Quantitative Medical Imaging
October Monthly Call
October 13, 2011
WITH FUNDING
SUPPORT
PROVIDED BY
NATIONAL
INSTITUTE OF
STANDARDS
AND
TECHNOLOGY
Andrew J. Buckler, MS
Principal Investigator
Agenda
• Domain, Web site, and License
• Review of On-site Meeting at NCI
• App updates:
– Specify
– Formulate
– Execute
– Analyze
– Package
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
2
On-screen demonstration
DOMAIN, WEB SITE, AND LICENSE
(see www.qi-bench.org)
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
3
Value proposition of QI-Bench
(as expressed to NCI partners)
• Efficiently collect and exploit evidence establishing
standards for optimized quantitative imaging:
– Users want confidence in the read-outs
– Pharma wants to use them as endpoints
– Device/SW companies want to market products that produce
them without huge costs
– Public wants to trust the decisions that they contribute to
• By providing a verification framework to develop
precompetitive specifications and support test
harnesses to curate and utilize reference data
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
4
Opportunities to Demonstrate
Meaningful Use of caBIG Technologies
• Coordinated program relating vocabulary and
physical standards
• Driving use case for swBIG
• Contribute to so-far elusive collaboration
infrastructure for QIN
• Augment TRANSCEND’s current contributions in
genome-based biomarkers to imaging
• Testbed example for Open Source Development
Initiative
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
5
QI-Bench Program Needs
(as expressed to NCI partners)
Specify (partially funded)
– Utilize robust backend database using RDB/RDF SPARQL in place of current XML
– Complete app, incl. integrate presently separate AIM and QIBO portions
Formulate (least funded)
– Integrate NBIA Connector, NIST DICOM-based query, and caB2B
– Use QIBO for OBO concept driven information modeling (w/ BRIDG and LS-DAM)
Execute (funded)
– Support serial studies / change analysis (augmenting absolute measures)
– Black-box API harness (augmenting white-box reference methods)
– Support reader studies (using ClearCanvas with AIM)
Analyze (least funded)
– Issues as identified in gap analysis vis-à-vis current MVT
– Extend schema as per W3C best practice for certainty, severity, strength,
relevance relations to support outcome studies
Package (partially funded)
– Converge imaging and device standards in SDTM
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
6
On-screen demonstration
SPECIFY PROTOTYPE
(see http://specify.qi-bench.org/user_session/new)
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
7
Thoughts on Formulate
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
8
Thoughts on Formulate
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
9
Use of Execute for 3A Challenge
• pilot3A:
– QA/QC
– Lab Protocol
• Logistics:
– Participant agreement
– Registrar
– Timeline
• Pivotal
– Spreadsheet -> metadata
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
10
Analyze Status
• File System Engineering\User Needs\Definitive Metrology Terms
for QI 2011-09-26.docx
• File ..\QIBA and Quantitative Imaging\Approach to Compliance
2011 08 15.ppt
Near-term 1. Process the lesion reads on the same 40 lesions used in the 1A pivotal as a 7th
reader using 1A STATA method and compare results. [QI-Bench<->1A STATA]
2. Extend the STATA analysis to the 408, publish this result as the first QI-Bench
publication (after QC).
Mid-term
Longer-term
October 13, 2011
3.
Process the 6 selected lesions from the MVT demonstrator using the 1A
STATA method and compare results. [MVT<->1A STATA]
4. Process the lesion reads on the same 6 lesions used in the MVT demo set as
a 7th reader and compare results. [QI-Bench<->MVT]
5. Convert 1A STATA analysis to R and compare the results on the 408. [STATA<>R]
6. Extend MVT to use the created R scripts (and fill other gaps).
7. Re-do analyses to verify that results come out the same.
Convert to R-based, MVT-implemented analysis.
Perform and analyze
other studies (e.g., 1C,
3A, 1187, other modes,
etc. using STATA analysis
method.
QI-Bench: Optimizing Performance through Characterization
11
Package: NCI-CDISC Imaging CRF Project
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
12
Package: Metadata Table Mappings
Domain
SDTM
Variabl
e Name
Variabl
e
Label
Definiti
on
DM
BRTHDT
C
Patients
Date of
Birth
Date/ti
me of
birth of
subject
CDASH/SDTM
Variables
ACRIN
DICOM
NBIA
Data
Element
BRIDG
Data
type
(0010,
0030)
Patient's
Date of
Birth
Biologic
Entity.
birthDat
e*
CHAR*
ACRIN
Reference
DICOM
Tag
October 13, 2011
NBIA
DE
Controll
ed
Terms,
Codelist
or
Format
NA
Role
Record
Qualifier
Implem
entation
Notes
Core
Permissi
ble
Point to
NCIt, RadLex,
etc. here
ISO8601 &
21090
SDTM
Role
QI-Bench: Optimizing Performance through Characterization
13
During the Coming Month
Annual Report to NIST
– Structured similarly to semi-annual
User View Priorities
– Lab Protocol
– StudyDescription spreadsheet as Reference Data Set Manager metadata
Developer Toolset
– Data center in place: 24 Processor cores, 40 GB Main Memory, 12 TB Disk storage,
Red Hat Linux, Windows Server 2008 R2, and Mac OS X
– Next up: Git and Jira
Continued Engagement with caBIG
– Open Source Development Initiative
– Driving use case for semantic infrastructure
– Deployment on TCGA and/or TRANSCEND programs
QI-Bench Face to Face
– As combined function of 3A Challenge Workshop
– Tuesday November 15 in Gaithersburg
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
14
October 13, 2011
QI-Bench: Optimizing Performance through Characterization
15