Li LM, Feng LY, Liu CC, Huang WP, Yu Y, Cheng PY, Gao JB. Can visceral fat parameters based on computed tomography be used to predict occult peritoneal metastasis in gastric cancer? World J Gastroenterol 2023; 29(15): 2310-2321 [PMID: 37124887 DOI: 10.3748/wjg.v29.i15.2310]
Corresponding Author of This Article
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
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Case Control 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/
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 byHenan 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
Abstract
BACKGROUND
The preoperative prediction of peritoneal metastasis (PM) in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.
AIM
To explore the predictive value of visceral fat (VF) parameters obtained from preoperative computed tomography (CT) images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma (GC).
METHODS
A total of 128 confirmed GC cases (84 male and 44 female patients) that underwent CT scans were analyzed and categorized into PM-positive (n = 43) and PM-negative (n = 85) 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.
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 areas under the receiver operating characteristic curves (AUCs) of VFROI 1 and VFROI 2 were 0.599 and 0.657, 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 (AUC: 0.749 vs 0.730, P = 0.339).
CONCLUSION
The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.
Core Tip: The preoperative prediction of peritoneal metastasis (PM) in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan. We therefore aimed to explore the predictive value of visceral fat (VF) parameters obtained from preoperative computed tomography images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma (GC). Consequently, mean attenuation of VF is a potential auxiliary parameter to predict occult PM in patients with GC.
