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©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Can visceral fat parameters based on computed tomography be used to predict occult peritoneal metastasis in gastric cancer?
Li-Ming Li, Lei-Yu Feng, Chen-Chen Liu, Wen-Peng Huang, Yang Yu, Peng-Yun Cheng, Jian-Bo Gao
Li-Ming Li, Jian-Bo Gao, Department of Radiology, Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive system Tumor, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Lei-Yu Feng, Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Chen-Chen Liu, Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Wen-Peng Huang, Department of Nuclear Medicine, Peking University First Hospital, Beijing 100034, China
Yang Yu, Peng-Yun Cheng, Beijing Branch, Siemens Healthineers Ltd., Shenyang 110011, Liaoning Province, China
Author contributions: Li LM, Huang WP, and Gao JB designed the research study; Huang WP, Li LM, and Gao JB performed the research; Yu Y and Cheng PY contributed analytic tools; Li LM, Feng LY, and Liu CC analyzed the data and wrote the manuscript; all authors have read and approved the final manuscript.
Supported by Henan Province 2023 Scientific Research Projects Focused on Higher Education Project, China, No. 23A320059.
Institutional review board statement: The study was reviewed and approved by the First Affiliated Hospital of Zhengzhou University Institutional Review Board (Approval No. 2021-KY-1070-002).
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Dataset available from the corresponding author at jianbogaochina@163.com.
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: Jian-Bo Gao, Doctor, Professor, Department of Radiology, Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive system Tumor, The First Affiliated Hospital of Zhengzhou University, No. 1 East Jianshe Road, Zhengzhou 450052, Henan Province, China. jianbogaochina@163.com
Received: November 4, 2022
Peer-review started: November 4, 2022
First decision: January 3, 2023
Revised: January 21, 2023
Accepted: March 20, 2023
Article in press: March 20, 2023
Published online: April 21, 2023
Processing time: 160 Days and 22.3 Hours
ARTICLE HIGHLIGHTS
Research background
The preoperative prediction of peritoneal metastasis (PM) in gastric cancer (GC) would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.
Research motivation
Tumor infiltration of the peritoneum alters the characteristics of the surrounding VF on computed tomography (CT), and these changes have been investigated in previous studies.
Research objectives
We therefore aimed to explore the predictive value of VF parameters obtained from preoperative CT images for occult PM and to develop an individualized model for predicting occult PM in patients with GC.
Research methods
A total of 128 confirmed GC cases that underwent CT scans were analyzed and categorized into PM-positive and PM-negative groups. The clinical characteristics and VF parameters of two regions of interest (ROIs) were collected. Univariate and stratified analyses based on VF volume were performed to screen for predictive characteristics for occult PM. Prediction models with and without VF parameters were established by multivariable logistic regression analysis.
Research results
The mean attenuations of VFROI 1 and VFROI 2 varied significantly between the PM-positive and PM-negative groups (P = 0.044 and 0.001, respectively). The mean attenuation of VFROI 2 was included in the final prediction combined model, but not an independent risk factor of PM (P = 0.068). No significant difference was observed between the models with and without mean attenuation of VF (area under the curve: 0.749 vs 0.730, P = 0.339).
Research conclusions
The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.
Research perspectives
Our study demonstrates the great potential of VF parameters in predicting occult PM in GC and presents a noninvasive preoperative model that combines the mean attenuation of VF and clinical factors for predicting occult PM in GC.
