1. DICOM INTERNATIONAL CONFERENCE & SEMINAR Oct 9-11, 2010 Rio de Janeiro, Brazil Collection and Management of Image Data for Clinical Trials Lawrence Tarbox Washington University in St. Louis Colin Rhodes a, Steve Moore b, Ken Clark b, David Maffitt b, John Perry c, Toni Handzel a, Fred Prior b a VirtualScopics Inc., Rochester, NY 14625 USA b Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO c Hampshire, IL 60140 USA

2. Warning! Small Type Ahead! Do not strain to read! I will talk through the diagrams. Slides will be available for download to see the details

3. Imaging Biomarkers in Clinical Trials Quantitative image analysis requires digital image data, and often non-standard (i.e. non-clinical) image acquisition parameters. All of this digital data must be acquired, managed, processed, and ultimately reduced to meaningful scientific evidence presented to a sponsor. To access sufficiently large participant populations, clinical trials are usually multi-center but increasingly they are also international. Research imaging protocols frequently generate more data than clinical studies.

5. Efficiency and Quality Are Critical 55% of Imaging Studies were received within 5 days, 86% received within 20 days. Anecdotal Industry information points to 5%-50% image fallout rate heavily dependant on acquisition modality. Time from scan date to receipt at the core lab Data Courtesy of Jeff Markin

6. NCI 1R41CA132790-01 (PI: Rhodes, Prior)

7. Using an Electronic Imaging Trial Management System Transmission Delays and Data Loss are Reduced B. Vendt, R. McKinstry, W. Ball, M. Kraut, F. Prior, and M. DeBaun, “Silent Cerebral Infarct Transfusion (SIT) Trial Imaging Core: Application of Novel Imaging Information Technology for Rapid and Central Review of MRI of the Brain,” Journal of Digital Imaging, vol. 22, pp. 326-343, 2009. Time from scan date to receipt at the core lab (68.7%) are received within 5 days; 95% within 20 Days; Data Drop-out Rate < 5%.

8. Regulatory Compliance Data submissions to the FDA in support of pharmaceutical trials require documentation of all access to the data from its time of creation to the point of submission (Provenance Tracking, Digital Signatures). –Any modification of the data (including image processing) must be documented and electronically signed. Image visualization systems (PACS) are FDA regulated medical devices and therefore subject to strict regulations on software development and validation. Software that manages data collected during clinical trials is also subject to FDA regulation (GMP). Open source software is permitted but only after carefully controlled validation and verification.

9. Regulatory Compliance Software Process: Code of Federal Regulations, Title 21 parts 820, 2009. Available from: http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSe arch.cfm?CFRPart=820&showFR=1 http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSe arch.cfm?CFRPart=820&showFR=1 Provenance Tracking: Code of Federal Regulations, Title 21, part 11, 2009. Available from: http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfCFR/CFRS earch.cfm?CFRPart=11&showFR=1 http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfCFR/CFRS earch.cfm?CFRPart=11&showFR=1 Software can NOT comply with these regulations. The regulations relate to processes that may involve software, not the software itself.

10. Three Main Components Located at each study site –Clinical Studies Anonymization Workstation (CSAW) Located at the Contract Research Organization (CRO) –Image Check-in and Quality Assurance Management System (ICMS) –Information Repository Management System (IRMS)

12. CSAW Implementation Principally based on the Clinical Trials Processor (CTP), part of RSNA MIRC –Configurable pipeline for receiving, de-identifying, checking, processing, and transmitting data Creates IHE TCE Manifest Digital Signatures as integrity checks Includes additional web-based management components –Out-of-band confirmation of transmission –Collection of data missing from the DICOM objects

15. Check-in and Quality Check Check received images against manifest Automated check for required Attributes Quarantine of images that do not pass checks Optional manual check for image quality Release to IRMS for further processing

17. Imaging Trial Data Analysis Reader studies: –Multiple blind reads with or without consensus; –Radiologist generated measurements; –Electronic Case Report Forms linked to the imaging study should facilitate workflow and reduce transcription error. Quantitative analysis: –Semi-automated - human guided analysis software; –Automated imaging pipelines. Image management and distribution are key to all forms of analysis. Workflow management and optimization are increasingly important as data volumes grow.

19. : caBIG-IMG-xx-01-05112007 (Azar: PI) caBIG-IMG-82-01-04102008 (Schwanke: PI) IRMS Prototype

20. Validation A feasibility study is underway linking one imaging site (Washington University) and one CRO imaging core lab (VirtualScopics). 1)the elapsed time from image capture to when the images are measured or reviewed at the central processing center; and 2)the number of imaging protocol and FDA compliance errors found at each step in the workflow from image capture through analysis at the central processing center Audit of Development Process documentation and controls. Audit of Trial Processes and Procedures for Part 11 compliance based on electronic Provenance tracking.

21. In Summary Quantitative digital imaging is playing an increasingly important role in clinical trials. Collecting, managing and analyzing images in clinical trials require specialized software systems. Management development processes must meet FDA quality requirements and the software itself must support Part 11 compliant processes. Once such management systems are deployed, sponsors have the opportunity for improved trial monitoring and information access.

22. Acknowledgements This project funded in part by the National Institutes of Health through an R41 SBIR grant CA132790-01A1 The CTP project is funded through RSNA The XIP and AVT projects are partially funded through numerous subcontracts funded by National Cancer Institute