Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network

Keyvan Farahani; Jayashree Kalpathy-Cramer; Thomas L Chenevert; Daniel L Rubin; John J Sunderland; Robert J Nordstrom; John Buatti; Nola Hylton

doi:10.18383/j.tom.2016.00265

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Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network

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Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network

Keyvan Farahani, Jayashree Kalpathy-Cramer, Thomas L Chenevert, Daniel L Rubin, John J Sunderland, Robert J Nordstrom, John Buatti and Nola Hylton

Tomography (Ann Arbor), Vol.2(4), pp.242-249

12/2016

DOI: 10.18383/j.tom.2016.00265

PMID: 28798963

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Abstract

The Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI) conducts research in development and validation of imaging tools and methods for predicting and evaluating clinical response to cancer therapy. Members of the network are involved in examining various imaging and image assessment parameters through network-wide cooperative projects. To more effectively use the cooperative power of the network in conducting computational challenges in benchmarking of tools and methods and collaborative projects in analytical assessment of imaging technologies, the QIN Challenge Task Force has developed policies and procedures to enhance the value of these activities by developing guidelines and leveraging NCI resources to help their administration and manage dissemination of results. Challenges and Collaborative Projects (CCPs) are further divided into technical and clinical CCPs. As the first NCI network to engage in CCPs, we anticipate a variety of CCPs to be conducted by QIN teams in the coming years. These will be aimed to benchmark advanced software tools for clinical decision support, explore new imaging biomarkers for therapeutic assessment, and establish consensus on a range of methods and protocols in support of the use of quantitative imaging to predict and assess response to cancer therapy.

quantitative imaging

cancer therapy

challenge

crowdsourcing

collaborative project

Details

Title: Subtitle: Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network
Creators: Keyvan Farahani - Cancer Imaging Program, National Cancer Institute, Bethesda, Maryland
Jayashree Kalpathy-Cramer - Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
Thomas L Chenevert - Department of Radiology, University of Michigan, Ann Arbor, Michigan
Daniel L Rubin - Department of Radiology, Biomedical Data Science, and Medicine (Biomedical Informatics Research), Stanford University, Palo Alto, California
John J Sunderland - Department of Radiology, University of Iowa, Iowa City, Iowa
Robert J Nordstrom - Cancer Imaging Program, National Cancer Institute, Bethesda, Maryland
John Buatti - Department of Radiation Oncology, University of Iowa, Iowa City, Iowa; and
Nola Hylton - Department of Radiology, University of California San Francisco, San Francisco, California
Resource Type: Journal article
Publication Details: Tomography (Ann Arbor), Vol.2(4), pp.242-249
DOI: 10.18383/j.tom.2016.00265
PMID: 28798963
NLM abbreviation: Tomography
ISSN: 2379-1381
eISSN: 2379-139X
Publisher: Grapho Publications, LLC; Ann Abor, Michigan
Language: English
Date published: 12/2016
Academic Unit: Radiology; Physics and Astronomy; Radiation Oncology; Neurosurgery; Otolaryngology
Record Identifier: 9984047768602771

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