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