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Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram

OBJECTIVE: The present study aimed to predict myocardial ischemia in coronary heart disease (CHD) patients based on the radiologic features of coronary computed tomography angiography (CCTA) combined with clinical factors. METHODS: The imaging and clinical data of 110 patients who underwent CCTA sca...

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Autores principales: Yang, You-Chang, Dou, Yang, Wang, Zhi-Wei, Yin, Ruo-Han, Pan, Chang-Jie, Duan, Shao-Feng, Tang, Xiao-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893015/
https://www.ncbi.nlm.nih.gov/pubmed/36742075
http://dx.doi.org/10.3389/fcvm.2023.1024773
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author Yang, You-Chang
Dou, Yang
Wang, Zhi-Wei
Yin, Ruo-Han
Pan, Chang-Jie
Duan, Shao-Feng
Tang, Xiao-Qiang
author_facet Yang, You-Chang
Dou, Yang
Wang, Zhi-Wei
Yin, Ruo-Han
Pan, Chang-Jie
Duan, Shao-Feng
Tang, Xiao-Qiang
author_sort Yang, You-Chang
collection PubMed
description OBJECTIVE: The present study aimed to predict myocardial ischemia in coronary heart disease (CHD) patients based on the radiologic features of coronary computed tomography angiography (CCTA) combined with clinical factors. METHODS: The imaging and clinical data of 110 patients who underwent CCTA scan before DSA or FFR examination in Changzhou Second People’s Hospital, Nanjing Medical University (90 patients), and The First Affiliated Hospital of Soochow University (20 patients) from March 2018 to January 2022 were retrospectively analyzed. According to the digital subtraction angiography (DSA) and fractional flow reserve (FFR) results, all patients were assigned to myocardial ischemia (n = 58) and normal myocardial blood supply (n = 52) groups. All patients were further categorized into training (n = 64) and internal validation (n = 26) sets at a ratio of 7:3, and the patients from second site were used as external validation. Clinical indicators of patients were collected, the left ventricular myocardium were segmented from CCTA images using CQK software, and the radiomics features were extracted using pyradiomics software. Independent prediction models and combined prediction models were established. The predictive performance of the model was assessed by calibration curve analysis, receiver operating characteristic (ROC) curve and decision curve analysis. RESULTS: The combined model consisted of one important clinical factor and eight selected radiomic features. The area under the ROC curve (AUC) of radiomic model was 0.826 in training set, and 0.744 in the internal validation set. For the combined model, the AUCs were 0.873, 0.810, 0.800 in the training, internal validation, and external validation sets, respectively. The calibration curves demonstrated that the probability of myocardial ischemia predicted by the combined model was in good agreement with the observed values in both training and validation sets. The decision curve was within the threshold range of 0.1–1, and the clinical value of nomogram was higher than that of clinical model. CONCLUSION: The radiomic characteristics of CCTA combined with clinical factors have a good clinical value in predicting myocardial ischemia in CHD patients.
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spelling pubmed-98930152023-02-03 Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram Yang, You-Chang Dou, Yang Wang, Zhi-Wei Yin, Ruo-Han Pan, Chang-Jie Duan, Shao-Feng Tang, Xiao-Qiang Front Cardiovasc Med Cardiovascular Medicine OBJECTIVE: The present study aimed to predict myocardial ischemia in coronary heart disease (CHD) patients based on the radiologic features of coronary computed tomography angiography (CCTA) combined with clinical factors. METHODS: The imaging and clinical data of 110 patients who underwent CCTA scan before DSA or FFR examination in Changzhou Second People’s Hospital, Nanjing Medical University (90 patients), and The First Affiliated Hospital of Soochow University (20 patients) from March 2018 to January 2022 were retrospectively analyzed. According to the digital subtraction angiography (DSA) and fractional flow reserve (FFR) results, all patients were assigned to myocardial ischemia (n = 58) and normal myocardial blood supply (n = 52) groups. All patients were further categorized into training (n = 64) and internal validation (n = 26) sets at a ratio of 7:3, and the patients from second site were used as external validation. Clinical indicators of patients were collected, the left ventricular myocardium were segmented from CCTA images using CQK software, and the radiomics features were extracted using pyradiomics software. Independent prediction models and combined prediction models were established. The predictive performance of the model was assessed by calibration curve analysis, receiver operating characteristic (ROC) curve and decision curve analysis. RESULTS: The combined model consisted of one important clinical factor and eight selected radiomic features. The area under the ROC curve (AUC) of radiomic model was 0.826 in training set, and 0.744 in the internal validation set. For the combined model, the AUCs were 0.873, 0.810, 0.800 in the training, internal validation, and external validation sets, respectively. The calibration curves demonstrated that the probability of myocardial ischemia predicted by the combined model was in good agreement with the observed values in both training and validation sets. The decision curve was within the threshold range of 0.1–1, and the clinical value of nomogram was higher than that of clinical model. CONCLUSION: The radiomic characteristics of CCTA combined with clinical factors have a good clinical value in predicting myocardial ischemia in CHD patients. Frontiers Media S.A. 2023-01-19 /pmc/articles/PMC9893015/ /pubmed/36742075 http://dx.doi.org/10.3389/fcvm.2023.1024773 Text en Copyright © 2023 Yang, Dou, Wang, Yin, Pan, Duan and Tang. 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 Cardiovascular Medicine
Yang, You-Chang
Dou, Yang
Wang, Zhi-Wei
Yin, Ruo-Han
Pan, Chang-Jie
Duan, Shao-Feng
Tang, Xiao-Qiang
Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title_full Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title_fullStr Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title_full_unstemmed Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title_short Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
title_sort prediction of myocardial ischemia in coronary heart disease patients using a ccta–based radiomic nomogram
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893015/
https://www.ncbi.nlm.nih.gov/pubmed/36742075
http://dx.doi.org/10.3389/fcvm.2023.1024773
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