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

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

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 ...

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, 545-580, 2003 Rudin M., Weissleder R.; Molecular Imaging in drug discovery and development Nat. Rev. Drug Discov., 2, 123-131, 2003 Gleich B., Weizenecker J.; Tomographic Imaging using the nonlinear response of magnetic particles Nat., 435(30), 1214-1217, 2005 CONFIDENTIAL 4

Imaging applications in drug discovery and development Rudin M., Weissleder R.; Molecular Imaging in drug discovery and development Nat. Rev. Drug Discov., 2, 123-131, 2003

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

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.

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

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

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

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

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

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

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

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

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

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

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)

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