Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model.

Background: Gallbladder (GB) adenomas, precancerous lesions for gallbladder carcinoma (GBC), lack reliable non-invasive tools for preoperative differentiation of neoplastic polyps from cholesterol polyps. This study aimed to evaluate an interpretable machine learning (ML) combined model for the precise differentiation of the pathological nature of gallbladder polyps (GPs).

Methods: This study consecutively enrolled 744 patients from Xi'an Jiaotong University First Affiliated Hospital between January 2017 and December 2023 who were pathologically diagnosed postoperatively with cholesterol polyps, adenomas or T1-stage GBC.

Assessing the genomic feature of Chinese patients with ampullary adenocarcinoma: potential therapeutic targets.

Backgrounds: Ampullary adenocarcinoma (AMPAC) is a rare malignancy, treated as pancreatic or intestinal cancer based on its histologic subtype. Little is known about the genomic features of Chinese patients with AMPAC.

Materials And Methods: We enrolled 145 Chinese AMPAC patients in our local cohort and performed a compressive somatic and germline genetic testing using a 156 gene panel.