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

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Published Date: Feb 25, 2025

Abstract

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).

Authors

  • Minghui Dou
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Hengchao Liu
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Zhenqi Tang
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Longxi Quan
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Mai Xu
  • Feiqian Wang
    Department of Ultrasound, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Zhilin Du
    Department of Oncology, Chengdu Seventh People's Hospital (Affliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan, China.
  • Zhimin Geng
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. gengzhimin@mail.xjtu.edu.cn.
  • Qi Li
    The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
  • Dong Zhang
    Institute of Acoustics, Nanjing University, Nanjing 210093, China.

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