Submucosal Enhancing Stripe as a Contrast Material-enhanced MRI-based Imaging Feature for the Differentiation of Stage T0-T1 from Early T2 Rectal Cancers.

Abstract

Background Accurate differentiation of stage T0-T1 rectal tumors from stage T2 rectal tumors facilitates the selection of appropriate surgical treatment. MRI is a recommended technique for local staging, but its ability to distinguish T1 from T2 tumors is poor. Purpose To explore the value of a submucosal enhancing stripe (SES), an uninterrupted enhancing band between the rectal tumor and the muscular layer on contrast material-enhanced T1-weighted images, as a potential imaging feature to differentiate T0-T1 from T2 rectal tumors. Materials and Methods This retrospective study included patients with pT0-T1 and pT2 rectal tumors who underwent pretreatment MRI and rectal tumor resection between January 2012 and November 2019. Two radiologists independently evaluated tumor characteristics (SES; status of muscularis propria [SMP]; and tumor shape, location, and size) at MRI. The associations of clinical and imaging characteristics with stage T0-T1 or T2 tumors were assessed, β values were calculated, and predictive models were built. The diagnostic accuracies for the differentiation of T0-T1 tumors from T2 tumors with SES and SMP were compared. Results Data from 431 patients (mean age, 60 years ± 10 [standard deviation]; 261 men) were evaluated. SES (β = 3.9; 95% CI: 3.1, 4.7; P < .001), SMP (β = 1.3; 95% CI: 0.7, 1.9; P < .001), and carpetlike shape (β = 1.6; 95% CI: 0.5, 2.8; P = .01) were independent factors distinguishing T0-T1 tumors from T2 tumors. The diagnostic accuracy was 87% (95% CI: 84, 90; 376 of 431) for SES and 67% (95% CI: 63, 72; 290 of 431) for SMP (P < .001). Conclusion Submucosal enhancing stripe (SES) at contrasted-enhanced MRI, status of muscularis propria (SMP) on T2-weighted images, and tumor shape can serve as independent imaging features to differentiate stage T0-T1 rectal tumors from stage T2 rectal tumors. Moreover, SES is a more accurate feature than is SMP. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.