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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Gastrointestinal Cancers: Gastric and Esophageal Cancers
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1467665

Identifying Subtle Differences ：A Radiomics Model Assessment for Gastric Schwannomas and Gastrointestinal Stromal Tumors Across Risk Grades

Provisionally accepted
Zimei Yang Zimei Yang 1Chongfei Ma Chongfei Ma 1*Jialiang Ren Jialiang Ren 2Min Li Min Li 1Xiaosheng Xv Xiaosheng Xv 1*Xin Fu Xin Fu 1*Li Yang Li Yang 1*
  • 1 Fourth Hospital of Hebei Medical University, Shijiazhuang, China
  • 2 GE HealthCare China Co Ltd, Beijing, China

The final, formatted version of the article will be published soon.

    Objective: This study aims to develop and validate an enhanced computed tomography (CT)-based radiomics modelto differentiate gastric schwannomas (GS) from gastrointestinal stromal tumors (GIST) across various risk categories.This retrospective analysis was conducted on 26 GS and 82 GIST cases, all confirmed by postoperative pathology. Data was divided into training and validation cohorts at a 7:3 ratio. We collected patient demographics, clinical presentations, and detailed CT imaging characteristics. Through univariable and multivariable logistic regression analyses, we identified independent predictors for discriminating between GS and GIST, facilitating the construction of a conventional model. Radiomic features were extracted and refined through manual 3D segmentation of venous phase thin-slice images to develop a radiomics model. Subsequently, we constructed a comprehensive combined model by integrating selected clinical and radiomics indicators. The diagnostic performances of all models in differentiating GS from GIST and stratifying GISTs according to malignancy risk were evaluated.We identified several key independent variables distinguishing GS from GIST, including tumor location, cystic changes, degree of enhancement in arterial phase, and enhancement uniformity. The conventional model achieved AUCs of 0.939

    Keywords: Gastrointestinal Stromal Tumor, risk stratification, computed tomography imaging, Gastric schwannoma, Radiomics

    Received: 20 Jul 2024; Accepted: 04 Dec 2024.

    Copyright: © 2024 Yang, Ma, Ren, Li, Xv, Fu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Chongfei Ma, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
    Xiaosheng Xv, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
    Xin Fu, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
    Li Yang, Fourth Hospital of Hebei Medical University, Shijiazhuang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.