MRI features in differentiating mucosal high-grade neoplasia from early invasive squamous cell cancer of the esophagus.

Abstract

To evaluate the diagnostic accuracy of unenhanced and contrast-enhanced MRI in the differentiation of mucosal high-grade neoplasia (MHN) from early invasive squamous cell cancer (EISCC) of the esophagus. Between March 2015 and January 2019, 72 study participants with MHN (n = 46) and EISCC (n = 26) of the esophagus were enrolled in this prospective study. Postoperative histopathologic analysis was the reference standard. All participants underwent MRI (T2-multi-shot turbo spin-echo sequence (msTSE), diffusion-weighted imaging (DWI), and 3D gradient-echo-based sequence (3D-GRE)). Two radiologists, blinded to participants' data, independently evaluated MRI and assigned MR features including shape (mucosal thickening or focal mass), signal on T2-msTSE and DWI, enhancement degree (intense or slight), and enhancement pattern (homogeneous, heterogeneous, or heart-shaped). Diagnostic performance of the 5 features was compared using the chi-square test; kappa values were assessed for reader performance. Surgery was performed within 3.6 + 3.5days after MR imaging. Inter-reader agreement on MR features was excellent (kappa value = 0.854, p < 0.001). All 8 mass-like MHN were "heart-shaped" in appearance. The degree of enhancement showed the best diagnosis performance in differentiating between MHN and EISCC of the esophagus. The combination of all 5 features had only borderline improved sensitivity, specificity, and AUC of 100%, 96.2%, and 0.999, respectively, which was not statistically significant compared with the degree of enhancement alone. MRI can differentiate MHN from EISCC in esophagus; the presence of "heart-shaped" appearance favors the diagnosis of MHN. • All 8 mass-like MHN showed a "heart-shaped" enhancement pattern which may help differentiating MHN from EISCC. • Degree of enhancement had the best diagnostic performance in differentiating between MHN and EISCC in esophagus. • The combined 5 features (shape, signal in T2-msTSE and DWI, enhancement degree, and enhancement pattern) provided sensitivity, specificity, and AUC of 100%, 96.2%, and 0.999, respectively, which was not statistically significant than tumor enhancement alone in distinguishing MHN from EISCC.