Value of High-Resolution DWI in Combination With Texture Analysis for the Evaluation of Tumor Response After Preoperative Chemoradiotherapy for Locally Advanced Rectal Cancer.

Abstract

<b>OBJECTIVE.</b> The purpose of this study is to determine the performance of the apparent diffusion coefficient (ADC) value calculated from high-resolution DWI using readout-segmented echo-planar imaging (rs-EPI) and to assess the texture parameters of T2-weighted MR images in identifying pathologic complete response (pCR) after patients with locally advanced rectal cancer (LARC) undergo preoperative chemoradiotherapy (CRT). <b>MATERIALS AND METHODS.</b> A total of 76 patients with LARC who underwent preoperative CRT and subsequent surgery were enrolled in the study retrospectively. All patients underwent post-CRT MRI, which included acquisition of a DWI sequence with use of the rs-EPI technique. The histopathologic tumor regression grade was the reference standard. Patients were subdivided into pCR and non-pCR groups. Two radiologists independently drew whole-tumor ROIs on DW images and T2-weighted MR images to calculate the mean ADC value and first-order texture parameters. <b>RESULTS.</b> Interobserver agreement was good to excellent (intraclass correlation coefficient [ICC], 0.79-0.993) for imaging analysis. Calculated from high-resolution DWI, the mean post-CRT ADC value was significantly higher in the pCR group (<i>p</i> < 0.001). The pCR group also showed lower uniformity (<i>p</i> < 0.001) of the T2-weighted image. The mean ADC value and uniformity were significantly correlated with the tumor regression grade. The mean ADC value was a good indicator for differentiating pCR from absence of pCR (ROC AUC value, 0.912). Uniformity (ROC AUC value, 0.776) showed a moderate ability to identify pCR. Combining the mean ADC value and uniformity yielded an ROC AUC value comparable to that of the mean ADC value (<i>p</i> = 0.125). <b>CONCLUSION.</b> Mean post-CRT ADC values calculated from high-resolution DWI using rs-EPI could effectively select for patients with LARC who have a pCR after preoperative CRT. First-order texture parameters of T2-weighted MR images could also identify patients with pCR by reflecting tumor heterogeneity, even though they could not significantly improve the diagnostic performance.