DICOM – A Preclinical Perspective

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. Enabled by Pre-Clinical Workspace Statistically Significant Results Exploratory or Hypothesis driven Transition to ...

4. Preclinical Imaging “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 fundamentalbiological processes in a new light; Genes Dev., 17, 545-580, 2003 Rudin M., Weissleder R.;Molecular Imaging in drug discovery and developmentNat. Rev. Drug Discov., 2, 123-131, 2003 Gleich B., Weizenecker J.;Tomographic Imaging using the nonlinear response of magnetic particlesNat., 435(30), 1214-1217, 2005 CONFIDENTIAL 4

5. Imaging applications in drug discovery and development Rudin M., Weissleder R.;Molecular Imaging in drug discovery and developmentNat. Rev. Drug Discov., 2, 123-131, 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. Series SOP Common Module SOP Common Module Image Pixel Module Non Image Series Number Modality Series Description Image Subject ID Strain Name Sex Project Project ID Description Principal Investigator Subject Study ID Study Date Study Preclinical Real-World Model 1..n 1..n 1..n 1..n 1..n

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

12. Project Clinical Trial Subject Subject Study Study Series Series Image Image Mapping Preclinical Model to DICOM Patient

13. Project Clinical Trial Subject Subject Study Study Series Series Image Image Mapping Preclinical Model to DICOM Patient

14. Project Clinical Trial Subject Subject Study Study Series Series Image Image IMALYTICS Model Patient 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

15. Project-oriented Workflow

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 • Challenges • 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