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Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy

PURPOSE: This study aimed to construct a radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation (POAF) after pulmonary endarterectomy (PEA) in patients with chronic thromboembolic pulmonary hypertension (CTEPH). METHODS: We reviewed the preoperative compute...

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Autores principales: Liu, Zhan, Deng, Yisen, Wang, Xuming, Liu, Xiaopeng, Zheng, Xia, Sun, Guang, Zhen, Yanan, Liu, Min, Ye, Zhidong, Wen, Jianyan, Liu, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9869069/
https://www.ncbi.nlm.nih.gov/pubmed/36698949
http://dx.doi.org/10.3389/fcvm.2022.1046931
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author Liu, Zhan
Deng, Yisen
Wang, Xuming
Liu, Xiaopeng
Zheng, Xia
Sun, Guang
Zhen, Yanan
Liu, Min
Ye, Zhidong
Wen, Jianyan
Liu, Peng
author_facet Liu, Zhan
Deng, Yisen
Wang, Xuming
Liu, Xiaopeng
Zheng, Xia
Sun, Guang
Zhen, Yanan
Liu, Min
Ye, Zhidong
Wen, Jianyan
Liu, Peng
author_sort Liu, Zhan
collection PubMed
description PURPOSE: This study aimed to construct a radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation (POAF) after pulmonary endarterectomy (PEA) in patients with chronic thromboembolic pulmonary hypertension (CTEPH). METHODS: We reviewed the preoperative computed tomography pulmonary angiography images of CTEPH patients who underwent PEA at our institution between December 2016 and May 2022. Patients were divided into training/validation and testing cohorts by stratified random sampling in a ratio of 7:3. Radiomics features were selected by using intra- and inter-class correlation coefficient, redundancy analysis, and Least Absolute Shrinkage and Selection Operator algorithm to construct the radiomics signature. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical practicability of the radiomics signature. Two hundred-times stratified five-fold cross-validation was applied to assess the reliability and robustness of the radiomics signature. RESULTS: A total of 93 patients with CTEPH were included in this study, including 23 patients with POAF and 70 patients without POAF. Five of the 1,218 radiomics features were finally selected to construct the radiomics signature. The radiomics signature showed good discrimination with an AUC of 0.804 (95%CI: 0.664–0.943) in the training/validation cohort and 0.728 (95% CI: 0.503–0.953) in the testing cohorts. The average AUC of 200 times stratified five-fold cross-validation was 0.804 (95%CI: 0.801–0.806) and 0.807 (95%CI: 0.798–0.816) in the training and validation cohorts, respectively. The calibration curve showed good agreement between the predicted and actual observations. Based on the DCA, the radiomics signature was found to be clinically significant and useful. CONCLUSION: The radiomics signature achieved good discrimination, calibration, and clinical practicability. As a potential imaging biomarker, the radiomics signature of epicardial adipose tissue (EAT) may provide a reference for the risk assessment and individualized treatment of CTEPH patients at high risk of developing POAF after PEA.
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spelling pubmed-98690692023-01-24 Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy Liu, Zhan Deng, Yisen Wang, Xuming Liu, Xiaopeng Zheng, Xia Sun, Guang Zhen, Yanan Liu, Min Ye, Zhidong Wen, Jianyan Liu, Peng Front Cardiovasc Med Cardiovascular Medicine PURPOSE: This study aimed to construct a radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation (POAF) after pulmonary endarterectomy (PEA) in patients with chronic thromboembolic pulmonary hypertension (CTEPH). METHODS: We reviewed the preoperative computed tomography pulmonary angiography images of CTEPH patients who underwent PEA at our institution between December 2016 and May 2022. Patients were divided into training/validation and testing cohorts by stratified random sampling in a ratio of 7:3. Radiomics features were selected by using intra- and inter-class correlation coefficient, redundancy analysis, and Least Absolute Shrinkage and Selection Operator algorithm to construct the radiomics signature. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical practicability of the radiomics signature. Two hundred-times stratified five-fold cross-validation was applied to assess the reliability and robustness of the radiomics signature. RESULTS: A total of 93 patients with CTEPH were included in this study, including 23 patients with POAF and 70 patients without POAF. Five of the 1,218 radiomics features were finally selected to construct the radiomics signature. The radiomics signature showed good discrimination with an AUC of 0.804 (95%CI: 0.664–0.943) in the training/validation cohort and 0.728 (95% CI: 0.503–0.953) in the testing cohorts. The average AUC of 200 times stratified five-fold cross-validation was 0.804 (95%CI: 0.801–0.806) and 0.807 (95%CI: 0.798–0.816) in the training and validation cohorts, respectively. The calibration curve showed good agreement between the predicted and actual observations. Based on the DCA, the radiomics signature was found to be clinically significant and useful. CONCLUSION: The radiomics signature achieved good discrimination, calibration, and clinical practicability. As a potential imaging biomarker, the radiomics signature of epicardial adipose tissue (EAT) may provide a reference for the risk assessment and individualized treatment of CTEPH patients at high risk of developing POAF after PEA. Frontiers Media S.A. 2023-01-09 /pmc/articles/PMC9869069/ /pubmed/36698949 http://dx.doi.org/10.3389/fcvm.2022.1046931 Text en Copyright © 2023 Liu, Deng, Wang, Liu, Zheng, Sun, Zhen, Liu, Ye, Wen and Liu. 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
Liu, Zhan
Deng, Yisen
Wang, Xuming
Liu, Xiaopeng
Zheng, Xia
Sun, Guang
Zhen, Yanan
Liu, Min
Ye, Zhidong
Wen, Jianyan
Liu, Peng
Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title_full Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title_fullStr Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title_full_unstemmed Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title_short Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
title_sort radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9869069/
https://www.ncbi.nlm.nih.gov/pubmed/36698949
http://dx.doi.org/10.3389/fcvm.2022.1046931
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