DICOM Grid Interface Service for Clinical and Research PACS:
A Globus Toolkit Web Service for Medical Data Grids
S.G. Erberichab, M. Bhandekarb, M.D. Nelsonb, A. Chervenakc, C. Kesselmanc
aDepartment
of Radiology, Childrens Hospital Los Angeles, Keck School of Medicine, Univ. of Southern California
of Biomedical Engineering, Viterbi School of Engineering, Univ. of Southern California
cGrid Computing Division, Information Science Institute, Univ. of Southern California
bDepartment
Abstract.
Picture Archiving and Communication Systems (PACS) have become the
standard for digital image warehousing within hospitals and practice networks.
However PACS are monolithic systems not intended to communicate in a flexible and
dynamic way to affiliated hospitals or to support ad-hoc tele-radiology between outside
physicians or radiologists. Enterprise PACS provides only limited and mostly vendor
restricted access to outside affiliates. Here we present an extension to traditional PACS
which bridges between institutional PACS and dynamic medical data Grids. A data Grid
is a collection of IT services which provide access control, distributed data
management, and publication and discovery methodologies. We describe how existing
data Grid technology can be used toward a medical data Grid by adding a DICOM Grid
Interface service. The service implements an Open Grid Service Architecture (OGSA)
standard service based on the Web Service Resource Framework (WSRF)
implementation of the Globus Toolkit release 4 – a OGSA compliant open-source Grid
middleware. The OGSA compliance preserves interoperability among Grid technology
providers and is therefore of special importance in medical data Grids federating various
IT infrastructures.
Keywords: DICOM, PACS, Grid PACS, Globus Toolkit 4, OGSA, Data Grid
1. Introduction
Picture Archiving and Communication Systems (PACS) have become the standard for
digital image warehousing within hospital and practice networks. However PACS are
monolithic systems not intended to communicate in a flexible and dynamic way to
affiliated institutes or to support ad-hoc tele-radiology between outside physicians or
radiologists. Enterprise PACS [1] provides only limited and mostly vendor restricted
access to outside affiliates.
Major limitations to integrate PACS beyond institutional borders can be identified as:
(i) Data transport and access security: Images need to be protected from third-party
capture and manipulation. Therefore images need to be strongly decrypted when
traversing public domain networks like the Internet. Stringent user authentication is
critical when spawning access control over several institutions. User authorization to
specific services and image data needs to be defined and enforced. Both require an
umbrella security layer over the local PACS security. (ii) Systematic and standardized
methodology to store and query/retrieve images in distributed environments. Images
need to be uniquely identifiable when storage is federated by indexing or physical
collection. PACS is designed as a peer-to-peer client/server model and therefore lacks
the ability to dynamically discover images within a distributed environment.
A promising approach to overcome these limitations is to create a middleware
architecture layer between PACS on one side and image producers and consumers on
the other side. Such an approach would keep the existing technology and investments
on both sides in place while extending functionality and scope of operations. Several
middleware solutions have been suggested to overcome the limitations. One common
methodology is to consolidate local PACS in a single global PACS using some sort of
peer-to-peer secure network connections [2,3], e.g. secure socket layer (SSL) or
transport layer security (TLS), to the participating institutions. However such solutions
carries several disadvantages, including low response times during high demand, single
point of failure, and high administrative overhead for virtual private network (VPN) or
SSL connection methodologies.
Grid technology has emerged as a solution in industry and academia for heavy datadriven and networked collaborative environments. Grid computing started in the late
1990’s when data management and simulation projects in physics, climate, and
astronomy domains at the Terabyte scale faced similar data handling and access
problems [4]. Grid technology presents itself as promising candidate to overcome the
described data management and access limitations. Manca et al. originally introduced
the concept [5] of using open-source Grid technology to provide storage class provider
(SCP) and query/retrieve DICOM classes using the Storage Resource Broker (SRB)
technology [6]. Based on their and commercial implementations derived Grid based
PACS [7] and disaster backup/archive solutionsz in experimental and commercial
environments [8-10] have been recently presented. Current activities utilize commercial
Grid implementation, open-source Globus Toolkit release 3, and Moebius [11]
technologies.
This previous work clearly demonstrated that Grid technology is well suited to integrate
and link PACS into a resource accessible to all participating institutions. However the
diversity of current Grid implementations, commercial or open-source, identifies
lacking interoperability between Grid technologies as a major road-block for further
investment and development in Grid technology. This is because Grid technology
lacked previously a standard definition for service interfacing and interoperability. The
Open Grid Service Architecture (OGSA) is the response to this missing Grid standard
[12] and defines the architecture for future Grid services.
Here we present an extension to traditional PACS which bridges between institutional
PACS and a medical data Grid following the OGSA standard. The focus of this work is
on a new service, the OGSA compliant DICOM Grid Interface Service (DGIS), and its
integration into existing OGSA compliant services for data management, publication,
and discovery. DGIS is based on the Web Service Resource Framework (WSRF)
implementation of the Globus Toolkit release 4 (GT4). GT4 [13] is one of the first
OGSA compliant open-source Grid middleware available today. The current version of
DGIS implements Verification, SCP, and Q/R DICOM classes and allow transparent
DICOM interoperability between local image producers/consumers (image
modalities/readers). The collection of OGSA services used in the is work together
implement an Enterprise PACS solution – a medical image data Grid.
2. Methods
We have designed and implemented an Open Grid Service Architecture compliant Web
Service – the DICOM Grid Interface Service (DGIS) - which provides secure DICOM
image communication over Internet between dynamic end-points, e.g. PACS, modality,
or display workstation. The DGIS currently implements three of the most relevant
DICOM classes related to PACS operations: (i) Verification Service Class, (ii) Storage
Service Class, and (ii) Query/Retrieve Service Class. Platform independent Java
language and run-time environment has been used in conjunction with open-source
Globus Toolkit release 4 to implement the Grid connectivity. Pixelmed, an open-source
Java DICOM library, has been used to implement DICOM services. We used a PC Intel
Pentium4/HT system (3.2Ghz, 2GB RAM, 400GB RAID1) running SuSE Novell 9.3
operating system as development platform.
Verification Service Class: DGIS implements the C-ECHO (Verification) and AASSOCIATE (Association Negotiation) responses for a Storage Class Provider (SCP).
Image Transfer from Hospital to Grid-PACS
Hospital
Vendor Modality
or PACS
(1) DICOM
DICOM Grid
Interface Service
(DGIS)
Grid-PACS
Grid Service
Registry (GSR)
(2.2) publish
(2.3) query
(2.1) register new series
(3.2) replicate
Replica Location
Service (RLS)
Meta Catalog
Service (MCS)
(4.1) discover new files
(4.3) update
(3.1) discover new files
(3.3) update
Data Replication
Service (DRS)
(4.2) replicate
Data Replication
Service (DRS)
Figure 1: OGSA services and workflow for Grid PACS implementation. The DICOM Grid interface
service executed DICOM storage requests of new images into the data Grid using standard GT4 data Grid
services MCS, RLS, and DRS for publication and storage.
Storage Service Class Provider: DGIS runs at an image producer site (e.g. a hospital)
and accepts SCP requests and stores DICOM images in a local gateway buffer (Figure
1). Each received image series is archived in a loss-less compressed file record and an
XML DICOM schema is created from the series header information comprising patient,
study, and acquisition DICOM object attributes. The Series UID of each series is used
as unique key to identify and locate series records inside the Grid. A local instance of
the GT4 Data Replicator Service (DRS) receives the series file record and a request for
transmission to a archiving host on the Grid. DRS invokes GT4 services RFT and at the
transport level GridFTP for data transport. The GT4 Replica Location Service (RLS) is
invoked to publish the physical location (URL) of the new series record. The XML
schema of each series is sent to the Meta Catalog Service (MCS).
Query/Retrieve Service Class Provider: DGIS provides two query/retrieve interfaces
(Figure 2): (i) The standard DICOM Q/R service interface and (ii) a Web Services
interface. In (i) the DICOM interface implements the C-FIND, C-MOVE, and C-GET
operations for patient, study, series, or composite object instances. C-FIND invokes a
SQL/XML query to the MCS and returns a C-FIND response object containing
matching attributes. C-MOVE and C-GET invoke an MCS query and identify requested
series records based on the series UID. Then DRS is invoked to retrieve series record(s)
from the Grid storage if not available at the local gateway. C-STORE/-GET execution
transmits images from DGIS to the third-party (C-MOVE) or calling DICOM receiver
(C-GET). Interface (ii) exposes web service methods to initiate a C-MOVE instance to a
third-party end-point, e.g. display workstation. This interface allows web–based
query/retrieve and DICOM transfer initiation through a Grid Web-Portal by authorized
users anywhere in the Grid.
Image Transfer from Grid PACS to Hospital
Hospital
Vendor Workstation
(4) DICOM
DICOM Grid
Interface Service
(DGIS)
Grid-PACS
(1.1) Login
(2.1) Query series
(3.1) Select and retrieve
(3.2) Request series
Grid Service
Registry (GSR)
Grid Web Portal
(3.5) Publish replica
(4.2) Query location
(1.2) Certificate (2.2) Query catalog
(3.3) Retrieve series
Replica Location
Service (RLS)
MyProxy
Meta Catalog
Service (MCS)
(3.4) Alternate Retrieve series
Data Replication
Service (DRS)
Data Replication
Service (DRS)
Figure 2: Image workflow from Grid to participating institute. Images can be query/retrieved using
DICOM or by Web Service request to DGIS. Images are discovered in the Meta Catalog and located
using Replica Location Service. DRS is than invoked to replicate an instance of the requested images to
DGIS, followed by pushing the image to the requested destination, e.g. vendor workstation.
Authorization to use DGIS and invoked services is determined by X.509 certificates. A
host-based certificate is used for DICOM invoked services. Delegated (proxy)
certificates are used for Web Service initiated requests.
3. Results
The DGIS provides a standard DICOM v3 compliant interface for SCP and Q/A
services. We have used a subset of three remote sites out of the Children’s Oncology
Group Grid (22 hospitals) as testbed for the reference implementation. We selected the
sites in respect to geographical disperse locations: USC network (Children’s Hospital
Los Angeles), California (Stanford Medical Center), East-coast (NCI/NIH).
DICOM interface performance for 1000 files (150KB each, MR DICOM, 256x256, 16
Bit voxels) averages 3.26MB/s.
Table 1: Grid transport performance (secure GridFTP protocol) of 1000 series records (1 MB each,
lossless LZW compressed) between CHLA/USC Grid center and geographically dispersed Grid nodes.
Geographical Distribution
Destination
Average transport performance
City Level
USC, Los Angeles, CA
3.8 MB/s
State Level
Stanford Medical Center, Palo 1.45MB/s
Alto, CA
National Level
National Cancer Center
0.28MB/s
(NCI/NIH), Bethesda, MD
5. Conclusion
Grid technology provides a dynamic and flexible light-weight solution to expand
traditional PACS and Enterprise PACS installations to become shared resources on the
Grid. The DGIS is the key service to bridge the hospital DICOM PACS domain and the
Grid domain to share medical images among institutions. Key to the acceptance of such
a Grid extension is that DGIS exposes relevant DICOM Service Classes and thus reuses
existing DICOM based SCU and Q/R modalities. The Web Service interface on the
other hand provides additional query capabilities based on the meta catalog information
which goes beyond DICOM object attributes, e.g. based on anatomical annotations or
complex ontology. The latter is highly relevant for fused data derived from multi-modal
images or image processing or data mining.
6. Acknowledgement
This work is supported by NIH grant UO1-CA97452.
References
[1] alSafadi Y, Lord WP, Mankovich NJ. PACS/information systems interoperability using Enterprise
Communication
Framework. IEEE Trans Inf Technol Biomed. 1998 Jun;2(2):42-7.
[2] Brelstaff G, Moehrs S, Anedda P, Tuveri M, Zanetti G. Internet patient records: new techniques. J
Med Internet Res. 2001 Jan-Mar;3(1):E8.
[3] Bennett WF, Spigos DG, Vaswani KV, Terrell JE. Cable modem access to picture archiving and
communication system images using a web browser over the Internet. Digit Imaging. 2000 May;13(2
Suppl):93-6.
[4] http://eu-datagrid.web.cern.ch/eu-datagrid
[5] Manca S, Leoni L, Giachetti L, Zanetti G, A Virtual Data Grid Architecture for Medical Data using
SRB. Proceedings Europacs 2004, Trieste, p475-78
[6] Arcot Rajasekar, Michael Wan, Reagan Moore, Wayne Schroeder, George Kremenek, Arun
Jagatheesan, et al. Storage Resource Broker - Managing Distributed Data in a Grid, Computer Society of
India Journal, Special Issue on SAN, Vol. 33, No. 4, pp. 42-54 Oct 2003
[7] Espert IB, Garcaa VH, Quilis JD. An OGSA Middleware for managing medical images using
ontologies. J Clin Monit Comput. 2005 Oct;19(4-5):295-305.
[8] King EB, Brent L, Zhou Z, Documet J, Huang HK. The data storage grid: the next generation of faulttolerant storage for backup and disaster recovery of clinical images, Proc. SPIE Vol. 5748, p. 208-217,
Medical Imaging 2005: PACS and Imaging Informatics; Osman M. Ratib, Steven C. Horii; Eds., Apr
2005
[9] http://www.bycast.com
[10] http://www.i3archive.com
[11] http://projectmobius.osu.edu/publications.php
[12] http://forge.gridforum.org/projects/ogsa-wg
[13] http://globus.org/toolkit