Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
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
Abstract
BACKGROUND

Gastric cancer (GC) remains a significant global health challenge, with high incidence and mortality rates. Neoadjuvant chemotherapy is increasingly used to improve surgical outcomes and long-term survival in advanced cases. However, individual responses to treatment vary widely, and current imaging methods often fall short in accurately predicting efficacy. Advanced imaging techniques, such as computed tomography (CT) 3D reconstruction and texture analysis, offer potential for more precise assessment of therapeutic response.

AIM

To explore the application value of CT 3D reconstruction volume change rate, texture feature analysis, and visual features in assessing the efficacy of neoadjuvant chemotherapy for advanced GC.

METHODS

A retrospective analysis was conducted on the clinical and imaging data of 97 patients with advanced GC who received S-1 plus Oxaliplatin combined chemotherapy regimen neoadjuvant chemotherapy from January 2022 to March 2024. CT texture feature analysis was performed using MaZda software, and ITK-snap software was used to measure the tumor volume change rate before and after chemotherapy. CT visual features were also evaluated. Using postoperative pathological tumor regression grade (TRG) as the gold standard, the correlation between various indicators and chemotherapy efficacy was analyzed, and a predictive model was constructed and internally validated.

RESULTS

The minimum misclassification rate of texture features in venous phase CT images (7.85%) was lower than in the arterial phase (13.92%). The volume change rate in the effective chemotherapy group (75.20%) was significantly higher than in the ineffective group (41.75%). There was a strong correlation between volume change rate and TRG grade (r = -0.886, P < 0.001). Multivariate analysis showed that gastric wall peristalsis (OR = 0.286) and thickness change rate ≥ 40% (OR = 0.265) were independent predictive factors. Receiver operating characteristic curve analysis indicated that the volume change rate [area under the curve (AUC) = 0.885] was superior to the CT visual feature model (AUC = 0.795). When the cutoff value was 82.56%, the sensitivity and specificity were 85.62% and 96.45%, respectively.

CONCLUSION

The CT 3D reconstruction volume change rate can serve as a preferred quantitative indicator for evaluating the efficacy of neoadjuvant chemotherapy in GC. Combining it with a CT visual feature predictive model can further improve the accuracy of efficacy evaluation.

Keywords: Gastric cancer; Neoadjuvant chemotherapy; Computed tomography; 3D reconstruction; Efficacy evaluation

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.