1. DICOM – A Preclinical Perspective
AK Narayan, Kishan Harwalkar, Kshitija Thakar
Philips Healthcare,
April 09, 2008

2. Agenda Introduction to Preclinical IMALYTICS Workspace
Information Model Requirements
Mapping to DICOM
DICOM Constraints on Preclinical
Challenges and Future Work
Conclusions

3. Research Workflow
Research is characterized by exploratory and/or hypothesis-driven programs often supported by grants to either discover or explore new insights into biological processes.
The systematic discovery and development of biomarkers, drugs, and therapies that will ultimately be translated from animal models to human should they prove promising during preclinical studies.
Exploratory or Hypothesis driven
Statistically Significant Results
Enabled by
Pre-Clinical
Workspace
Transition to ...

4. Preclinical Imaging Fundamental Understanding of Biology/ Biochemistry
“Researchers are not mouse doctors”
Fundamental
Understanding
of Biology/ Biochemistry
Design and
Evaluation of new
Biomarkers (drugs)
(diagnosis/therapy)
Test Bed for new Imaging
Technologies
transfer in-vitro
to in-vivo
verify models
dynamics and kinetics
efficacy (candidate
selection)
dosing
small size prototypes
low capital investment
POC (proof of concept)
Massoud T.F., Gambhir S.S.; Molecular Imaging in living subjects: seeing fundamental biological processes in a new light; Genes Dev., 17, , 2003
Rudin M., Weissleder R.; Molecular Imaging in drug discovery and development Nat. Rev. Drug Discov., 2, , 2003
Gleich B., Weizenecker J.; Tomographic Imaging using the nonlinear response of
magnetic particles Nat., 435(30), , 2005
CONFIDENTIAL 4

5. Imaging applications in drug discovery and development
Rudin M., Weissleder R.; Molecular Imaging in drug discovery and development Nat. Rev. Drug Discov., 2, , 2003

6. Multi-modality in Preclinical
Massoud & Gambhir, Genes & Development, 2003

7. Preclinical application needs
Increasing the productivity, reproducibility, and standardization of a
variety of experimental approaches such as:
Snapshot measurement on a single subject
Longitudinal studies on the single subject across multiple sessions
Group studies on multiple subjects in the same laboratory
Studies on distributed population groups that are done to substantiate the hypothesis.

8. IMALYTICS Workspace
Multi-modality Preclinical Workstation
Provides a combined view of the different facets of the drug discovery process.
Provides advanced image analysis, quantification, and visualization tools dedicated to research and discovery

9. IMALYTICS Modeling requirements
Data Mining
Project Oriented View
Each Preclinical Project will involve multiple Subjects with Series of images under each
Interoperability
High Interoperability with existing Standards
High Interoperability with existing Preclinical data
Compatibility
Extendable for Clinical Trials
Compatible with existing Clinical Apps

10. Preclinical Real-World Model
Project ID
Description
Principal Investigator
Project
1..n
1..n
Subject ID
Strain Name
Sex
Subject
Series Number
Modality
Series Description
Series
1..n
1..n
1..n
Study ID
Study Date
Study
SOP Common Module
Image Pixel Module
Image
SOP Common Module
Non Image

11. DICOM Clinical Trial Model
Patient ID
Patient Name
Patient Sex
Patient
Clinical Trial Sponsor Name
Clinical Trial Protocol Name
Clinical Trial Protocol ID
Clinical Trial Subject
1..n
1..n
Study ID
Study Date
Study
1..n
Series Number
Modality
Series Description
Series
1..n
SOP Common Module
Image Pixel Module
Image

12. Mapping Preclinical Model to DICOM
Depicts the Conceptual Model of the Preclinical domain
Data mining at Project Level would be easy 
Less Compatibility with existing clinical applications
Low Interoperability with clinical DICOM data
Patient
Project
Clinical Trial Subject
Subject
Study
Study
Series
Series
Image
Image

13. Mapping Preclinical Model to DICOM
High co-relation with DICOM Model
High Compatibility with existing Clinical Applications
High Interoperability 
Differs from the Conceptual Preclinical model
Data mining at Project level is not easy
Patient
Project
Clinical Trial Subject
Subject
Study
Study
Series
Series
Image
Image

14. Clinical Trial Subject
IMALYTICS Model
Interoperability :
Easily achievable
Compatibility :
Can be used for Clinical Trial
Clinical Apps can be easily integrated
Data Mining :
Not possible via the Model
Can be achieved via Software
Semantic Correlation :
High Correlation with DICOM
Patient
Project
Clinical Trial Subject
Subject
Study
Study
Series
Series
Image
Image

15. Project-oriented Workflow
Enables Project Oriented View with local Database
The Project Oriented view can be seamlessly used for Clinical Trials 
Project Oriented View may not be possible with DICOM Network and Media
Importing a Complete Project in one shot is not possible

16. DICOM Constraints on Preclinical
Group Studies
Multiple Subjects are a part of the same Scan
Sharing the same Study after splitting into multiple hierarchy is not possible
Orientation of individual subject can not be represented

17. DICOM Constraints on Preclinical
DICOM Type 2 attributes may not always be applicable in the Preclinical domain
Patient Birth Date
Patient Sex
Referring Physician

18. Challenges and Future Work
IMALYTICS Model vs. Preclinical model by other vendors
Non availability of Data from different vendors
Non availability of DICOM Conformance Statements for preclinical products
Future Work
Extending the IMALYTICS model for Group Studies
Applicability of the current model for
Distributed population Study
Clinical Trials
Dealing with non-image data like Histology (in-silico, in-vitro, ex-vivo)

19. Conclusions
Preclinical Imaging has emerged recently as a powerful tool that enables Clinical Research
Going forward Interoperability would be the key in Preclinical domain (especially for translational research)
Specific platforms to address Interoperability in Preclinical (IHE/Connectathon) are required