DICOM Ontology (DO) Project

Daniel L. Rubin M.D., M.S.Clinical Asst. Professor of Radiology

Research Scientist, Center for Biomedical Informatics Research

Stanford University

David S. Channin, MDAssociate Professor of Radiology

Northwestern University

Curtis P. Langlotz, MD, PhDAssociate Professor of Radiology

University of Pennsylvania

Charles E. Kahn, Jr., MD, MSProfessor of Radiology

Medical College of Wisconsin

David Clunie, MDChief Technology Officer

RadPharm Inc.

DICOM

• DICOM is global standard for medical imaging• Comprises combined knowledge from

engineers and radiologists from academia and industry

• Subsets of DICOM used extensively in all caBIG Imaging Workspace projects

Many projects refer to parts of DICOM

The pixel at the tip of the arrow [coordinates (x,y)] inthis image[DICOM: 1.2.814.234543.23243]represents the Ascending Thoracic Aorta[SNOMED:A3310657]

AIM Schema includes information from DICOM

Challenges with DICOM

• DICOM lacks a reference information model• Hinders interoperability in applications• Inconsistent use of controlled terminology or relations

• Specified in PDF documents; not computable• Duplication of effort in workspace projects• Potential conflicts among different models

that represent same imaging information• DICOM is huge—time consuming to review

The DICOM Standard is caBIG

DO Project Goals

• Create ontology based on DICOM• Make explicit the entities and relations in DICOM• Harmonize with other ontologies (RadLex, SNOMED)• Harmonize with other imaging projects (AIM)

• Evaluate impact by studying use cases related to existing projects in the workspace

DO ProjectPhase I Goals

• Requirements gathering• What subset of DICOM is relevant to caBIG?• What content should be included in the DICOM ontology?• Who should build this?

• Define scope of Phase II• The parts of DICOM that will be reviewed• The actual building of the ontology• Controlled terminology identification/reconciliation tasks• Evaluation via use cases

• Proof-of-concept presentation at RSNA 2007

Phase I Activities to define scope of Phase II

DICOM Ontology Project Activities

• Determine the requirements for the DICOM Ontology

• Identify the expertise of participants required to create the DICOM Ontology (DO)

• Determine the extent to which DICOM uses controlled terminology

• Assess the gap between the DO and caBIG™ terminology resources (EVS and caDSR)

• Specify operations on the ontology (e.g., DO XML)

DO Progress #1

• SCOPE DEFINITION of the DICOM standard to define the work to be done in Phase II• We reviewed DICOM Information Object Definitions

(IODs)—both image- and non-image objects relevant to clinical trials

• We excluded • Non-radiology image as well as RT objects (could be added

in a future phase, especially the RT objects)

• We included• All image types in clinical trials.

• Relevant parts of DICOM used for DO will be part 3 and some of part 16

Some included IODs

• A.2 COMPUTED RADIOGRAPHY IMAGE INFORMATION OBJECT DEFINITION• A.3 COMPUTED TOMOGRAPHY IMAGE INFORMATION OBJECT DEFINITION• A.4 MAGNETIC RESONANCE IMAGE INFORMATION OBJECT DEFINITION• A.5 NUCLEAR MEDICINE IMAGE INFORMATION OBJECT DEFINITION• A.6 ULTRASOUND IMAGE INFORMATION OBJECT DEFINITION• A.7 ULTRASOUND MULTI-FRAME IMAGE INFORMATION OBJECT DEFINITION• A.14 X-RAY ANGIOGRAPHIC IMAGE INFORMATION OBJECT DEFINITION• A.15 X-RAY ANGIOGRAPHIC BI-PLANE IMAGE INFORMATION OBJECT DEFINITION • A.16 X-RAY RF IMAGE INFORMATION OBJECT DEFINITION• A.21 POSITRON EMISSION TOMOGRAPHY IMAGE INFORMATION OBJECT

DEFINITION• A.26 DIGITAL X-RAY IMAGE INFORMATION OBJECT DEFINITION• A.27 DIGITAL MAMMOGRAPHY X-RAY IMAGE INFORMATION OBJECT DEFINITION• A.36 ENHANCED MR INFORMATION OBJECT DEFINITIONS• A.38 ENHANCED COMPUTED TOMOGRAPHY IMAGE INFORMATION OBJECT

DEFINITION• A.47 ENHANCED X-RAY ANGIOGRAPHIC IMAGE INFORMATION OBJECT DEFINITION• A.48 ENHANCED X-RAY RF IMAGE INFORMATION OBJECT DEFINITION

Some excluded IODs

• A.17 RT IMAGE INFORMATION OBJECT DEFINITION• A.18 RT DOSE INFORMATION OBJECT DEFINITION• A.19 RT STRUCTURE SET INFORMATION OBJECT DEFINITION• A.20 RT PLAN INFORMATION OBJECT DEFINITION• A.29 RT BEAMS TREATMENT RECORD INFORMATION OBJECT DEFINITION• A.30 RT BRACHY TREATMENT RECORD INFORMATION OBJECT DEFINITION• A.31 RT TREATMENT SUMMARY RECORD INFORMATION OBJECT DEFINITION• A.49 RT ION PLAN INFORMATION OBJECT DEFINITION• A.50 RT ION BEAMS TREATMENT RECORD INFORMATION OBJECT DEFINITION• A.9 STANDALONE OVERLAY INFORMATION OBJECT DEFINITION• A.10 STANDALONE CURVE INFORMATION OBJECT DEFINITION• A.12 STANDALONE MODALITY LUT INFORMATION OBJECT DEFINITION• A.13 STANDALONE VOI LUT INFORMATION OBJECT DEFINITION• A.22 STANDALONE PET CURVE INFORMATION OBJECT DEFINITION• A.23 STORED PRINT INFORMATION OBJECT DEFINITION• A.24 HARDCOPY GRAYSCALE IMAGE INFORMATION OBJECT DEFINITION• A.25 HARDCOPY COLOR IMAGE INFORMATION OBJECT DEFINITION

DO Progress #2

• We defined required expertise for building DO• Intimate familiarity with DICOM standard and its

documentation, and how to turn that documentation into software applications

• Expertise in imaging informatics and in using DICOM for developing software

• Ontology building expertise• Terminology expertise (radiology-related terminologies)• Expertise in caBIG methodologies (specifically caDSR,

EVS)

DO Progress #3

• Determining the extent to which DICOM uses controlled terminology• The Phase II protocol will require harmonization of

DICOM with RadLex, SNOMED and LOINC, ISO standards (e.g., country codes).

• Assess the gap between the DO and caBIG™ terminology resources (EVS and caDSR)• An important, but time-consuming task, needing to be

done in a future phase• Will be simpler after first harmonizing with RadLex

Requirements for Phase II

Phase II Project Tasks

• Build the DO from the current DICOM standard• Reconcile the DO with other information

models in the Imaging Workspace• Identify any Intellectual Property restrictions• Identify the scope of Phase II and possible

future phases• Specify a mechanism by which the quality and

integrity of the DO can be tested against the formal definition of the DICOM Standard

• Specify a mechanism for on-going maintenance of the DO

• Define future phases, if needed

Steps for Building the DO

• Translate DICOM standard to structured format

• Critical review of the DICOM standard once DICOM is in ontological format

• Assemble the ontological components and build the DO

Translating DICOM to Structured Format

• Ontology building could be daunting—the DICOM standard is huge (17 parts, approx 2500 pages) and distributed as text documents.

• Information pertaining to the DO is spread across several relevant parts • Part 3: information models, information object definitions (IODs)

and modules and macros • Part 6: data dictionary, including the type and multiplicity of each

data element used as an attribute within objects defined in Part 3• Part 16: value sets (context groups) referenced by the information

objects in Part 3 and templates for structured reports• Approach: translate the DICOM standard into a

structured format that can be imported into an ontology authoring tool such as Protégé

• Leverage existing XML transformations, modifying them to translate DICOM to RDF so that it can be directly be imported into Protégé, and then manipulated to create DO

Critical Review of DICOM while Building Ontology

• Encode DICOM E-R Diagrams• These currently exist in non-computable format in DICOM

standard• Will produce computable representations of E-R diagrams

and harmonize with other semantics components of the DO

• Reconcile DO for modeling inconsistencies in DICOM• Overloaded data elements in the same concept at different

levels of DICOM Pixel Spacing (0028,0030) are defined• Same concept but different value sets of same level of info

model Rescale Type (0028,1054)• Same concept, but different descriptions Imager Pixel

Spacing (0018,1164) is defined • Same concept, but different conditionality Lossy Image

Compression Ratio (0028,2112)

Proposed Strategy for Evaluation

• Use cases: AIM, NCIA, IQ, XIP, AVT, gACRIN projects. Does DO provide all the imaging knowledge needed? • AIM—references to image context information• NCIA—info about image technique, acquisition,

demographics• IQ—same as NCIA• XIP—any structured information relating to • AVT—attributes related to comparing images at

different time points• gACRIN—more accurate modeling of ACRIN

warehouse

Acknowledgements and Support

• caBIG Imaging Workspace, Subcontract from Booz-Allen & Hamilton, Inc.

Stay tuned for Phase II !

Contact info:

rubin@med.stanford.edu