Retrospective Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Apr 15, 2020; 12(4): 447-456
Published online Apr 15, 2020. doi: 10.4251/wjgo.v12.i4.447
Nomogram using F-18 fluorodeoxyglucose positron emission tomography/computed tomography for preoperative prediction of lymph node metastasis in gastric cancer
Bong-Il Song
Bong-Il Song, Department of Nuclear Medicine, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu 42601, South Korea
Author contributions: Bong-Il Song edited the manuscript.
Supported by National Research Foundation of Korea, No. 2017R1C1B5076640.
Institutional review board statement: This study was reviewed and approved by the Institutional Review Board of Keimyung University Dongsan Medical Center (IRB No. 2018-06-028-003).
Informed consent statement: The 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: Song BI declare no relevant conflicts of interests.
Data sharing statement: No additional data are available.
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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Bong-Il Song, MD, Associate Professor, Department of Nuclear Medicine, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, 1095 Dalgubeol-daero, Dalseo-gu, Daegu 42601, South Korea. song@dsmc.or.kr
Received: December 27, 2019
Peer-review started: December 27, 2019
First decision: January 19, 2020
Revised: March 13, 2020
Accepted: March 25, 2020
Article in press: March 25, 2020
Published online: April 15, 2020
Processing time: 110 Days and 5.9 Hours
ARTICLE HIGHLIGHTS
Research background

Gastric cancer (GC) is one of the most commonly diagnosed malignancies and the second leading cause of cancer-related deaths worldwide. The status of lymph node (LN) metastasis is an important prognostic factor in patients with GC. However, the evaluation of LN metastasis status in the preoperative setting is not accurate.

Research motivation

A few studies have been conducted to develop a nomogram for the prediction of LN metastasis in GC. However, a preoperative LN metastasis prediction model, based on the tumor metabolic information as measured by F-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) and laboratory findings, does not exist for GC. The purpose of this study was to develop a preoperative nomogram for LN metastasis in patients with GC.

Research objectives

This study aims to identify predictive factors and to develop a preoperative nomogram for the prediction of LN metastasis using F-18 FDG PET/CT and preoperative laboratory findings in patients with GC.

Research methods

Between 2008 and 2010, a total of 566 GC patients who underwent preoperative F-18 FDG PET/CT and subsequent surgical treatment without any preoperative intervention were analyzed. The LN metastasis prediction model was developed in the training cohort (n = 377) and validated in the internal validation cohort (n = 189). Clinicopathological data were retrieved from the patients’ medical records and the F-18 FDG PET/CT images were retrospectively interpreted. Univariate and multivariable logistic regression was performed to validate the preoperative predictive factors for LN metastasis.

Research results

The multivariate logistic analysis showed that the combination of maximum standardized uptake value (SUVmax) of the primary tumor (T_SUVmax) and SUVmax of LN (N_SUVmax), serum albumin, and carbohydrate antigen (CA) 19-9 was the best model to predict the risk of LN metastasis. The preoperative nomogram for the prediction of LN metastasis using T_SUVmax, N_SUVmax, serum albumin, and CA 19-9 showed good performance in the validation cohort as well as the training cohort.

Research conclusions

The combination of preoperative F-18 FDG PET/CT metabolic parameters (T_SUVmax and N_SUVmax) and laboratory findings (albumin and CA 19-9) could be a useful tool for LN metastasis assessment and treatment planning in patients with GC.

Research perspectives

The preoperative nomogram for the prediction of LN should be verified on a larger and external validation cohort for widespread acceptance.