Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

Elaine Limkin 1 Roger Sun 1 Laurent Dercle 2 Evangelia Zacharaki 3, 4 Charlotte Robert 1 Sylvain Reuzé 1 Antoine Schernberg 1 Nikos Paragios 5 Eric Deutsch 1, 6 Charles Ferté 7
1 Département de radiothérapie [Gustave Roussy]
2 IGR - Institut Gustave Roussy
3 CVC - Center for Visual Computing
4 GALEN - Organ Modeling through Extraction, Representation and Understanding of Medical Image Content
Inria Saclay - Ile de France, Ecole Centrale Paris
5 MAS - Mathématiques Appliquées aux Systèmes - EA 4037
6 UMR 1030 - Unité de radiothérapie moléculaire
7 CCF - Département de cancérologie cervico-faciale [Gustave Roussy]
Abstract : Medical image processing and analysis (also known as Radiomics) is a rapidly growing discipline that maps digital medical images into quantitative data, with the end goal of generating imaging biomarkers as decision support tools for clinical practice. The use of imaging data from routine clinical work-up has tremendous potential in improving cancer care by heightening understanding of tumor biology and aiding in the implementation of precision medicine. As a noninvasive method of assessing the tumor and its microenvironment in their entirety, radiomics allows the evaluation and monitoring of tumor characteristics such as temporal and spatial heterogeneity. One can observe a rapid increase in the number of computational medical imaging publications - milestones that have highlighted the utility of imaging biomarkers in oncology. Nevertheless, the use of radiomics as clinical biomarkers still necessitates amelioration and standardization in order to achieve routine clinical adoption. This Review addresses the critical issues to ensure the proper development of radiomics as a biomarker and facilitate its implementation in clinical practice.
Keywords : precision medicine quantitative imaging radiomics computational medical imaging tumor biology
Type de document :
Article dans une revue
Annals of Oncology, Oxford University Press (OUP), 2017, 28 (6), pp.1191 - 1206. 〈10.1093/annonc/mdx034〉
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Elaine Limkin, Roger Sun, Laurent Dercle, Evangelia Zacharaki, Charlotte Robert, et al.. Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology. Annals of Oncology, Oxford University Press (OUP), 2017, 28 (6), pp.1191 - 1206. 〈10.1093/annonc/mdx034〉. 〈hal-01648559〉

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