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Last Updated: 02/06/18
Quantitative Imaging Network (QIN)

About the Quantitative Imaging Network (QIN)

Teams

Research teams enter the Quantitative Imaging Network through the NIH peer review process in which a research application is submitted in accordance with a specific program announcement (for the QIN, the announcements are PAR-18-248 and PAR-18-249), and are reviewed in special study section. Meritorious applications are considered for funding, and are given support if funds are available. Once in the network, each team is responsible for making steady progress on the research topic presented in its application. In addition, team members are obligated to serve on network-wide activities such as the Executive Committee and/or one or more of the current working groups. These activities are presented in the Network structure section.

The map shows the teams that have been a part of the QIN. A total of 34 research teams have participated in the QIN thus far since 2008. Because some teams have completed their research tenure with the network, the present number of active participants is now 22 supported by NCI. Each of these teams is listed below with links to their research abstracts and contact information.

In addition to the research team supported by the NCI, the QIN also has two teams from Canada fully supported by the Canadian Government. These teams participate in all functions of the network and vote on issues before the Executive Committee. They are included in the list of QIN participants.

Several international teams have joined the QIN through Associate Membership admission. These associate members have greatly enhanced the capabilities of the network by supplying clinical images, analysis tools and methods, and expertise to advance quantitative imaging methods in clinical trials. A current list of associate members is provided below.

QIN Member List

Columbia University
Lawrence H. Schwartz (lschwartz@columbia.edu)
Quantitative Volume and Density Response Assessment: Sarcoma and HCC as a Model

Dana-Farber Cancer Institute
Hugo Aerts (hugo_aerts@dfci.harvard.edu)
Genotype and Imaging Phenotype Biomarkers in Lung Cancer

ECOG-ACRIN
Mitchell D. Schnall (mitchell.schnall@uphs.upenn.edu)
ECOG-ACRIN-Based QIN Resource for Advancing Quantitative Cancer Imaging in Clinical Trials

Emory University
Hyunsuk Shim (hshim@emory.edu)
Quantitative Magnetic Resonance Spectroscopic Imaging to Predict Early Response to SAHA Therapy in GBM Management

Medical College of Wisconsin
Kathleen Schmainda (kathleen@mcw.edu)
Quantitative (Perfusion & Diffusion) MRI Biomarkers to Measure Glioma Response

Memorial Sloan Kettering Cancer Center
Amita Dave (davea@mskcc.org)
Quantitative imaging tools to derive DW-MRI oncological biomarkers

Moffitt Cancer Center & Research Institute
Robert Gillies (robert.gillies@moffitt.org)
Radiomics of NSCLC

Stanford University (team#1)
Daniel Rubin (dlrubin@stanford.edu)
Qualification and Deployment of Imaging Biomarkers of Cancer Treatment Response

Stanford University (team#2)
Sandy Napel (snapel@stanford.edu)
Qualification and Deployment of Imaging Biomarkers of Cancer Treatment Response

University of Arkansas Medical Sciences
Fred Prior (FWPrior@uams.edu)
Resources for Development and Validation of Radiomic Analysis & Adaptive Therapy

University of British Columbia
Francois Benard (fbenard@bccrc.ca)
Integrating Quantitative Imaging Methods and Genomic Biomarkers to Assess the Therapeutic Response to Cancers

University of California — Los Angeles
Michael McNitt-Gray (mmcnittgray@mednet.ucla.edu)
Quantitative CT Imaging for Response Assessment When Using Dose Reduction Methods

University of Chicago
Maryellen Giger (m-giger@uchicago.edu)
Quantitative Image Analysis for Assessing Response to Breast Cancer Therapy

University Health Network
David Jaffray (david.jaffray@rmp.uhn.on.ca)
Image-based Quantitative Assessment of tumor Hypoxia

University of Iowa
John M. Buatti (john-buatti@uiowa.edu)
Quantitative Imaging to Assess Response in Cancer Therapy Trials

University of Michigan (team#1)
Brian Ross (bdross@umich.edu)
Advancing Quantification of Diffusion MRI for Oncologic Imaging

University of Michigan (team#2)
Lubomir Hadjiyski (lhadjiysk@umich.edu)
Biomarkers for Staging and Treatment Response Monitoring of Bladder Cancer

University of Michigan (team#3)
Yue Cao (yuecao@med.umich.edu)
Quantitative MRI Models of Head & Neck Cancers for Physiological Adaption of RT

University of Texas SW Medical Center
Ananth Madhuranthakam (Ananth.Madhuranthakam@UTSouthwestern.edu)
Quantitative Non-Contrast Perfusion using Arterial Spin Labeling for
Assessment of Cancer Therapy Response

University of Washington
Paul Kinahan (kinahan@u.washington.edu)
Advanced PET/CT Imaging for Improving Clinical Trials

Vanderbilt University
Richard Abramson (richard.abramson@vanderbilt.edu) &
Thomas E. Yankeelov (thomas.yankeelov@utexas.edu)
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant Therapy

QIN Emeritus Members

Brigham & Women’s Hospital
Fiona Fennessy, MB, PhD (ffennessy@partners.org)
Quantitative MRI of prostate cancer as a biomarker and guide for treatment

Johns Hopkins University and Washington University in Saint Louis
Eric C. Frey, Ph.D., Michael A. Jacobs, Ph.D., Richard L. Wahl, M.D (ecfrey@gmail.com)
Multi-Modality Quantitative Imaging for Evaluation of Response to Cancer Therapy

Mayo Clinic
Bradley Erickson (bje@mayo.edu)
Objective Decision Support Environment for Clinical Trials

Massachusetts General Hospital
Jayashree Kalpathy-Cramer (kalpathy@nmr.mgh.harvard.edu)
Quantitative MRI of Glioblastoma Response

Mount Sinai
Bachir Taouli (Bachir.taouli@mountsinai.org)
Evaluation of HCC Response to Systemic Therapy with Quantitative MRI

Oregon Health & Science University
Wei Huang (huangwe@ohsu.edu)
Shutter-Speed Model DCE-MRI for Assessment of Response to Cancer Therapy

University of California at San Francisco
Nola Hylton (nola.hylton@ucsf.edu)
Quantitative Imaging for Assessing Breast Cancer Response to Treatment

University of Pittsburgh
James Mountz (mountzjm@upmc.edu
Quantitative Biomarker Imaging for Early Therapy Response Assessment in Cancer

Associate Member List

All India Institute of Medical Sciences, New Delhi, India
N.R Jagannathan: jagan1954@hotmail.com

Barrow Neurological Institute
Chad Quarles: chad.quarles@barrowneuro.org

Cancer Center (Oncology Clinic), City Clinic, Sofia, Bulgaria
Veselka Stoynova: Veselka.STOYNOVA@cityclinic.bg

Case Western Reserve University
Anant Madabhushi: anant.madabhushi@case.edu

Center of Functionally Integrative Neuroscience,
Aarhus University, Aarhus University Hospital, Denmark
Kim Mouridsen: KIM@CFIN.AU.DK

Charité - University Medicine Berlin, Berlin, Germany
Winfried Brenner: Winfried.Brenner@charite.de

City Clinic Sofia, Bulgaria
Lachezar D. Penev: lachezar.penev@cityclinic.bg

Sahlgrenska University Hospital — Univ. of Gothenburg, Sweden
Rolf Heckemann: rolf.heckemann@medtechwest.se

Tata Memorial Hospital, Mumbai, India
Abhishek Mahajan: drabhishek.mahajan@yahoo.in;

Tata Memorial Cancer Center, Mumbai, India
Meenakshi Thakur: thakurmh@yahoo.co.in

Tokuda Hospital, City Clinic, Sofia, Bulgaria
Galina Kirova Nedyalkova: gal.kirova@gmail.com

University College at Cork, Ireland
Finbarr O’Sullivan: f.osullivan@ucc.ie

University of Pittsburgh
James Mountz: mountzjm@upmc.edu

University School of Medicine, South Korea
Kyung Soo Lee: kyungs.lee@samsung.com