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The Quantitative Imaging Network QIN

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

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The Quantitative Imaging Network QIN

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

  2. Welcome to the QIN 2014

  3. 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-14-116

  4. The new program announcement

  5. Goals for PAR-14-116 • 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.

  6. Two research strategies including research infrastructure Enrollment issues Clinical trial design Clinical trial qualification Phantoms Inclusion in multisite trials Analysis Clinical acceptance Informatics support Harmonization across platforms Test - retest Validation from multisite trials Tool optimization Analysis Clinical consensus Tool validation Protocol development Tool development Variance & bias reduction Data archiving Consensus Modifying clinical trials (Not part of QIN) Metrology tools Database Integration into multisite clinical trials. Validated quantitative imaging methods. Research Infrastructure

  7. PAR-14-116 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

  8. The Current QIN Teams

  9. The Current QIN Teams

  10. 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?

  11. Coordinating Committee Executive Committee All QIN Elements 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 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. How can program staff support QIN activities? What will shareholders see as a result? (Cancer Centers, clinical trial groups) • 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. • 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. Program Staff

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

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

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

  15. 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

  16. Expected Outcomes from the Meeting • Revised Working Group plans for the coming year (2014). • Draft of Working Group plans for 2015. • Leadership initiation in all groups. • Associate membership launched. • International relationships created. • Channels for QIN outreach developed.

  17. 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

  18. 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

  19. QIN Hub & Spoke ModelsProgram Contact: Yantian Zhang (CIP) • PAR 13 169: Academic Industry Partnerships • QIN currently has 6 AIP linked to QIN • Clinical and pre clinical or co clinical imaging • http://grants.nih.gov/grants/guide/pa-files/PAR-13-169.html • Informatics Technology for Cancer Research • ( R01, U01, U24) • QIN currently has one U24 (SLICER) • http://itcr.nci.nih.gov/ • NIH BIG DATA Initiatives ( next slides)

  20. BD2K New Funding Opportunities PA-14-154: Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R43/R44) http://grants.nih.gov/grants/guide/pa-files/PA-14-154.html PA-14-155): Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R01) http://grants.nih.gov/grants/guide/pa-files/PA-14-155.html PA-14-156: Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science (R01) http://grants.nih.gov/grants/guide/pa-files/PA-14-156.htmlPA-14-157: Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R41/R42) http://grants.nih.gov/grants/guide/pa-files/PA-14-157.html

  21. BD2K New Funding Opportunities RFA-HL-14-031: Development of an NIH BD2K Data Discovery Index Coordination Consortium(U24) http://grants.nih.gov/grants/guide/rfa-files/RFA-HL-14-031.html RFA-HG-14-020: Development of Software and Analysis Methods for Biomedical Big Data in Targeted Areas of High Need (U01) http://grants.nih.gov/grants/guide/rfa-files/RFA-HG-14-020.html

  22. 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

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