Editorial: Radiomics Advances Precision Medicine

Abstract

Radiomics applies quantitative methods to medical images and derives phenotypic information that might not be obvious during traditional visual inspection. The potential for radiomics to identify previously unrecognizable imaging biomarkers for tumor genotype and pathology has sparked considerable interest in exploring the clinical potential of radiomics (1). Since its initial presentation in 2012 (2), radiomics has been widely applied in oncology (Wu et al.) and has achieved robust performance in assessment of genomic features (Shen et al.) (3); tumor subtypes (4, 5); nodal metastases of various cancers such as colorectal cancer, gastric cancer, breast cancer (6-8) and occult distant metastases (9). In addition, radiomics has been used in evaluation of treatment response (10, 11) and outcome prediction The recent rapid development of artificial intelligence and its application in mining medical "big data" have further advanced the field of radiomics in both oncological research and clinical practice.

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