The Quantitative Imaging Network QIN Introductory Remarks Robert J. Nordstrom Larry Clarke Pushpa Tandon Yantian Zhang Huiming Zhang Lori Henderson March 27 – 28, 2014 Lalitha Shankar Keyvan Farahani George Redmond James Deye Jacek Capala John Freymann Justin Kirby

2014

QIN Program Status 17 teams are active –2 additional teams are just starting Medical College of Wisconsin, Schmainda UCLA, McNitt-Gray –2 teams have passed SPL review –2 teams will enter under Canadian funding –27 applications waiting for review in two rounds New program announcement: PAR

The new program announcement

Goals for PAR Enhance the value of quantitative imaging in clinical trials to predict or measure response to therapy. –Develop, optimize & validate quantitative imaging methods and software tools –Address the challenge of integrating existing or new methods and tools into multi-site clinical trials.

Clinical consensus Data archiving Phantoms Consensus Two research strategies including research infrastructure Informatics support Variance & bias reduction Clinical trial design Database Test - retest Enrollment issues Protocol development Clinical trial qualification Analysis Metrology tools Research Infrastructure

PAR QIN U01 Details Renewal applications are permitted –Single Site or multi-site trials (data collections) –Domestic and foreign applications encouraged –Industry participation encouraged –Budget remains capped at $500k direct costs (5 years) –Itemized budget for WG’s, data and tool sharing Research Strategy: Different Emphasis –Need not to be strong in all areas QI methods Selection of clinical trials Imaging Modalities Research Infrastructure

The Current QIN Teams

The Overview Perspective of QIN Program staff must look at this effort from a number of different perspectives: –What can QIN do for its customers? –How is QIN organized to deliver this? –What will the clinical research community gain? –How can program staff help?

What QIN processes are needed? Establish methods for open communication strategies and balanced activities among Working Groups, the Executive Committee, and external groups. Active participation on Working Group, Coordinating Committee, and Executive Committee conference calls, keeping the missions of each group in focus to avoid mission creep. Guide group teaming to leverage collective intellectual capital and reduce the formation of silos where they might occur. Strive for open science solutions to encourage sharing of data and algorithms. What will QIN do for its customers? (oncologists, pharma) Provide technically robust and clinically validated quantitative solutions for anatomical and functional imaging to predict and/or measure response of cancer to therapy. Offer reliable, easy to use adaptable, scalable, and upgradable quantitative imaging tools to promote adaptive therapy. Interact with industry to establish pathways leading to commercialization of quantitative imaging tools. What will shareholders see as a result? (Cancer Centers, clinical trial groups) Relevant, clinically validated quantitative imaging tools offered to the oncology community in a timely and cost-effective manner. Standardized imaging methods and terminology that will provide accurate quantitative measures of therapy response and reliable outcome prediction. How can program staff support QIN activities? Continue to bring new teams into the QIN program through application justifications to the SPL. Add associate members to the QIN. Continue to hold meaningful QIN Program Director meetings on a timely basis. Develop meaningful evaluation criteria to measure the effectiveness of the Working Groups on a regular basis and be prepared to make changes in organization and/or direction. Encourage dissemination of tools and data through peer-reviewed QIN publications, TCIA, and through clinical trial cooperative groups. Identify and catalyze areas of technical collaboration (data sharing, algorithm validation, etc.) among QIN members to accelerate achievement of program goals. Facilitate outreach to industry and regulatory bodies as well as professional societies. Organize and conduct meaningful meetings of the QIN members. Encourage leveraging of limited resources to achieve program goals. All QIN Elements Coordinating CommitteeExecutive Committee Program Staff

Working Group Activities We are here now. These are next year’s tasks What comes next?

Coordinating Committee Chairs & co-chairs of the working groups. Must elect a chair for this group. Meet by teleconference every-other month. –2 nd Wednesday of month, 2 PM EDT –Next meeting, May 14, 2014 Have next 2-year working group chart finalized.

Individual Team Goals Find areas of cooperation. Plan events such as challenges. Check progress.

Next Year’s Report Focus on working groups –Challenge results –Tool cataloging & sharing Contributions from each technical team Printed for distribution Posted on an appropriate web site

Expected Outcomes from the Meeting Revised Working Group plans for the coming year (2014). Draft of Working Group plans for Leadership initiation in all groups. Associate membership launched. International relationships created. Channels for QIN outreach developed.

NCI Program/SPL Review of Applications Clinical relevance of proposed trial/drug Rationale: Single site or multi-site clinical trial Clinical rational: Scientific Innovation Network wide : Consensus publications Leadership ( EC, CC, WG’s) Participation ( EC, CC, WG’s) Delivery of a specific QI methodology across one or ideally across several clinical sites

QIN Outreach Scientific Societies –RSNA, ISMRM, SNM, AAPM, MICIA, SPIE –Grand Challenges for QI methods/analysis Industry –Network wide participation International –Canada, UK, India, China, EU..) –Sharing of research resources –Development of an international consensus –Shared targeted collaboration with industry

QIN Hub & Spoke Models Program Contact: Yantian Zhang (CIP) PAR : Academic Industry Partnerships –QIN currently has 6 AIP linked to QIN –Clinical and pre clinical or co clinical imaging – Informatics Technology for Cancer Research –( R01, U01, U24) –QIN currently has one U24 (SLICER) – NIH BIG DATA Initiatives ( next slides) –

BD2K New Funding Opportunities PA : Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R43/R44) htmlhttp://grants.nih.gov/grants/guide/pa-files/PA html PA ): Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R01) PA : Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science (R01) PA : Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R41/R42) html html

BD2K New Funding Opportunities RFA-HL : Development of an NIH BD2K Data Discovery Index Coordination Consortium(U24) RFA-HG : Development of Software and Analysis Methods for Biomedical Big Data in Targeted Areas of High Need (U01)

Other Exploratory Opportunities Imaging Phenotype-Genomics Correlations –Workshop (June 2013), White Paper (2014) –QIN can serve the role as a technical resource Preclinical and Co Clinical Drug Trials –Collaboration with Mouse Models MMHCC –Interest in development of QIN standards –NCI CBIIT contract ( Informatics support) –NCI CBIIT Workshop ( 2013), and planned ( 2014) NCI Outreach: WMIC South Korea (2014): –Promote standards for mouse models and QI methods –Preclinical and Co-Clinical Trials