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Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study
PURPOSE: This study was to investigate the diagnostic efficacy of radiomics models based on the enhanced CT images in differentiating the malignant risk of gastrointestinal stromal tumors (GIST) in comparison with the clinical indicators model and traditional CT diagnostic criteria. MATERIALS AND ME...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425090/ https://www.ncbi.nlm.nih.gov/pubmed/36052224 http://dx.doi.org/10.3389/fonc.2022.966743 |
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author | Wang, Yun Wang, Yurui Ren, Jialiang Jia, Linyi Ma, Luyao Yin, Xiaoping Yang, Fei Gao, Bu-Lang |
author_facet | Wang, Yun Wang, Yurui Ren, Jialiang Jia, Linyi Ma, Luyao Yin, Xiaoping Yang, Fei Gao, Bu-Lang |
author_sort | Wang, Yun |
collection | PubMed |
description | PURPOSE: This study was to investigate the diagnostic efficacy of radiomics models based on the enhanced CT images in differentiating the malignant risk of gastrointestinal stromal tumors (GIST) in comparison with the clinical indicators model and traditional CT diagnostic criteria. MATERIALS AND METHODS: A total of 342 patients with GISTs confirmed histopathologically were enrolled from five medical centers. Data of patients wrom two centers comprised the training group (n=196), and data from the remaining three centers constituted the validation group (n=146). After CT image segmentation and feature extraction and selection, the arterial phase model and venous phase model were established. The maximum diameter of the tumor and internal necrosis were used to establish a clinical indicators model. The traditional CT diagnostic criteria were established for the classification of malignant potential of tumor. The performance of the four models was assessed using the receiver operating characteristics curve. REUSLTS: In the training group, the area under the curves(AUCs) of the arterial phase model, venous phase model, clinical indicators model, and traditional CT diagnostic criteria were 0.930 [95% confidence interval (CI): 0.895-0.965), 0.933 (95%CI 0.898-0.967), 0.917 (95%CI 0.872-0.961) and 0.782 (95%CI 0.717-0.848), respectively. In the validation group, the AUCs of the models were 0.960 (95%CI 0.930-0.990), 0.961 (95% CI 0.930-0.992), 0.922 (95%CI 0.884-0.960) and 0.768 (95%CI 0.692-0.844), respectively. No significant difference was detected in the AUC between the arterial phase model, venous phase model, and clinical indicators model by the DeLong test, whereas a significant difference was observed between the traditional CT diagnostic criteria and the other three models. CONCLUSION: The radiomics model using the morphological features of GISTs play a significant role in tumor risk stratification and can provide a reference for clinical diagnosis and treatment plan. |
format | Online Article Text |
id | pubmed-9425090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94250902022-08-31 Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study Wang, Yun Wang, Yurui Ren, Jialiang Jia, Linyi Ma, Luyao Yin, Xiaoping Yang, Fei Gao, Bu-Lang Front Oncol Oncology PURPOSE: This study was to investigate the diagnostic efficacy of radiomics models based on the enhanced CT images in differentiating the malignant risk of gastrointestinal stromal tumors (GIST) in comparison with the clinical indicators model and traditional CT diagnostic criteria. MATERIALS AND METHODS: A total of 342 patients with GISTs confirmed histopathologically were enrolled from five medical centers. Data of patients wrom two centers comprised the training group (n=196), and data from the remaining three centers constituted the validation group (n=146). After CT image segmentation and feature extraction and selection, the arterial phase model and venous phase model were established. The maximum diameter of the tumor and internal necrosis were used to establish a clinical indicators model. The traditional CT diagnostic criteria were established for the classification of malignant potential of tumor. The performance of the four models was assessed using the receiver operating characteristics curve. REUSLTS: In the training group, the area under the curves(AUCs) of the arterial phase model, venous phase model, clinical indicators model, and traditional CT diagnostic criteria were 0.930 [95% confidence interval (CI): 0.895-0.965), 0.933 (95%CI 0.898-0.967), 0.917 (95%CI 0.872-0.961) and 0.782 (95%CI 0.717-0.848), respectively. In the validation group, the AUCs of the models were 0.960 (95%CI 0.930-0.990), 0.961 (95% CI 0.930-0.992), 0.922 (95%CI 0.884-0.960) and 0.768 (95%CI 0.692-0.844), respectively. No significant difference was detected in the AUC between the arterial phase model, venous phase model, and clinical indicators model by the DeLong test, whereas a significant difference was observed between the traditional CT diagnostic criteria and the other three models. CONCLUSION: The radiomics model using the morphological features of GISTs play a significant role in tumor risk stratification and can provide a reference for clinical diagnosis and treatment plan. Frontiers Media S.A. 2022-08-16 /pmc/articles/PMC9425090/ /pubmed/36052224 http://dx.doi.org/10.3389/fonc.2022.966743 Text en Copyright © 2022 Wang, Wang, Ren, Jia, Ma, Yin, Yang and Gao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Wang, Yun Wang, Yurui Ren, Jialiang Jia, Linyi Ma, Luyao Yin, Xiaoping Yang, Fei Gao, Bu-Lang Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title | Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title_full | Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title_fullStr | Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title_full_unstemmed | Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title_short | Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study |
title_sort | malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: a multi-center study |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425090/ https://www.ncbi.nlm.nih.gov/pubmed/36052224 http://dx.doi.org/10.3389/fonc.2022.966743 |
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