Tool Support for Cancer Lesion Tracking and Quantitative Assessment of Disease Response

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1 Tool Support for Cancer Lesion Tracking and Quantitative Assessment of Disease Response Mia Levy, MD Vanderbilt University Daniel Rubin, MD Stanford University

2 Tumor Response Assessment Objective criteria for measuring response to treatment are critical to cancer research and practice

3 Image Based Response Assessment Baseline Follow-up

4 Current Clinical Workflow Oncologist Orders Imaging Study Images Acquired Radiologist Reviews Images

5 Image Mark up

6 Radiologist Reviews Images Markup Regions of Interest (ROI) Textual Report Summary of Findings Lesion Location Anatomic Description Image Number Lesion Dimension(s) Impression of disease status

7 Oncologist Response Assessment & Oncologist Reviews Report & Images Tries to locate the lesions the radiologist referred to in report Qualitative comparison of lesions across studies Qualitative assessment of response Aids treatment decision making

8 Clinical Trial Workflow Goal: Consistent Quantitative Assessment of response across clinical trial patients Method: Response Assessment Protocol Modality Response Criteria

9 Oncologist Response Assessment & Oncologist Reviews Report & Images Tries to locate the lesions the radiologist referred to in report Quantitative measurement of cancer lesions Lesion Flow sheet Quantitative Tumor Burden Response

10 Lesion Flow Sheet

11 Data Acquisition Problem Current methods for identifying and tracking cancer lesions are inadequate for consistent application of quantitative methods to assess response to treatment

12 Analysis Clinical Imaging Reporting Number of CT Scans Baseline (13) Follow up (29) Total (42) Sufficient to Calculate RECIST Sum of Longest Diameters 54% 14% 26% Baseline (55) Follow up (112) Report Identified Lesion 71% 38% Image Mark up Lesion 73% 70% Longest Diameter Reported 55% 28% Longest Diameter Marked 50% 26% Levy MA, Rubin DL. Tool support to enable evaluation of the clinical response to treatment. AMIA Annu Symp Proc. 2008:

13 Operational Challenges Multiple Radiologists reading baseline & follow up cases Distributed task but radiologists do not have access to lesion flow sheet Complex set of rules lack education

14 Informatics Challenges Image Mark up Stored Locally Lack semantic data Lesion identification and tracking ambiguous

15 Solution: Image Annotation Tool

16 Image Annotation Tool OsiriX DICOM Viewer ipad image Physician Annotation Device (ipad) Plug in to OsiriX image viewing application User interface for image annotation Implements the cabig Annotation Image Markup (AIM) standard DICOM PACS Annotation Database RadLex Ontology Rubin DL, Rodriguez C, Shah P, Beaulieu C. ipad: Semantic Annotation and Markup of Radiological Images. AMIA 2008 Proceedings.

17 Image Annotation Tool AIM schema OsiriX DICOM Viewer ipad Annotation Image Markup (AIM) Information model and data structure for storing the key semantic lesion information Metadata pertinent to features of disease, such as lesion identification, location, size measurements, and method of measurement XML DICOM PACS Annotation Database RadLex Ontology Rubin DL, Rodriguez C, Shah P, Beaulieu C. ipad: Semantic Annotation and Markup of Radiological Images. AMIA 2008 Proceedings.

18 ipad Enhancements: Cancer Lesion Identification & RECIST classification Enable user to assign unique identifier to cancer lesions across studies over time Semantic annotation of RECIST specific terms Baseline Target Lesion Follow up Non Target Lesion

19 Preliminary System Evaluation Colorectal Trial Lymphoma Trial Number of Subjects Number of Imaging Studies Baseline Follow up Number of Target Lesions Expected Number Target Lesions Annotated in Follow up Study Actual Number of Target Lesions Annotated in Follow up Study Total Percentage Target Lesions Annotated in Follow up 100% 92% 93%

20 ipad Enhancement: Lesion Tracking

21 Hanging Protocol Lesion Review

22 ipad Enhancement: Quantitative Tumor Burden Calculation & Visualization

23 Planned Evaluation: ipad Enhancements Retrospective Lesion Annotation for Closed Metastatic Breast Cancer Trial Evaluation of change in target lesion measurement from prior reports & mark up Prospective Lesion Annotation for Ongoing Metastatic Breast Cancer Clinical Trial Evaluation of change in prospective lesion reporting

24 Acknowledgements ipad Developers Cesear Rodriguez Chris Baldassano Stanford Radiology Lewis Shin Stanford Oncology George Fisher Josh Brody Vanderbilt Oncology Ingrid Mayer Carlos Arteaga Funding SIIM Research Grant

25 Thank You Questions?

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