Sun XF, Zhu HT, Ji WY, Zhang XY, Li XT, Tang L, Sun YS. Preoperative prediction of malignant potential of 2-5 cm gastric gastrointestinal stromal tumors by computerized tomography-based radiomics. World J Gastrointest Oncol 2022; 14(5): 1014-1026 [PMID: 35646280 DOI: 10.4251/wjgo.v14.i5.1014]
Corresponding Author of This Article
Ying-Shi Sun, MD, Chief Doctor, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing 100142, China. sys27@163.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
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 Oncol. May 15, 2022; 14(5): 1014-1026 Published online May 15, 2022. doi: 10.4251/wjgo.v14.i5.1014
Preoperative prediction of malignant potential of 2-5 cm gastric gastrointestinal stromal tumors by computerized tomography-based radiomics
Xue-Feng Sun, Hai-Tao Zhu, Wan-Ying Ji, Xiao-Yan Zhang, Xiao-Ting Li, Lei Tang, Ying-Shi Sun
Xue-Feng Sun, Hai-Tao Zhu, Wan-Ying Ji, Xiao-Yan Zhang, Xiao-Ting Li, Lei Tang, Ying-Shi Sun, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
Author contributions: Sun XF designed the study and was responsible for the work; Sun XF, Tang L, and Ji WY conducted data collection; Sun XF and Zhang XY conducted image measurement; Zhu HT and Li XT conducted statistical analyses; Sun XF wrote the paper; all authors edited the paper.
Supported byBeijing Hospitals Authority Ascent Plan, No. 20191103; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support, No. ZYLX201803; Beijing Natural Science Foundation, No. Z180001 and No. Z200015; and PKU-Baidu Fund, No. 2020BD027.
Institutional review board statement: This retrospective study was approved by the Institutional Review Board of Peking University Cancer Hospital & Institute.
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: The authors have no conflicts to declare.
Data sharing statement: The authors do not want to share the data.
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: Ying-Shi Sun, MD, Chief Doctor, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing 100142, China. sys27@163.com
Received: December 1, 2021 Peer-review started: December 1, 2021 First decision: December 27, 2021 Revised: December 29, 2021 Accepted: April 21, 2022 Article in press: April 21, 2022 Published online: May 15, 2022 Processing time: 160 Days and 1 Hours
ARTICLE HIGHLIGHTS
Research background
Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with varying degrees of malignant potential. Therefore, preoperative evaluation of the biological behavior of GISTs is important for surgical decision-making. Endoscopic resection is an effective and safe treatment for gastric GISTs smaller than 2 cm. Nevertheless, whether endoscopic surgery can be used in resecting gastric GISTs between 2 and 5 cm remains controversial considering the potential risk of metastasis and recurrence. The difficulty in assessing the malignant potential of 2-5 cm gastric GISTs present challenges to surgeons.
Research motivation
Preoperative prediction of the malignant potential and prognosis of GISTs is crucial for clinical decision-making. Radiomics has also been used to preoperatively predict the malignant potential of GISTs. However, the study on 2-5 cm gastric GISTs has not yet been reported.
Research objectives
As stated above, we proposed a radiomics method for predicting the malignant potential of 2-5 cm gastric GISTs based on preoperative enhanced computerized tomography (CT) images. The method may be helpful for preoperative design of individualized treatment strategy for patients with 2-5 cm gastric GISTs.
Research methods
This was a retrospective study in which three models were constructed, including radiological model, radiomics model, and nomogram model. A radiological model was constructed based on CT findings and clinical characteristics. XGboost method was used to construct a radiomics model. Nomogram was constructed by combining the radiomics score with CT findings.
Research results
The area under the curve (AUC) of the nomogram model was significantly larger than the AUC of the radiological model in both the training group and the test group. The decision curve of analysis showed that the nomogram model produces increased benefit across the entire risk threshold range.
Research conclusions
In this study, we developed a radiomics model and a nomogram for malignancy differentiation of 2-5 cm gastric GISTs, which achieved satisfactory discrimination and had the potential to act as a reproducible imaging marker to support the decision-making support in a noninvasive and effective way.
Research perspectives
Future research should be considered on model validation and more integral factors such as KIT and PDGFRA mutations.
