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J Am Coll Radiol. 2018 Mar;15(3 Pt B):538-542. doi: 10.1016/j.jacr.2017.12.008. Epub 2018 Feb 1.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 1: From Methodology to Clinical Implementation.

Author information

1
Institute of Computational Health Sciences, UCSF, San Francisco, California. Electronic address: faiq.shaikh@hotmail.com.
2
Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California.
3
UPMC Enterprises, Pittsburgh, Pennsylvania.
4
Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York.
5
Department of Radiology, Temple University, Philadelphia, Pennsylvania.
6
Carnegie Mellon University, Pittsburgh, Pennsylvania.
7
Department of Radiology, Stanford University, Palo Alto, California.
8
Department of Radiology, Division of Nuclear Medicine, University of Miami, Miami, Florida.
9
School of Social Welfare, Stony Brook University, New York, New York.
10
Institute of Computational Health Sciences, UCSF, San Francisco, California.

Abstract

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancements in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration have ushered us into the era of radiomics, which has tremendous potential in clinical decision support as well as drug discovery. There are important issues to consider to incorporate radiomics as a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that to enterprise development (Part 2).

KEYWORDS:

Radiomics; enterprise; medicine; precision; radiology; translational

PMID:
29366600
DOI:
10.1016/j.jacr.2017.12.008
[Indexed for MEDLINE]

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