Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma

Abstract

Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor’s heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical.

Imaging-Based Biomarkers Predict Programmed Death-Ligand 1 and Survival Outcomes in Advanced NSCLC Treated With Nivolumab and Pembrolizumab: A Multi-Institutional Study

“… 8 , 9 Radiomics-based techniques have a number of benefits, including the fact that they are noninvasive and the features can be derived from routine medical images. 10 , 11 These make them ideal for translating to clinical practice as the method does not involve invasive procedures to predict or monitor a patient's response to various therapeutic interventions. Studies in the literature have found that radiomics can be used to build diagnostic or predictive biomarkers in a variety of malignancies, including advanced solid tumors, melanoma, and other types of NSCLC.…”