Work

Radiogenomics: bridging imaging and genomics

Year: 2019

Type: article

Abstract: From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic profile, a field commonly referred to as "radiogenomics." In this review, a general outline of radiogenomic literature concerning prominent mutations across different tumor sites will be provided. The field of radiogenomics originates from image processing techniques developed decades ago; however, many technical and clinical challenges still need to be addressed. Nevertheless, increasingly accurate and robust radiogenomic models are being presented and the future appears to be bright.

Source: Abdominal Radiology

DOI: 10.1007/s00261-019-02028-w

Authors: Zuhir Bodalal, Stefano Trebeschi, Thi Dan Linh Nguyen-Kim, Winnie Schats, Regina Beets-Tan

Institutions: The Netherlands Cancer Institute, Maastricht University, University of Zurich, University Hospital Zurich

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,140