Diagnostic challenges of inflammatory submucosal tumor-like lesions: a multicenter propensity score-matching analysis.

Abstract

Background: Gastrointestinal submucosal tumors (SMTs) are frequently encountered in clinical practice, with diverse etiologies and overlapping endoscopic features. Inflammatory SMT-like lesions (I-SMTLs), though rare and benign, mimic SMTs endoscopically but are fundamentally inflammatory. Limited research exists on their specific diagnostic characteristics.

Methods: This multicenter retrospective study analyzed 59 I-SMTLs among 1,226 pathologically confirmed SMTs from five hospitals in China. The diagnostic efficacy of endoscopic ultrasound (EUS) for I-SMTLs was assessed, and comparison with non-inflammatory SMT-like lesions (non-I-SMTLs) was made using propensity score matching (PSM) balanced for sex, age, lesion location and size. Correlation between endoscopic and pathological characteristics were quantified using Cramer's V coefficient.

Results: I-SMTLs accounted for 4.81% (59/1,226) of SMTs, with 98.31% (58/59) measuring under 2 cm. EUS demonstrated low sensitivity (3.39-4.00%) and a high misdiagnosis rate (96.61%) for I-SMTLs, with over 55% misdiagnosed as potentially malignant and 15% remaining inconclusive. In the PSM cohort (59 I-SMTLs, 118 non-I-SMTLs), I-SMTLs were more frequently located in submucosa (71.19% vs. 42.37%), exhibited mixed-echoic category (18.64% vs. 1.69%), heterogeneous echogenicity (62.71% vs. 21.19%) and unclear boundaries (42.37% vs. 13.56%). Correlation analysis showed cases with smooth muscle hyperplasia in pathology were more likely to arise from the muscularis propria or muscularis mucosae (Cramer's V = 0.490), and cases with fibrous tissue alterations were more likely to exhibit mixed or hyperechoic patterns (Cramer's V = 0.545) and heterogeneous echotexture (Cramer's V = 0.336) on EUS.

Conclusions: I-SMTLs pose significant diagnostic challenges. Distinguishing EUS features, including submucosal location, mixed-echoic patterns, heterogeneous textures, and unclear boundaries, may improve diagnostic accuracy and facilitate appropriate clinical decision-making.