Prediction of efficacy of neoadjuvant chemoradiotherapy for rectal cancer: the value of texture analysis of magnetic resonance images

Purpose To explore the clinical feasibility of predicting the efficacy of neoadjuvant chemoradiotherapy (nCRT) for rectal cancer on the basis of texture analysis (TA) of T2-weighted imaging (T2WI). Methods The cohort for this prospective study comprised 136 patients with rectal cancer to be treated with nCRT, all of whom underwent three MR scans (pre-, early, and post-nCRT). Treatment efficacy was assessed on the basis of the outcomes of pathologic complete response (pCR) and non-pCR as determined by postoperative pathological examination. Extraction and analysis of texture features in T2WI of defined tumor regions were performed by AK software. Pre- and early-nCRT texture features were selected as potential predictors of outcomes by logistic regression analysis, and a prediction model for pCR was developed. A receiver operating characteristic (ROC) curve was used to assess the predictive power of texture features in pre- and early-nCRT images. Results Univariate logistic regression analysis demonstrated that the pre-nCRT features of energy, entropy, and skewness, and early-nCRT features of variance, kurtosis, energy, and entropy were independent predictors of pCR. A prediction model incorporating these predictors was constructed by multivariate logistic regression, The AUCs of pre-nCRT, early, and combined models were 0.751, 0.831, and 0.873, respectively; the sensitivities 66, 71, and 75%, respectively; and the specificities 87.22, 86.11, and 91.67%, respectively. Conclusions TA of T2WI images can predict the efficacy of nCRT for rectal cancer, possibly providing a new marker of tumor biological response in clinical practice.