Wang CY, Zhang L, Ma JW. Computed tomography 3D reconstruction and texture analysis for evaluating the efficacy of neoadjuvant chemotherapy in advanced gastric cancer. World J Gastrointest Surg 2025; 17(6): 104545 [DOI: 10.4240/wjgs.v17.i6.104545]
Corresponding Author of This Article
Jing-Wei Ma, Associate Chief Physician, Department of Medical Imaging I, Shaanxi Kangfu Hospital, No. 52 Electronic Road 2, Xi’an 710065, Shaanxi Province, China. lijing5923@sina.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Surg. Jun 27, 2025; 17(6): 104545 Published online Jun 27, 2025. doi: 10.4240/wjgs.v17.i6.104545
Computed tomography 3D reconstruction and texture analysis for evaluating the efficacy of neoadjuvant chemotherapy in advanced gastric cancer
Chun-Ye Wang, Lei Zhang, Jing-Wei Ma
Chun-Ye Wang, Lei Zhang, Department of Imaging, Yantaishan Hospital, Yantai 264003, Shandong Province, China
Jing-Wei Ma, Department of Medical Imaging I, Shaanxi Kangfu Hospital, Xi’an 710065, Shaanxi Province, China
Author contributions: Wang CY and Zhang L contributed equally to the conception and design of the study, as well as data collection and analysis; Ma JW provided critical insights into the data interpretation, supervised the overall project, and handled the manuscript’s final review and submission. All authors read and approved the final manuscript.
Institutional review board statement: This study was approved by the Institutional Review Board of Shaanxi Kangfu Hospital (approval No. SXKF2024-11).
Informed consent statement: Informed consent was obtained from all subjects involved in the study.
Conflict-of-interest statement: The authors declare that they have no conflicts of interest related to this study.
Data sharing statement: The data generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jing-Wei Ma, Associate Chief Physician, Department of Medical Imaging I, Shaanxi Kangfu Hospital, No. 52 Electronic Road 2, Xi’an 710065, Shaanxi Province, China. lijing5923@sina.com
Received: January 8, 2025 Revised: February 23, 2025 Accepted: May 12, 2025 Published online: June 27, 2025 Processing time: 142 Days and 3.4 Hours
Core Tip
Core Tip: This study highlights the value of computed tomography (CT) 3D reconstruction, texture analysis, and visual features in assessing neoadjuvant chemotherapy efficacy for gastric cancer (GC). The tumor volume change rate, derived from CT 3D reconstruction, showed a strong correlation with pathological tumor regression grade, outperforming CT visual features in predictive accuracy. Texture analysis, especially in the venous phase, demonstrated superior diagnostic capability. Combining these quantitative and qualitative imaging indicators provides a robust evaluation framework, aiding personalized treatment decisions. These findings emphasize the clinical utility of advanced imaging techniques for optimizing chemotherapy strategies and improving patient outcomes in GC management.
