
Deliverable numbers in order of delivery dates. Please use the numbering convention <WP number>.<number of deliverable within that WP>. For example, deliverable 4.2 would be the second deliverable from work package 4.
9
Please indicate the nature of the deliverable using one of the following codes:
R = Report, P = Prototype, D = Demonstrator, O = Other
10
Please indicate the dissemination level using one of the following codes:
PU = Public
PP = Restricted to other programme participants (including the Commission Services).
RE = Restricted to a group specified by the consortium (including the Commission Services).
CO = Confidential, only for members of the consortium (including the Commission Services).
11 Measured in months from the project start date (month 1).
Table 1.3c: Activity description
Activity number
Activity description GARR
NA1 Start date or starting event:
Activity title
Activity Type
12
Participant number
Participant short name
Person-months per participant
Objectives
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
12
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 13
Participant number
Participant short name
Person-months per participant
Objectives
FBF
NA2 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
13
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 14
Participant number
Participant short name
Person-months per participant
Objectives
COMETA
NA3 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
14
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 15
Participant number
Participant short name
Person-months per participant
Objectives
MAAT
SA1 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
15
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 16
Participant number
Participant short name
Person-months per participant
Objectives
IC
SA2 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
16
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 17
Participant number
Participant short name
Person-months per participant
Objectives
UGDIST
JRA1 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
17
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 18
Participant number
Participant short name
Person-months per participant
Objectives
CNR
JRA2 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
18
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Activity number
Activity title
Activity Type 19
Participant number
Participant short name
Person-months per participant
Objectives
EADC
JRA3 Start date or starting event:
Description of work (possibly broken down into tasks) and role of partners
Deliverables (brief description) and month of delivery
19
Please indicate one activity per activity:
RTD: Research and technological development; COORD: Co-ordination; SUPP: Support; MGT: Management of the consortium; SVC: Service activities.
Table 1.3d: Summary of staff effort GARR
[A summary of the staff effort is useful for the evaluators. Please indicate in the table number of person months over the whole duration of the planned work, for each Activity by each participant.
Identify the work-package leader for each activity by showing the relevant person-month figure in bold.]
Participant number
Participant short name
NA1 NA2 NA3
…..
Total person months
Table 1.3e: List of milestones
[Milestones are control points where decisions are needed with regard to the next stage of the project. For example, a milestone may occur when a major result has been achieved, if its successful attainment is a required for the next phase of work. Another example would be a point when the consortium must decide which of several technologies to adopt for further development.]
Milestone
Number
Milestone
Name
Activity(s)
Involved ?
Expected
Date 20
Means of verification 21
20 Measured in months from the project start date (month 1).
21 Show how both the participants and the Commission can check that the milestone has been attained. Refer to indicators if appropriate.
Table 1.3f: Connectivity services cost table (TBD, GARR)
[Connectivity services costs result from the provision of connectivity. Connectivity is defined as a set of one or more circuits allowing for the transmission of full duplex bit streams between defined end points.
If relevant to your proposal, please identify the cost for connectivity services per partner.]
Part. Part. Short name
Cost (€)
Number
1
2
3
….
Total
[Note that connectivity services are considered as a service activity and thus have to be declared under the column “Services” in the relevant A3 forms. The funding of connectivity services costs is limited to a maximum of
50% of the eligible costs.]
Section 2.
I MPLEMENTATION [GARR]
2.1
Management structure and procedures
[Describe the organisational structure and decision-making mechanisms of the project. Show how they are matched to the complexity and scale of the project.]
The minimal structure will be:
(Overall management) o A Project Manager (PM) with a Deputy (DPM) nominated by the Coordinator
(GARR). o A Project Management Board (PMB): one member + a deputy per partner + the PM and his/her deputy. The PMB is in charge for co-ordinating and managing items that effect the contractual terms of the project. o Project Office (PO): 3 persons minimum, to deal with administrative and external communication (in collaboration with Dissemination activities – NA3).
The project manager (PM) is appointed by the co-ordinating partner to run the project, and the project office supports the PM in the day-to-day operational management of the project.
(Technical and scientific management) o A Technical and Scientific Manager (SM) will be selected by the Scientific partners to coordinate the technical and scientific works. o He or she will be supported by a scientific advisory board (SAB) that will ensure the scientific quality and relevance of the project output. o A Technical Board, including the SM and all Activity Leaders and their deputies.
(To be expanded)
2.2
Individual participants
[PMB representatives or team leaders should provide the Profile, role and curricula or key staff to be involved in the project – see the INFN example as a reference]
[ Maximum length for Section 2.2: one page per participant
For each participant in the proposed project, provide a brief description of the organisation, the main tasks they have been attributed, and the previous experience relevant to those tasks. Provide also a short profile of the staff members who will be undertaking the work.]
2.2.1
Consortium GARR – GARR (Coordinator)
Profile and Role in the project
GARR is the Italian Research and Education Network, interconnecting all major Academic and
Scientific organizations in Italy. GARR institutional mandate includes the mission of facilitating cooperation in the field of research through the delivery of leading-edge e-Infrastructures, both at a national and international level, and stimulating the user community to pursue joint endeavours in this field. GARR collaborates since 2004 with the Italian Ministry pf Health, to provide the community of Medical Research with high capacity network connectivity and advanced services.
GARR also supports the community in e-Infrastructure related activities, by gathering its requirements in terms of networking, distributed computing etc, and implementing solutions to meet them effectively. Targeted dissemination of eInfrastructures, and knowledge transfer in ordcr to favour the adoption of advanced telecommunication technologies and services are also delivered to specific communities.
Beside coordinating the project, GARR will provide dedicated network support in order to ensure that the higher layers of the eInfrastructure (i.e. grid middleware, application level) can efficiently exploit its potential. GARR will play an important role in NAs, as well as in delivering key Service
Activities.
..
Key Personnel
Laura Leone has a degree in engineering and is a Network Senior Engineer involved at GARR since 2001. She is an expert of the network planning and provisioning GARR national and international infrastructure. She is a PM of national projects of deployment of network infrastructure for research for medical communities. At GARR she has been involved in others EC funded projects (GN2,
Mupbed).
Mario Reale has a degree in Physics from the University of Rome Tor Vergata, Italy and a Ph.D in Physics from the University of
Wuppertal, Germany.
He gained a wide, multi-year experience in Grid developing and monitoring, with special reference to the scientific (High Energy
Physics) context, as well as advanced knowledge in grid middleware and its testing and validation.
At GARR, he provides support to the GARR Grid community at national and international level and he is involved in several ECfunded projects relating to grids, such as EGEE-III, EUMEDGRID-Support and GEANT3.
Federica Tanlongo is PR manager of GARR. She has an ICT master degree in New Media and Communication from the University of Rome “La Sapienza”. She joined GARR in 2005, where she is currently in charge for coordinating communication and dissemination activities. She has been involved in a number of European projects (i.e. EUMEDCONNECT and
EUMEDCONNECT2, EUMEDGRID, EUChinaGRID, EGEE2, EU-IndiaGrid and EU-IndiaGrid2, GEANT3 etc) chiefly on dissemination, international cooperation, multimedia communication, and project management issues.
..
2.2.2
CNR
Profile and role in the projectCNR will enter the project with two Research institutes working in the
Neurological domain: IBFM and ISN.
The Institute of Molecular Bioimaging and Physiology (IBFM) combines the research activities of the Institute of Neuroscience and Bioimaging, of the Department of Molecular Physiology and
Biotechnology and of the Center for Studies of Cerebral Neurophysiology of Genoa.
The Institute is well known for its research in bioimaging with Single Photon Emission Tomography (SPET),
Positron Emission Tomography (PET), particularly for neurological applications. The institute has considerable experience in physics and mathematics for the development and applications of methods for SPET, PET and MRI image processing and analysis.
In this project IBFM-CNR will be involved in: a) the optimisation and validation of voxel-based statistical methods for the assessment of SPET/PET cerebral studies increasing the confidence level of neurological diagnosis, and b) their implementation into an international, Grid-based, web portal of clinical application neuroinformatics services.
The aim of our Neuroimaging Laboratory is to develop neuroimaging research in the clinical neurosciences and to thereby generate scientific findings that will improve our understanding of the functional and structural abnormalities within specific neurological disorders. Research projects include both basic and clinical neuroscience, investigating normal brain functioning and structural/functional changes occurring in several disorders, such as Epilepsy, Parkinson’s disease,
Multiple Sclerosis and movement disorders.
The aim of our Neuroimaging Laboratory is to develop neuroimaging research in the clinical neurosciences and to thereby generate scientific findings that will improve our understanding of the functional and structural abnormalities within specific neurological disorders. Research projects include both basic and clinical neuroscience, investigating normal brain functioning and structural/functional changes occurring in several disorders, such as Epilepsy, Parkinson’s disease, Multiple Sclerosis and movement disorders.
In this project the Neuroimaging Research Unit (URT-CNR) is involved in: a) the optimisation of advanced neuroimaging methods performing morphological measurement of specific subcortical regions (i.e. hippocampus) involved in well-known neurodegenerative mechanisms, and b) their implementation into an international, Grid-based, web portal of clinical application neuroinformatics services. Subcortical volume measurement will be performed by using an automated segmentation method as provided by Freesurfer ( http://surfer.nmr.mgh.harvard.edu
). This method has been validated against manual tracings in healthy individuals and in patients with neurological diseases. The automated procedures for volumetric measurements of several subcortical regions (including hippocampus) provided segments and labels for up to 40 unique structures and assigned a neuroanatomical label to each voxel in an MRI volume, based on probabilistic information estimated automatically from a manually labeled training set. The segmentation used three pieces of information to disambiguate labels: (1) the prior probability of a given tissue class occurring at a specific atlas location, (2) the likelihood of the image for the given tissue class, and (3) the probability of the local spatial configuration of labels for the given tissue class.
5 selected publications relative to the DECIDE project:
-E. Paulesu, B. Goldacre, P. Scifo, S. F. Cappa, M. C. Gilardi, I. Castiglioni, D. Perani, F. Fazio. Functional heterogeneity of left inferior frontal cortex as revealed by fMRI.
NeuroReport, 1997; 8: 2011-16. Impact factor: 1.904, fonte: ISI Journal Citation Report.
-G. Biella, M. L. Sotgiu, G. Pellegata, E. Paulesu, I. Castiglioni, F. Fazio. Acupuncture Produces Central
Activations in Pain Regions. Neuroimage, 2001; 14: 60-66. Impact factor: 5.694.
-A. Berti, G. Bottini, M. Gandola, L. Pia, N. Smania, A. Stracciari, I. Castiglioni, G. Vallar, E. Paulesu.
Shared cortical anatomy for motor awareness and motor control . Science, 2005; 309: 488-491. Impact factor: 28.103..
-I. Castiglioni, I. Buvat, G. Rizzo, M. C. Gilardi, J. Feuardant, F. Fazio. A publicly accessible Monte Carlo database for validation purposes in emission tomography . Eur. J. Nucl. Med. Mol. Imaging, 2005: 32(10):
1234-1239. Impact factor: 4.532.
- I. Castiglioni, B. Canesi, A. Schenone, D. Perani, M. C. Gilardi. A Grid-based SPM service (GriSPM) for
SPECT and PET neurological studies . Eur. J. Nucl. Med. Mol. Imag., 2009; 36: 1193-1195. Impact factor:
4.532.
Key personnel ,
Institute of Molecular Physiology and Bioimaging, National Research Council, IBFM-CNR
Isabella Castiglioni, Researcher
Born in Milan in 1968. Laura (bachelor degree) in Physics with 110/110 et laude at the University of Milan in 1993. Researcher in the Molecular Bio-imaging and Physiology Institute for National
Research Council since 1996. Responsible for the Research Activity “Monte Carlo simulations in
PET and SPECT (Bioimaging Physics)” for IBFM-CNR since 2000. Member of the Nuclear
Medicine Department and PET Centre of Scientific Institute H. San Raffaele since 2003. Member of the Neuroscience Division of Scientific Institute H. San Raffaele since 2008. Project leader of the CNR M.E. P06.026 project “Proteogenomic and molecular imaging in medicine”, for the CNR project “Technological Innovation-Integration in medicine”, since 2008.
Thesis co-adviser in Physics, Biomedical Engineering and Informatics since 1998. Tutor and
University Instructor in Biomedical Engineering from 1998 to 2001. Instructor for Residential
Courses on Neuroimaging for Physicians in Nuclear Medicine and on PET for Technicians in
Radiology and Nuclear Medicine, Scientific Institute H. San Raffaele since 2001. Instructor for the
Specialization School in Nuclear Medicine, Medicine and Chirurgic Faculty, Milan University from
2002 to 2005. Thesis co-adviser in Specialization in Medical Physics, Physics Faculty, Milan-
Bicocca University since 2006. Responsible of IAEA scientific training visits in PET and PET-CT
since 2007. Tutor for the Ph.D program in Biomedical Technologies, Milan-Bicocca University since 2007. Tutor for the 2 nd level International Master in Nuclear and Ionizing Radiations
Technologies, Istituto Universitario degli Studi Superiori, Pavia since 2009.
Reviewer of IEEE Transactions on Medical Imaging Journal since 1999. Reviewer of Physics in
Medicine and Biology since 2003. Reviewer of European Journal of Nuclear Medicine and
Molecular Imaging since 2005.
Neuroimaging Research Unit , Institute of Neurological Sciences
Ivan Duca. Network & computer engineering ; i.duca@isn.cnr.i.it
; 0984 9801267
Antonio Cerasa, PhD. Multimodal Neuroimaging techniques; a.cerasa@isn.cnr.i.it
; 0984
9801270
Prof. Aldo Quattrone, MD. Director of Neuroimaging Research Unit; a.quattrone@isn.cnr.it
Antonio Cerasa is PhD in Clinical Neuroscience, Faculty of Medicine, University of Messina. He is currently
Researcher assistant in multimodal advanced neuroimaging at the Neuroimaging Research Unit, Institute of
Neurological Sciences, National Research Council, Catanzaro.
..
2.2.3
COMETA
Profile and role in the project
COMETA 22 is a not-for-profit Organization established in Catania (Italy) in 2005 whose funding members are the Universities of Catania 23 , Messina 24 , and Palermo 25 , INFN (the Italian National Institute of Nuclear and Particle Physics, INAF 26 (the Italian National Institute of Astrophysics), INGV 27 (the Italian National
Institute of Geophysics and Volcanology), and the Consorzio SCIRE 28 .
The institutional goals of COMETA are to:
Create a Virtual Laboratory in Sicily, both for scientific and industrial applications, built on top of a
Grid infrastructure;
Connect the Sicilian e-Infrastructure to those already existing in Italy, in Europe, and in the rest of the world improving the scientific collaboration and increasing the “competitiveness” of e-Science and e-Industry;
Disseminate the “Grid paradigm” through the organization of dedicated events and training courses;
Trigger/foster the creation of spin-offs in the ICT area in order to reduce the
“brain drain”
of brilliant young people to other parts of Italy and beyond.
The COMETA e-Infrastructure consists of about 2000 CPU cores and 250 TB of storage and it is distributed over 7 sites (located in the poles of Catania, Messina and Palermo) where HPC clusters are connected by the
GARR network and the gLite Grid middleware. More than 120 applications 29 have been developed by
COMETA staff in the last three years among which the gLibrary 30 framework for digital repositories that has been developed in cooperation with INFN and used in several biomedical and cultural heritage contexts.
COMETA will contribute to XXXXX ……
Key Personnel
22 www.consorzio-cometa.it
.
23 www.unict.it
.
24 www.unime.it
.
25 www.unipa.it
.
26 www.inaf.it
.
27 www.ingv.it
.
28 www.consorzioscire.it
.
29 www.pi2s2.it/applications
30 https://glibrary.ct.infn.it
Dr. Giuseppe Andronico was born in Catania (Italy) in January 1965. He graduated in Physics “cum laude” at the University of Catania in 1991 and since 1995 he holds a Ph. D. in Physics from the same University.
Since March 2001 he is Technologist at the INFN Sezione di Catania. Since his graduation his main research activity has been done in the realm of Theoretical Physics. He has been involved in lattice field theory simulations.
Since late 1999 he has been interested in Grid Computing participating to several initiatives: European
DataGRID, INFN Grid, EGEE. In these initiatives he has been involved in developing code, in operations, in training and in dissemination activities. More recently he has been involved in some European funded projects: in EELA and EUMEDGRID, as WP manager, in EUChinaGRID, as Technical Manager, and in
EGEE-II.
He is currently involved in the TriGrid VL and PI2S2 projects, funded respectively by the Regione Siciliana and the Italian Ministry of University and Research. Since 2007 he is coordinator of the Data Center of the
Department Physics and Astronomy of the University of Catania and the Catania Department of INFN.
Prof. Roberto Barbera was born in Catania (Italy) in October 1963. He graduated in Physics "cum laude" at the University of Catania in 1986 and since 1990 he holds a Ph.D. in Physics from the same University.
Since beginning of 2005 he is Associated Professor at the Department of Physics and Astronomy of the
Catania University. Since his graduation his main research activity has been done in the domains of
Experimental Nuclear and Particle Physics. He has been involved in many experiments in France, Russia,
United States and Sweden to study nuclear matter properties in heavy ion collisions at intermediate energies.
He is author of about 90 scientific papers published on international journals and more than 150 proceedings of international conferences. He is editor of the International Journal of Distributed Systems and
Technologies and referee of both Journal of Grid Computing and Future Generation Computer Systems.
Since 1997 he is involved in the NA57 Experiment at CERN SPS and in the ALICE Experiment at CERN
LHC. Within ALICE, he has been the coordinator of the Off-line software of the Inner Tracking System detector and member of the Off-line Board. Since late 1999 he is interested in Grid Computing. He is member of the Executive Board of the Italian INFN Grid Project31 , of the Executive Committee of the
Italian Grid Infrastructure32 (the Italian National Grid Initiative) and of the Scientific & Technical
Committee of GARR33 (the Italian National Research and Education Network). Between 2005 and 2009 he has been the Director of two big Grid Projects (TriGrid VL34 and PI2S235 funded by the Sicilian Regional
Government and by the Ministry of University and Research, respectively. At European level, he has been involved with managerial duties in many EU funded projects and he is currently the Coordinator of the
EPIKH36 project and the Technical Coordinator of the EELA-237 project. Since 2002 he is the responsible of the GENIUS38 Grid portal project and, in 2004, he created the international GILDA39 Grid infrastructure for training and dissemination that he coordinates since the beginning.FBF
Profile and Role in the Project
FBF ( http://www.irccs-fatebenefratelli.it/sito/pagine/fatebenefratelli.php
) is the Italian
National Centre of Excellence for Alzheimer's and coordinator of neuGRID (www.neuGRID.eu), the e-Infrastructure that will be used in this project to host the diagnostic algorithms, and outGRID
(www.outGRID.eu), aimed to foster interoperability among international e-Infrastructures for computational neuroscience. FBF will: (i) coordinate the implementation of the algorithms on to the e-Infrastructure, (ii)
31 grid.infn.it
32 www.italiangrid.org
33 www.garr.it
34 www.trigrid.it
35 www.pi2s2.it
36 www.epikh.eu
37 www.eu-eela.eu
38 https://genius.ct.infn.it
39 https://gilda.ct.infn.it
coordinate the validation of the algorithms on clinical patients by a large number of European clinical centres, and (iii) liase with internationa infrastructures and working groups active in the field of computational neuroscience.
Key Personnel
2.2.4
HSR
Profile and Role in the Project
The Scientific Institute San Raffaele (HSR-U) and the Vita-Salute University represent reference centres in the field of Neuroscience, Neurology and Neuroimaging in Italy.
The HSR-U owns a large number of facilities devoted to the in vivo study of the brain functions in normal subjects and in neurological and psychiatric patients: 1. Radiochemistry laboratory for the development of novel radioligands for positron emission tomography studies of neurochemical processes. 2. Psychology laboratory for the development and testing of cognitive paradigms for testing neurologic patients and for functional imaging experiments. 3. A cyclotron (IBA Cyclone
18/9) and one SPECT scan and two modern PET scanners for brain functional emission tomography studies (GE-Advance PET with 3D scanning capabilities and STE). The cyclotron allows the routine production of 11 PET ligands for studies of brain metabolism, brain activation and neurotransmission.. 4. A 3T MRI scanner (Philips) devoted entirely to research. 5) Networks of computers connected with all the hospital dpts and with the Internet and Workstations dedicated to data analysis and imaging post processing.
The dedicated scientific personnel of HSR-U includes multidisciplinary groups of experts in radiochemistry, computing sciences, PET and MRI physics and engeneering, psychology, neuropsychology, neurology, psychiatry, and psychopharmacology,
This infrastructure can offer the opportunity of an articulated research plan starting from behavioural observations in humans, to in vivo measurements of brain neurochemical processes.
All this can be at one research site with the possibility of gaining access to patient population, after appropriate ethical approval. The HSR-U is well known for previous neuropsychological, neurological and psychiatric studies using metabolic measurements of brain activity in various neurological and psychiatric disorders and syndromes. The radiochemistry group in the centre has a long lasting experience and a well-known profile in tracer production and development. The
Departments of Neurology and Neuropsychiatric Sciences, are part of the HSR-U, and have appointment with the University Vita-Salute. Both clinical and laboratories facilities are highly implemented within the Departments. The clinical section comprises approximately 100 neurological beds and 80 psychiatric beds, Outpatients Unit (approx. 50 000 visits per year) for the follow-up of the patients discharged from Departments.
The specific activities of the HSR-U are multidisciplinary researches that offer an integrated approach between basic research, behavioral techniques and in vivo measurements of brain structure and function and brain neurochemical processes using advanced SPET-CT, PET-CT,
MRI, fMRI. The Nuclear Medicine Department has a long lasting experience and specific interest in functional studies of neurodegenerative conditions with large and established experience in multicenter clinical and neuroimaging research studies. Among these the European projects
Network for Efficiency and Standardisation of Dementia Diagnosis(NEST-DD) and Diagnostic
Molecular Imagaing (DIMI Network of Excellence). Given the collaboration with the Departments of
Neurology and Psychiatry, the Division of Neuroscience and with the Faculty of Psychological
Sciences, these techniques are applied in large samples of ad hoc patient populations.
BASIC DESCRIPTION OF THE INFRASTRUCTURE
The infrastructure proposed comprises the Centro Ciclotrone/PET and the Nuclear Medicine
Department at the Scientific Institute San Raffaele as the main diagnostic and research resource.
The infrastructure is completed by the MRI facilities in the Neuroradiology Department of the
Scientific Institute San Raffaele All these facilities can be considered part of the same infrastructure because of the spatial contiguity, because they are connected electronically, because the scientific staff gaining access to the resources is the same for all structures. The cyclotrons allows the routine production a wide range of PET ligands (up to 28 radiotracers, including the tracers for research purposes), labelled either with 11 C, 18 F, 15 O for metabolic or pharmacological studies and for activation studies. The neurochemical systems that can be studied in our lab include serotonergic system (5-HT
2A
, 5-HT
1A
, 5HT re-uptake), dopaminergic system (reuptake sites, D
1
, D
2
and D
4
receptors), benzodiazepine receptors and others.
The permanent staff involved includes scientists from different areas of research, covering a wide scientific background: the applicant, Prof. Daniela Perani is a neurologist, neuropsychologists and neuroradiologist with long lasting experience in PET, SPECT, MRI and and fMRI clinical and experimental research. Dr. Paola Vai and Dr. Andrea Panzacchi are nuclear medicine physicians with expertise in PET and SPECT brain studies, Dr. Elena Andreolli is a radiochemist with experience in radiotracers synthesis and production.
Prof. Maria Carla Gilardi and Dr. Valentino Bettinardi, physicists, Dr. Paola Scifo and Dr.
Giovanna Rizzo, engeneers, Dr. Sergio Todde , Dr. Mario Matarrese, Dr. Maria Grazia Minotti and
Dr. Franco Perugini radiochemists. The technical staff directly involved in operating the infrastructure and supporting its users includes 10 technicians.
Set-up date. There are 2 cyclotrons, 2 PET scanners available and a SPECT camera available for brain studies.
NUMBER OF PATIENTS .
In this project HSR will provide 50 healthy and 150 neurological subjects properly selected by clinical and cognitive evaluation and neuropsychological assessment. Both normal and neurological subjects will undergo SPECT-CT or PET-CT studies, as well as MRI scans following validated and standardized protocols.
The aim of the HSR unit is to validate and test neuroimaging methods that can be applied to the clinical diagnostic routine set up of patients with neurodegenerative conditions, in particular dementias and Parkinson disease..
..
Key Personnel
Daniela Perani is
Full Professor, Neurophysiolocical Psychology, University Vita-Salute San
Raffaele, Milano, Italy; Head of Research Unit Division of Neuroscience, San Raffaele
Scientific Institute; Coordinator Physician for Diagnostic Neuroimaging, Scientific
Institute San Raffaele, Milano Italy
Societies and Academic Appointments
Italian Neurological Society
Italian Neuropsychology Society
Italian Society of Psychophysiology
International Society for Neuroscience
Member of the International Neuropsychological Symposium, since 2000
Honorary Research Fellow Royal Post-Graduate Medical School, Hammersmith
Hospital, University of London, London, UK 1987-1988
Invited Professor at the Institut de France "Academie des Science" (April 1997)
Adjunct Professor, School of Specialty in Neurology, University of Milan, 1990-
1998
Adjunct Professor, Faculty of Psychology, University Vita-Salute HSR, from 1998 to 2001
Invited guest at the Department of Brain and Cognitive Sciences Massachusetts
Institute of Technology, Cambridge, MA USA: July-August 1997, August 1999,
August 2000
Invited guest at the Department of Cognitive Neuroscience, UCSD, San Diego Ca
USA: August 2001, August 2002, August 2003
Invited guest at the Max Planck-Institut fur Neuropsychologische Forschung, July
2001, July 2002, July 2003, July 2004
Invited Member of the International Scientific Advisory Board (Fachbeirat) at the
Max Planck-Institut fur Neuropsychologische Forschung, Leipzig: 2002-2010
2.2.5
UGDIST
Profile and Ro le in the Project
The Department of Communication, Computer and System Science (DIST) at the University of
Genoa ( http://www.dist.unige.it/dist/index_en.html
) is active in researches concerning information technologies and methodologies ranging from robotics to bioengineering and environmental activities. The main research activities of Biolab are related to Grid and computational applications for life sciences
(medical imaging, bioinformatics, systems biology).
In this project Biolab will be involved in activities concerning the neuroinformatic applications with specific reference to distributed web-based environments for the diagnosis of neurodegenerative diseases and to computational intelligence algorithms for the segmentation of medical images.
Key Personnel
Marco Fato
Assistant Professor
Coordinator of Task JRA2.1
Coordinator of Task SA1.3
1988 Master Degree in Electronic Engineering from the University of Genoa
1989 Research Assistant at the System, Communication and Computer Science
Department of the University of Genoa.
1990-1992 Consultant with Video Display Systems (VDS SpA) in Florence
1992-1993 Research Assistant at the System, Communication and Computer Science
Department of the University of Genoa.
1993-1996 PhD student at the System, Communication and Computer Science Department of the University of Genoa.
1995 Visiting Scientist at the Hewlett-Packard Company (HPLABS) and the Radiology
Department of the Stanford University, Palo Alto, USA .
1996
Genoa
Doctor of Philosophy degree in Biomedical Engineering from the University of
1996-2001 Research Fellow at the
System, Communication and Computer Science Department of the University of Genoa.
2001-2006 Senior Research Fellow at the System, Communication and Computer Science
Department of the University of Genoa.
2004-present: Project reviewer for the
Italian Ministry of Research.
2006-present: Associate Professor at the System, Communication and Computer Science
Department of the University of Genoa.
In charge of BIOLAB (Laboratory of Bioengineering and
Bioimages)
Projects
1993-1996
Project “
MERMAID -
Medical emergency aid through telematics” -
European
Commission DGXIII FP4
1997-2000 Project “ TEMETEN Towards a European Medical & Teleworking Network ” -
European Commission DGXIII FP4.
1998-1999
Project “
WETS - Worldwide Emergency Telemedicine Services
” - European
Commission DGXII FP5.
2000-2002
Project “
JUST - Just in time - health emergency interventions - Training of nonprofessionals by virtual reality and advance IT tools
” - European Commission DGXVI FP5.
2000-2003 Project 791 ex Legge 46 – “ Ambiente interattivo multimodale per la pianificazione dei trattamenti chirurgici e per la chirurgia guidata delle lesioni neoplastiche osteomicutanee
” –
Italian Ministry of Research.
2001-2003
Project “
VEPSY - Telemedicine and Portable Virtual Enviroments for Clinical
Psychology ” - European Commission DGXIII FP5.
2002-2004 Project FIRB Neuroinformatica (Italian node of the OCSE network of
Neuroinformatics) – Italian Ministry of Research
2002-2005 Project FIRB Grid.it “ Piattaforme abilitanti per griglie computazionali a elevate prestazioni orientate a organizzazioni virtual scalabili
” – Italian Ministry of Research.
2002-2005
Project FIRB “INTESA - Integrazione Telematica Sanitaria per la continuità di cura della salute del cittadino
” – Italian Ministry of Research.
2003-2005 Project “ SWALIS - Liste d’attesa per prestazioni chirurgiche: sperimentazione di sistemi per la loro gestione
” – Italian Ministry of Health.
2004-2005
Project “
GRID-COORD - ERA Pilot on a co-ordinated Europe-wide initiative in
Grid Research ”, European Commission – IST Programme FP6.
2004-2007
Project FAR “
BBKIT – Modelli e piattaforme di sviluppo di applicazioni per l’interazione Business to Business ” - Italian Ministry of Research
2006 – 2009 Project “ Sistemi intelligenti per la gestione del paziente nel ciclo diagnostico e terapeutico” – DM35706 –
Italian Ministry of Industry
2006-2011
Project FIRB LITBIO “
Laboratorio Interdisciplinare di Tecnologie Bioinformatiche
” – Italian Ministry of Research.
2007-2010 Project FIRB “ BIOBANCHE - Realizzazione di un sistema integrato a basso costo per la diagnosi multipla di malattie infettive, degenerative e tumorali che colpiscono i paesi in via di sviluppo
” – Italian Ministry of Research
2007-2010 Project FIRB “ MAST - MAgneti Superconduttivi per Tomografia ” – Italian Ministry of Research
Andrea Schenone
Senior Research Fellow
Leader of Activity JRA1
1978: Master Degree in Physics from the University of Genoa.
1981–1989: Researcher at the Health Physics Laboratory of San Martino Hospital in Genova.
1989–2000: Senior Researcher at the Biophysics Laboratory of the National Cancer Institute in
Genova.
1993: Guest Researcher at the National Institute of Mental Health in Bethesda (MD, USA).
1995–2006: Non-tenure-track positions at different departments of the University of Genoa
(System, Communication and Computer Science Department, Physics Department).
1997–2000: In-charge of the Medical Imaging Research Group at the National Cancer Institute in
Genova.
2000– 2003: Senior Scientific Consultant with companies and university departments.
2003–present: Senior Research Fellow at the System, Communication and Computer Science
Department of the University of Genoa.
He has been co-editor of two books on computational intelligence in biomedical applications.
He authored or coauthored about 60 scientific papers on biomedical images analysis, soft computing in biomedicine and biomedical Grid applications.
Projects
2000-2002
Project “
JUST - Just in time - health emergency interventions - Training of nonprofessionals by virtual reality and advance IT tools ” - European Commission DGXVI FP5.
2000-2003 Project 791 ex Legge 46 – “ Ambiente interattivo multimodale per la pianificazione dei trattamenti chirurgici e per la chirurgia guidata delle lesioni neoplastiche osteomicutanee
” –
Italian Ministry of Research.
2002-2004 Project FIRB Neuroinformatica (Italian node of the OCSE network of
Neuroinformatics) – Italian Ministry of Research
2002-2005
Project FIRB Grid.it “
Piattaforme abilitanti per griglie computazionali a elevate prestazioni orientate a organizzazioni virtual scalabili ” – Italian Ministry of Research.
2006-2011
Project FIRB LITBIO “
Laboratorio Interdisciplinare di Tecnologie Bioinformatiche
” – Italian Ministry of Research.
2007-2010 Project FIRB “ MAST - MAgneti Superconduttivi per Tomografia ” – Italian Ministry of Research
Livia Torterolo
Research Fellow
2004: Master degree cum laude in Biomedical Engineering from the University of Genoa.
2004–2006: consultant with several private companies related to grid computing technologies.
2006–2009: PhD student at the System, Communication and Computer Science Department of the University of Genoa.
2007: Visiting student at the Trinity College in Dublin, Ireland.
2009: Doctor of Philosophy degree in Biomedical Engineering from the University of
Genoa for researches concerning Grid applications for automated breast cancer prognosis through gene expression analysis.
2009–present: Research Fellow at the System, Communication and Computer Science Department of the University of Genoa.
Her research activity is focused on grid portal technology and grid-enabled biomedical applications.
She authored or coauthored about 10 scientific papers on grid-enabled biomedical applications.
Projects
2006-2011
Project FIRB LITBIO “
Laboratorio Interdisciplinare di Tecnologie Bioinformatiche
” – Italian Ministry of Research.
2.2.6
University of Foggia, Italy (UNIFG)
Profile
The contribution of UNIFG (http://www.medicina.unifg.it/sc_biomediche/dip_scibiomed.htm ) to this project is to recruit subjects and collect clinical, neuropsychological, biological and instrumental data. UNIFG will perform the adaptation for the e-infrastructure of the centralized analysis of EEG data to test the hypothesis that modern spectral EEG biomarkers of resting-state eyes-closed EEG rhythms (markers) are able to perform a low-cost preliminary personalized early diagnosis of AD and/or 1-year prognosis of cognitive decline in MCI and AD subjects as a function of genetic risk factors. The reason for his inclusion in this project is that he is the principal investigator of about 30 international peer-reviewed publications focused on the study of the relationships between EEG rhythms and cognition in mild cognitive impairment and Alzheimer’s disease subjects
Five relevant publications
Babiloni C, Pievani M, Vecchio F, Geroldi C, Eusebi F, Fracassi C, Fletcher E, De Carli C, Boccardi M,
Rossini PM, Frisoni GB. White-matter lesions along the cholinergic tracts are related to cortical sources of
EEG rhythms in amnesic mild cognitive impairment. Hum Brain Mapp. 2009 May;30(5):1431-43.
Babiloni C, Frisoni GB, Pievani M, Vecchio F, Lizio R, Buttiglione M, Geroldi C, Fracassi C, Eusebi F,
Ferri R, Rossini PM. Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease. Neuroimage. 2009 Jan 1;44(1):123-35. Epub 2008 Aug 16.
Babiloni C, Frisoni GB, Pievani M, Toscano L, Del Percio C, Geroldi C, Eusebi F, Miniussi C, Rossini PM.
White-matter vascular lesions correlate with alpha EEG sources in mild cognitive impairment.
Neuropsychologia. 2008;46(6):1707-20. Epub 2008 Apr 8.
Babiloni C, Frisoni GB, Pievani M, Vecchio F, Infarinato F, Geroldi C, Salinari S, Ferri R, Fracassi C,
Eusebi F, Rossini PM. White matter vascular lesions are related to parietal-to-frontal coupling of EEG rhythms in mild cognitive impairment. Hum Brain Mapp. 2008 Dec;29(12):1355-67.
Babiloni C, Frisoni G, Steriade M, Bresciani L, Binetti G, Del Percio C, Geroldi C, Miniussi C, Nobili F,
Rodriguez G, Zappasodi F, Carfagna T, Rossini PM. Frontal white matter volume and delta EEG sources negatively correlate in awake subjects with mild cognitive impairment and Alzheimer's disease. Clin
Neurophysiol. 2006 May;117(5):1113-29. Epub 2006 Mar 27.
Role in the Project
..
Key Personnel
Prof. C. Babiloni (Ph.D. in Biomedical sciences, Professor of Physiology at the University of Foggia, Italy) is an experienced neurophysiologist with a special interest in the evaluation of drugs for enhancing cognition in Alzheimer’s disease (AD). He has been developing EEG tools for early diagnosis and prognosis of.AD with Dr. Enzo Grossi of Bracco pharmaceutical industry. He published about 150 papers recorded in
PubMed on Neurophysiology and Clinical Neurophysiology (more than 30 on EEG and Alzheimer’s disease, more than 120 on EEG, the focus of his contribution to PHARMA-COG).
Prof. Babiloni is part of the European Networks of Excellence BIOPATTERN ( www.biopattern.org
; Chair:
Prof. Ifeachor), and DESCRIPA (http://eadc.alzheimer-europe.org/descripa.html; Chair: Prof. Visser) and
PHARMACOG (IMI2008; Chairs: Prof. Olivier Blin –UNIV. MARSEILLE- and Dr. Elaine Irving -
GLAXO-) focused on the development of screening guidelines and diagnostic criteria for early AD and drug discovery.
Personnel Involved in the project:
-
Prof. C. Babiloni, Ph.D, PI, (M): expert in quantitative EEG and cognitive neuroscience,
-
Prof. G. Cibelli, MD, PhD, (M): expert in physiology and neurology,
-
Prof. A. Bellomo MD, PhD, (M): expert in Psychiatry
-
Prof. P. Fiore MD, PhD , (M): expert in Rehabilitation
-
Dr. A. Petito, PhD, (F): expert in Neuropsychology
-
Dr. B. Lecce, PhD, (M): expert in Neurology
-
Dr. A. Valenzano, (F): expertise in Physiology,
-
Dr. F. Vecchio PhD, (M): expertise in quantitative EEG and cognitive neuroscience
-
Dr. C. Del Percio PhD,(M): expertise in quantitative EEG and cognitive neuroscience
Mr. M. De Rosas, Technician : expertise in quantitative EEG recording and analysis
2.2.7
SDN
Profile and Role in the ProjectSDN Foundation for Research and High Education in Nuclear
Diagnostic ( http://www.sdn-napoli.it/ ) was established in 2005 and was recognised as a research hospital and treatment centre (IRCCS or Istituto di Ricovero e Cura a Carattere Scientifico) through the Ministerial Decree issued on January 11, 2007
SDN is the first institute in Italy being approved as IRCCS in the field of Laboratory and Diagnostic
Imaging. Our Institution has 5 MRI units (one 3 Tesla, one 1.5 T, one low field open gantry, one ortho-clino MR, and one for joints), 3 PET/CT, 1 cyclotron for in house production of radiotracers, one SPECT/CT, 4 SPECT systems, 3 CT (one 64 sclices CT) ect. The Foundations is involved in several research projects. Among them there are projects related to neuroimaging post-processing. It been shown that early diagnosis in neurodegenerative diseases is feasible through imaging procedures. This is possible measuring atrophy of the cerebral structures involved in memory processes with magnetic resonance imaging (MRI) and their metabolic status through glucose consumption assessed with fluorodeoxyglucose (FDG)-PET. These procedures are usually performed in research laboratories where, however, heterogeneous post-processing and evaluation methods are applied. This prevents their diffusion in clinical centres that assess the vast majority of patients. In order to promote the dissemination of these advanced diagnostic tools to a broader patient base, it is necessary to identify which procedures can be usefully applied to achieve a correct diagnosis as early as possible. The SDN Foundation aims to validate a peculiar diagnostic procedure through the co-registration of MRI with FDG-PET. The acquired data will be verified by the partners unit and from the whole dataset it will be possible to test manual and automatic algorithms devoted to data analysis.
Once all the procedures will be standardised, there will be the possibility to overview the work done in peripheral clinical units. This could consist in a reading and post acquisition processing centre as well as second opinion session. To perform all the parts of the project and to develop the
dissemination of the results it is mandatory the high speed and real time connection among all the centres.
Key Personnel
Prof. Mario Rossi..
2.2.8
.
MAAT-G
Profile and Role in the Project
MAAT France is a consulting firm delivering IT solutions and professional services based on Grid and
Cloud computing with a special emphasis on e-Health. MAAT encompasses a rich expertise in the establishment and execution of International collaborations in the area, which it has capitalized upon its involvement in several initiatives. MAAT is part of the Spanish MAAT-G group ( www.maat-g.com
) – for which it is managing the biomedical applications product line. MAAT-G, on a larger scale, provides crosssectorial solutions including but not restricted to Information System, Customer Relationship Management and Data Integration. Over the last years, the group has acquired a stable yet solid position in Europe collaborating with several Regional Governments, Financial Institutions, Telecommunication Operators and
Professional Associations, and with offices/branches distributed over Toledo, Madrid, Valencia, Murcia,
Castilla-La Mancha, Castilla-León, Extremadura. At the International level, MAAT has implanted in Geneva in Switzerland, in London in the UK, in Bucaramanga in Colombia and more recently in Peru, Argentina and
France. Expressing its philosophy of continuously acquiring a rich and varied experience, MAAT promotes innovation and exchange of competencies through a robust and open team of researchers and engineers, motivated by the novelty and challenges of complex international projects.
Main tasks attributed to the organisation : SA1, ..
Previous experience related to those tasks: MAAT is involved in European/International collaborations,:
Mammogrid+ Europe: a private funded International project, which aims to develop a European platform for
Breast Cancer study, prevention and diagnostic (follow-up to EU FP5 MammoGrid project). - Health-e-
Child: a European FP6 funded project, which aims to develop a European platform for the horizontal and vertical integration of data, information and knowledge in Paediatrics, to support sophisticated decision support systems and knowledge discovery. neuGRID: a European FP7 funded project, which aims at developing a “google for brain imaging”, combining the storage capacity and computing power of the Grid with advanced brain mapping algorithms pipelines. EELA2: a European FP7 funded project aiming at deploying the EGEE gLite grid middleware technology in Latin American countries.
Through these initiatives, MAAT is playing an active role in the community by organising frequent scientific workshops and roundtables to encourage convergence and interoperability. As such it has been setting up a series of workshops so-called “Building Bridges in Healthgrids” (BBH) collocated with most relevant conferences in the field, such as the EGEE 2007 International Conference, the HealthGrid 2008 International
Conference, the EGEE 2009 User Forum and OGF25 events and anticipates to run a similar initiative at the up-coming MICCAI 2009 Conference.
Key personnel
Alfonso Rios (M). Dr. in Computer Sciences. CTO of MAAT-G group. Electronic Engineer and Phd in
Nuclear Physics at CERN (2000). Working in the field since 6 years, main research interests: Databases,
Data Mining, Supercomputing, Semantic Web and their applications to health, anthropology and high energy physics. He is the main author of MAAT-G core technology “G”. Principal Investigator: David Manset (M).
MPhil. Computer Sciences. CEO of MAAT France and Director of Biomedical Applications at MAAT-G group. Mphil in Computer Sciences, Coordination and Communication Systems (i.e. Artificial Intelligence).
Working in the field since 7 years, his main research interests are: Grid technologies, Model-Driven
Software Engineering. Technician: Jerome Revillard (M), PhD in Computer Sciences, Grid technologies, formal software architecture modelling methods. Technician: Jordi Paraire (M), MPhil in Computer
Sciences. Research interests: Grid networks, deployment, clusters administration, gridification of computing
intensive applications.
Relevant publications/patents:
1. Manset D et al. Gridifying Biomedical Applications: Experiences of the Health-e-Child Project. Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine and Healthcare. 2008
Information Science Reference (IGI Global).
2. Mesiti M, Manset D, et al. Data Integration Issues and Opportunities in Biological XML Data
Management. Open and Novel Issues in XML Database Applications: Future Directions and Advanced
Technologies. Accepted for publication.
3. Berlanga R, Manset D, et al. Medical Data Integration and the Semantic Annotation of Medical Protocols.
21 st IEEE International Symposium on Computer-Based Medical Systems (CBMS 2008). University of
Jyväskylä, Finland, June 17-19, 2008. Springer-Verlag ISBN 3-540-48273-3.
4. Jimenez-Ruiz E, Manset D, et al. The Management and Integration of Biomedical Knowledge:
Application in the Health-e-Child Project. Rios Proceedings of the OnToContent International Conference,
Montpellier, France. Lecture Notes in Computer Science 2006;4278:1062-7.
5. McClatchey R, Manset D, Solomonides T. Lessons Learned from MammoGrid for Integrated Biomedical
Solutions. Proceedings of the 19th IEEE International Symposium on Computer-Based Medical Systems –
CBMS ’06. Salt Lake City, US. IEEE Press 2006:745-50. ISBN 0-7695-2517-1.
2.2.9
.
Imperial College
Profile and role in the project
Imperial College ( http://www3.imperial.ac.uk/ ) is consistently ranked as one of the premier research institutions in the world and has extensive neuroimaging facilities. The PET cameras on the Hammersmith campus are operated by GE Healthcare and there are strong collaborative links with the GlaxoSmithKline
Clinical Imaging Centre ( CIC ) that operates a similar number of scanners on campus. We are in a unique position to conduct this project as we have accumulated many years of experience in the field and a PET database of neurochemical measures in normal volunteers and patients that is unrivalled in size in the UK.
The Unit performs ~650 PET scans per year the majority of which are for research in Neurology (Prof. David
Brooks and Prof. Paola Piccini), Epilepsy (Dr. Alex Hammers), Psychiatry (Dr. Oliver Howes) and Addiction
(Prof. David Nutt). The PET Methodology group has a strong track-record in developing extensive methodology (experimental design, mathematical modelling, statistical estimation), theoretical and applied, for the quantitative estimation of physiological parameters from PET studies. Current research focuses on computational chemistry and molecular modelling, neuro-informatics and data mining, image reconstruction, image corrections and kinetic modelling.
Development of Bespoken Neural Network Methodology for the analysis of PET biomarkers in
Neurological and Psyhiatric Disorders.
The alteration of functional end-points in Neurology and Psychiatry imaging with PET is usually subtle and requires sensitive tools to capture disease specific patterns. Artificial Neural Networks (ANN) are analytical methods that are perfectly suited for the task [1]. ANN are mathematical black boxes that instantiate nonlinear transformations of a number of inputs into outputs. ANN are “educated” to detect class-related features using matched inputs-output paired sets. One then can use image features as inputs to distinguish pathological populations (the outputs). We have already tested ANN in the analysis of PET image features
(FDOPA scans) to distinguish psychotics from normal controls. The results we recently published clearly show the significant potential of this application with ANN out-performing by far every other traditional linear analysis method [1]. However, application of ANN to PET data is still limited by the need of large training data-sets that usually are not available and grid-methodologies are ideal to expand training sets. We have the opportunity to apply short term this technology to 18 F-FDOPA studies in psychosis in our large existing data-base on normal controls, schizophrenics and prodromal schizophrenics and further test its generalisability and diagnostic potential with data-sets on similar populations at the Turku PET Centre.
Medium- and long-term plans will extend the technology to neurological cohorts ([11C]PIB, [18F]FDG,
[11C]PK11195).
Collaborators: Oliver Howes (CSC-KCL), Jarmo Hietala (Turku PET Centre).
References: Bose, S.K., Turkheimer, F.E., Howes, O.D., Mehta, M.A. , Cunliffe, R., Stokes, P.R., Grasby,
P.M. (2008) The application of an artificial neural network to classification of schizophrenic patients and healthy controls using [18F] Fluorodopa PET imaging. Schizophrenia Research, 106(2-3):148-55
Key personnel
Federico Turkheimer is Reader in Mathematical Neuroscience at the Division of Neuroscience, Imperial
College, London and is Head of the PET-Methodology Group at the MRC Clinical Sciences Centre at
Hammersmith Hospital. His main interest is in the application of mathematics and statistics to problems in neuroscience, particularly in imaging and genomics. He is an electronic engineer by training, holds a PhD in
Nuclear Medicine and has worked in PET and neuroscience for the past 17 years holding appointments at the National Institute of Mental Health (Bethesda), at the University of Cambridge and at the MRC Cyclotron
Unit (then Imanet) on the Hammersmith Campus.
Subrata Bose earned his PhD in Bioinformatics and MS in Computing from London Metropolitan University.
His research is focused on developing methodologies for the quantitative use of multi-modality medical images to examine the dynamic changes in selected functional processes and to investigate the effectiveness of new therapies in vivo. He is also interested in developing computational and statistical models/methods(Bioinformatics & Neuroinformatics) for processing and analysing clinical data,
Computerised System Validation and Audit including ICH GCP and 21 CFR part 11.
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2.2.10
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DBP-UW
Department of Biomedical Physics, University of Warsaw
Short Profile and Role in the Project
Department of Biomedical Physics, University of Warsaw (DBP UW) is active in the field of computational neuroscience, in particular in signal and image analysis and computer aided diagnosis. DBP UW focuses on development of advanced methods and algorithms for processing brain signals: EEG and ERP. The methods of estimation of functional connectivity in brain introduced by DBP UW are now used word wide for basic and applied studies.
The role of the DBP UW in the project will involve further development of the of the advanced methods of brain signal analysis especially tailored to the study of neuro- degenerative diseases with the aim of finding meaningful correlates with the patient condition and advancement of the disease. The multimodal integration of imaging and signal processing techniques will be performed with the aim of better understanding of the origins of neurological diseases and their treatment.
Web page: http://brain.fuw.edu.pl
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Key Personnel
Prof. Mario Rossi..
2.2.11
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EADC
Profile
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Role in the Project
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Key Personnel
Prof. Mario Rossi..
2.3
Consortium as a whole
[Describe how the participants collectively constitute a consortium capable of achieving the project objectives, and how they are suited and are committed to the tasks assigned to them. Show the complementarity between participants. Explain how the composition of the consortium is well balanced in relation to the objectives of the project.
If appropriate describe the industrial/commercial involvement to ensure exploitation of the results.
Show how the opportunity of involving SMEs has been addressed.
Sub-contracting: If any part of the work is to be sub-contracted by the participant responsible for it, describe the work involved and explain why a sub-contract approach has been chosen for it.
Other countries: If a one or more of the participants requesting EU funding is based outside of the EU Member states, Associated Countries and the list of International Cooperation Partner Countries40, explain in terms of the project’s objectives why such funding would be essential.
Additional partners: If there are as-yet-unidentified participants in the project, the expected competences, the role of the potential participants and their integration into the running project should be described.]
2.4
Resources to be committed
[ Recommended length for Section 2.4 – two pages.
In addition to the costs indicated on form A3 of the proposal, and the staff effort shown in section 1.3 above, please identify any other major costs (e.g. equipment).
Describe how the totality of the necessary resources will be mobilised, including any resources that will complement the EC contribution. Show how the resources will be integrated in a coherent way, and show how the overall financial plan for the project is adequate.]
40
See CORDIS web-site, and Annex 1 of the work programme.
Section 3.
I MPACT GARR+FBF+HSR
[Recommended length for the whole of Section 3 – ten pages]
3.1
Expected impacts listed in the work programme
[Describe how your project will put in place collaborative arrangements at the European level and what will be the perspectives for their long-term sustainability. Mention the steps that will be needed to bring about these impacts. Explain why this contribution requires a European (rather than a national or local) approach. Indicate how account is taken of other national or international research activities. Mention any assumptions and external factors that may determine whether the impacts will be achieved.]
The project will build upon the experience gained in NEUGRID and other initiatives …
Mention the steps that will be needed to bring about these impacts.
..
“The e-Infrastructure services will be expanded to more user communities and the needs of new application areas will be addressed.”
Explain why this contribution requires a European (rather than a national or local) approach. Indicate how account is taken of other national or international research activities. Mention any assumptions and external factors that may determine whether the impacts will be achieved.]
The international dimension is a key aspect in the so-called “Lisbon strategy’s” perspective:
“Research infrastructures top the list of areas where a European approach is called for, given the levels of funding involved and the need for them to be given the means to ensure they are able to provide services on a European scale. Issues related to major infrastructures cannot be dealt with effectively at national level. Needs in this area must be defined and decisions taken at European level.” 41
Furthermore, a special attention has been posed in this perspective to neighbouring countries. Instances of this strategy and its results are a number of initiatives co-funded so far by the
EC in the Baltic, the Balkans and the Mediterranean itself exploiting a recommendation from the
EC itself : “Exploration of the scope for using Article 169 to establish regional cooperation between countries participating in the Framework Programme which are geographically near to each other and are linked by historical ties or by common problems, such as EU countries and, where appropriate, associated Candidate Countries in the Mediterranean or Baltic regions.”
[Describe how your project will contribute towards the expected impacts on the access to – and use of – the pool of research infrastructures and what will be the new opportunities of access and use for researchers across the
EU. Mention the steps that will be needed to bring about these impacts.
Explain why this contribution requires a European (rather than a national or local) approach. Indicate how account is taken of other national or international research activities. Mention any assumptions and external factors that may determine whether the impacts will be achieved.]
..
“e-Infrastructures aim at developing a new research environment, building upon the ICT capabilities of existing infrastructures, in which all scientists have an easy-to-use controlled access to unique or distributed scientific facilities, regardless of their type and location in the world. Such an environment
41 Commission Communication: Building the ERA of knowledge for growth – CORDIS website, 6 April 2005 http://europa.eu.int/eur-lex/lex/LexUriServ/site/en/com/2005/com2005_0118en01.pdf
requires the emergence of "communities of practice" involving scientific users together with the computing and communication technologists to make the infrastructure layer transparent and adequately serving crossdisciplinary needs.” 42
Explain why this contribution requires a European (rather than a national or local) approach. Indicate how account is taken of other national or international research activities.
Mention any assumptions and external factors that may determine whether the impacts will be achieved.]
[Describe how your project will contribute towards an optimum development of research infrastructures at the
European level. Mention the steps that will be needed to bring about these impacts. Explain why this contribution requires a European (rather than a national or local) approach. Indicate how account is taken of other national or international research activities.
Mention any assumptions and external factors that may determine whether the impacts will be achieved.]
3.2
Dissemination and/or exploitation of project results, and management of intellectual property
[Describe the measures you propose for the dissemination and/or exploitation of project results among operators/users of research infrastructures, and the management of knowledge, of intellectual property, and of other innovation-related activities arising from the project.]
3.3
Contribution to socio-economic impacts
42 FP7 Capacities Work Programme – Part 1 – Research Infrastructures – pag …
Section 4.
E THICAL I SSUES
[Describe any ethical issues that may arise in their proposal. In particular, you should explain the benefit and burden of their experiments and the effects it may have on the research subject. Identify the countries where research will be undertaken and which ethical committees and regulatory organisations will need to be approached during the life of the project.
Include the Ethical issues table below. If you indicate YES to any issue, please identify the pages in the proposal where this ethical issue is described. Answering 'YES' to some of these boxes does not automatically lead to an ethical review 43 . It enables the independent experts to decide if an ethical review is required. If you are sure that none of the issues apply to your proposal, simply tick the YES box in the last row.
Notes:
For further information on ethical issues relevant to ICT, see Annex 5 of this Guide.
Only in exceptional cases will additional information be sought for clarification, which means that any ethical review will be performed solely on the basis of the information available in the proposal.
The following special issues should be taken into account:
Informed consent: When describing issues relating to informed consent, it will be necessary to illustrate an appropriate level of ethical sensitivity, and consider issues of insurance, incidental findings and the consequences of leaving the study.
Data protection issues: Avoid the unnecessary collection and use of personal data. Identify the source of the data, describing whether it is collected as part of the research or is previously collected data being used. Consider issues of informed consent for any data being used. Describe how personal identify of the data is protected.
Use of animals: Where animals are used in research the application of the 3Rs (Replace, Reduce, Refine) must be convincingly addressed. Numbers of animals should be specified. Describe what happens to the animals after the research experiments.
Human embryonic stem cells: Research proposals that will involve human embryonic stem cells (hESC) will have to address all the following specific points: the necessity to use hESC in order to achieve the scientific objectives set forth in the proposal. whether the applicants have taken into account the legislation, regulations, ethical rules and/or codes of conduct in place in the country(ies) where the research using hESC is to take place, including the procedures for obtaining informed consent; the source of the hESC the measures taken to protect personal data, including genetic data, and privacy; the nature of financial inducements, if any.
To ensure compliance with ethical principles, the Commission Services will undertake ethics audit(s) of randomly selected projects at its discretion
A web site is being prepared aiming to provide clear, helpful information on ethical issues.]
To the best of our knowledge, no ethical issues involving research intervention on human beings, research on human embryos and human embryonic stem cells non-human primates and animal in general are directly associable with the proposed project.
As to privacy and informed consent, no issues could be identified as directly related to the DECIDE infrastructure and activities; however, some eHealt applications envisaged in the set of the DECIDE supported ones may involve sensible issues. For this reason, applications from this class will be carefully evaluated prior the porting and sensitive cases will be submitted to the EC services for endorsement.
43 Projects raising specific ethical issues such as research intervention on human beings; research on human embryos and human embryonic stem cells and non-human primates are automatically submitted for ethical review
ETHICAL ISSUES TABLE
Informed Consent
• Does the proposal involve children?
• Does the proposal involve patients or persons not able to give consent?
• Does the proposal involve adult healthy volunteers?
• Does the proposal involve Human Genetic Material?
• Does the proposal involve Human biological samples?
• Does the proposal involve Human data collection?
Research on Human embryo/foetus
• Does the proposal involve Human Embryos?
• Does the proposal involve Human Foetal Tissue / Cells?
• Does the proposal involve Human Embryonic Stem Cells?
Privacy
• Does the proposal involve processing of genetic information or personal data (eg. health, sexual lifestyle, ethnicity, political opinion, religious or philosophical conviction)
• Does the proposal involve tracking the location or observation of people?
Research on Animals
• Does the proposal involve research on animals?
• Are those animals transgenic small laboratory animals?
• Are those animals transgenic farm animals?
• Are those animals cloning farm animals?
• Are those animals non-human primates?
Research Involving Developing Countries
• Use of local resources (genetic, animal, plant etc)
• Benefit to local community (capacity building ie access to healthcare, education etc)
Dual Use
• Research having potential military / terrorist application
ICT Implants
• Does the proposal involve clinical trials of ICT implants?
YES PAGE
I CONFIRM THAT NONE OF THE ABOVE ISSUES APPLY TO MY PROPOSAL
Glossary
References
[Ref.1] NEUGRID..
[Ref.2] ETC ETC
