Application of Radiomics in Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer: Strategies and Challenges

Abstract

Neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision is the standard treatment for locally advanced rectal cancer (LARC). A noninvasive preoperative prediction method should greatly assist in the evaluation of response to nCRT and for the development of a personalized strategy for patients with LARC. Assessment of nCRT relies on imaging and radiomics can extract valuable quantitative data from medical images. In this review, we examined the status of radiomic application for assessing response to nCRT in patients with LARC and indicated a potential direction for future research.

Radiomics features of computed tomography and magnetic resonance imaging for predicting response to transarterial chemoembolization in hepatocellular carcinoma: a meta-analysis

“…Further, Cannella et al (19) suggested that magnetic resonance imaging (MRI)-based radiomics showed acceptable predictive performance, with an AUC of 0.791 for predicting the tumor response to TACE in 51 patients with HCC. At present, radiomicsrelated literature on HCC has identified various features and predictors for tumor response in several differently designed studies (multicenter versus single center), image segmentation methods (manual versus semi-automatic segmentation), imaging modality (CT or MRI), and predictive models (hand-crafted radiomics versus machine learning versus deep learning methods) (20). However, researchers have not yet reached a consensus on the most effective means to use radiomics to predict treatment response in patients with HCC who undergo TACE.…”