Prediction of the efficacy of neoadjuvant chemoradiotherapy in patients with rectal cancer based on a texture analysis of T2-weighted magnetic resonance tumor image obtained at primary staging

Abstract

BACKGROUND: Recently, significant efforts have been undertaken to find potential noninvasive biomarkers for predicting the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy.

AIM: To assess the texture characteristics of locally advanced rectal cancer in primary T2-weighted imaging (T2-WI) as a potential predictor for the efficacy of standard neoadjuvant chemoradiotherapy and develop a prediction system for the efficacy of neoadjuvant chemoradiotherapy based on them.

MATERIALS AND METHODS: The retrospective study enrolled 82 patients with locally advanced rectal cancer who received combination treatment with neoadjuvant chemoradiotherapy. Patient data were divided into the training (n=58) and control (n=24) sets. For texture analysis, primary high-resolution T2-WI at the level of the tumor center, oriented perpendicular to the intestinal wall, was used. The texture analysis was performed by second-order statistics based on the gray-level co-occurrence matrices using MAZDA ver. 4.6 featuring the calculation of 11 texture parameters. In the training set, based on the morphological assessment of surgical specimens, significantly different texture analysis parameters were found for two groups of patients: neoadjuvant chemoradiotherapy responders (good prognosis group) and nonresponders (poor prognosis group). Accordingly, a scoring system was created for assessing the efficacy of neoadjuvant chemoradiotherapy. The system was tested on the control set, and diagnostic efficacy parameters were determined.

RESULTS: In the training set, the good and poor prognosis groups differed significantly in five texture parameters: AngScMom (p=0.021), SumofSqs (p=0.003), SumEntrp (p=0.003), Entropy (p=0.038), and SumVarnc (p=0.015), for which the cutoff points were found. These parameters were applied to create the scoring system (excluding the Entropy parameter, which had a strong direct correlation with SumEntrp and the lowest area under the curve, and SumofSqs, which had low reproducibility). The diagnostic efficiency of the scoring system for predicting the response had sensitivity, specificity, positive-predictive value, and negative- predictive value of 72%, 69%, 70%, and 71% for the training set and 80%, 64%, 62%, and 82% for the control set, respectively. The areas under the ROC curve were 0.77 and 0.72 for the training and control sets, respectively.

CONCLUSIONS: Texture analysis of the primary T2-WI of tumors in patients with locally advanced rectal cancer allows for predicting the efficacy of neoadjuvant chemoradiotherapy with moderate diagnostic efficiency. The results suggest good prospects for further research in this area.

Keywords

rectal cancer / magnetic resonance imaging / radiomics / texture analysis / treatment efficacy assessment / primary staging

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