Comparison of endoscopic ultrasonography features and pathological staging of gastric inflammatory fibroid polyps.

BACKGROUND

The diagnosis of gastric inflammatory fibroid polyps (IFPs) mainly depends on pathological confirmation after endoscopic or surgical treatment. Gastric IFP have typical manifestations under endoscopic ultrasonography (EUS), but atypical EUS features have also been reported. Previous studies have found that atypical features of gastric IFPs observed under EUS have corresponding histological manifestations. At present, there is no study elaborating the EUS manifestations of gastric IFPs at different pathological stages. We hypothesize that gastric IFPs at different pathological stages may have different EUS features.

AIM

To describe EUS features of gastric IFPs and compare with their pathological characteristics.

METHODS

Clinical data of 53 inpatients with pathologically diagnosed gastric IFPs after endoscopic treatment were collected. All patients underwent preoperative EUS. We analyzed the EUS characteristics of the lesions and compared with the pathological characteristics and staging of the resected specimens.

RESULTS

Most gastric IFPs showed medium-low echo (67.9%), homogeneous echo (90.6%), and unclear boundaries (83%), and involved the second and third layers of the gastric wall (69.8%) under EUS. The echogenicity level and echo homogeneity were significantly correlated with the pathological stage of gastric IFP. Gastric IFPs in the nodular stage presented hypoechoic and homogeneous echo. Gastric IFPs in the fibrovascular stage mostly showed medium-low echo and homogeneous echo. Gastric IFPs in the sclerotic stage showed different echogenicity levels and echo homogeneity. The accuracy of EUS in diagnosing gastric IFPs was 66.0% (35/53), and the accuracy in determining the origin layer of gastric IFPs was 73.4% (39/53).

CONCLUSION

Gastric IFPs at different pathological stages have different EUS features. In order to improve the diagnostic rate, it is necessary to combine EUS with EUS-guided fine-needle aspiration or artificial intelligence.