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Transl Oncol. 2014 Oct 24;7(5):556-69. doi: 10.1016/j.tranon.2014.07.007. eCollection 2014 Oct.

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures.

Author information

1
MD Anderson Cancer Center, 1400 Pressler Unit: 1482, Houston, TX 77030.
2
Computation Institute, University of Chicago, 5735 S. Ellis Avenue, Chicago, IL 60637.
3
Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612.
4
University of Chicago, 5841 South Maryland Avenue, Chicago, IL 60637.
5
Emory University School of Medicine, 36 Eagle row, 5th Floor South, Atlanta, GA 30322.
6
University of Pittsburgh Medical Center, Department of Radiology, 200 Lothrop St., Pittsburgh, PA 15213.
7
NYU Langone Medical Center, 550 1st Ave, New York, NY 10016 USA.
8
Case Western Reserve University, 2071 Martin Luther King Jr. Drive, Cleveland, OH 44106-7207.
9
Georgetown University Medical Center, Suite 2115 Wisconsin Ave, NW, Washington, DC 20057.
10
Department of Radiology, Stanford University, Stanford, CA 94305.
11
Department of Biomedical Informatics, Stony Brook University, 100 Nicolls Road, Stony Brook, NY 11794.
12
Hunter Holmes McGuire VA Medical Center, 1201 Broad Rock Boulevard, Richmond, VA 23249.
13
MD Anderson Cancer Center, 1515 Holcombe Blvd, #1350, Houston, TX 77030.

Abstract

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

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