Radiomic phenotype of peri-coronary adipose tissue as a potential non-invasive imaging tool for detecting atrial fibrillation.

IF 1.8 4区医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

British Journal of Radiology Pub Date : 2025-03-05 DOI:10.1093/bjr/tqaf046

Wu Jingping, Meng Xiao, Wu Dan, Li Yuwei, Zhang Xinghua, Wang Zhenping, Wang Xue, Fan Zhang

{"title":"Radiomic phenotype of peri-coronary adipose tissue as a potential non-invasive imaging tool for detecting atrial fibrillation.","authors":"Wu Jingping, Meng Xiao, Wu Dan, Li Yuwei, Zhang Xinghua, Wang Zhenping, Wang Xue, Fan Zhang","doi":"10.1093/bjr/tqaf046","DOIUrl":null,"url":null,"abstract":"Objectives：: Epicardial adipose tissue (EAT) contribute to atrial fibrillation (AF). We sought to explore the role of FAI (fat attention index), volume, fat radiomic profile (FRP) from peri-coronary artery adipose tissue (PCAT) on coronary computed tomography angiography (CCTA) in determining the presence of AF and differentiating AF types.Methods: This study enrolled 300 patients underwent CCTA retrospectively and divided them into AF (n = 137) and non-AF groups (n = 163). The imaging parameters of FAI, volume and FRP were excavated and measured after PCAT segmentation. Every coronary artery extracted 853 radiomics and a total of 2559 radiomics were collected. Significant and relevant FRP was screened by random forest algorithm based on machine learning, and then compared three models of VF (FAI and volume), FRP and FRPC (FRP and clinical factors). Among AF individuals, the FRP and FRPC scores of persistent AF (PerAF, n = 44) and paroxysmal AF (PAF, n = 93) were compared with boxplot.Results：: In the test cohort, FRP score performed excellent distinctive ability to identify AF with an AUC of 0.89 compared with the model enrolling FAI and volume (AUC = 0.83), and FRPC model showed improved AUC of 0.98 combining clinical factors. Among AF types, FPR and FRPC scores are significantly higher in the PerAF than PAF patients (p < 0.001). And twenty most contributive features were selected in identifying AF.Conclusion: Textural radiomic features derived from PCAT on coronary CTA detect micro-pathophysiological information associated with AF, which may help identify and differentiate AF and provide a hopeful imaging target.Advances in knowledge: The analysis of epicardial tissue around coronary arteries help identify and differentiate atrial fibrillation and its types. Fat radiomic profiles derived from peri-coronary arteries fat could provide non-invasive tool for atrial fibrillation.","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/bjr/tqaf046","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}

引用次数: 0

Abstract

Objectives：: Epicardial adipose tissue (EAT) contribute to atrial fibrillation (AF). We sought to explore the role of FAI (fat attention index), volume, fat radiomic profile (FRP) from peri-coronary artery adipose tissue (PCAT) on coronary computed tomography angiography (CCTA) in determining the presence of AF and differentiating AF types.

Methods: This study enrolled 300 patients underwent CCTA retrospectively and divided them into AF (n = 137) and non-AF groups (n = 163). The imaging parameters of FAI, volume and FRP were excavated and measured after PCAT segmentation. Every coronary artery extracted 853 radiomics and a total of 2559 radiomics were collected. Significant and relevant FRP was screened by random forest algorithm based on machine learning, and then compared three models of VF (FAI and volume), FRP and FRPC (FRP and clinical factors). Among AF individuals, the FRP and FRPC scores of persistent AF (PerAF, n = 44) and paroxysmal AF (PAF, n = 93) were compared with boxplot.

Results：: In the test cohort, FRP score performed excellent distinctive ability to identify AF with an AUC of 0.89 compared with the model enrolling FAI and volume (AUC = 0.83), and FRPC model showed improved AUC of 0.98 combining clinical factors. Among AF types, FPR and FRPC scores are significantly higher in the PerAF than PAF patients (p < 0.001). And twenty most contributive features were selected in identifying AF.

Conclusion: Textural radiomic features derived from PCAT on coronary CTA detect micro-pathophysiological information associated with AF, which may help identify and differentiate AF and provide a hopeful imaging target.

Advances in knowledge: The analysis of epicardial tissue around coronary arteries help identify and differentiate atrial fibrillation and its types. Fat radiomic profiles derived from peri-coronary arteries fat could provide non-invasive tool for atrial fibrillation.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

British Journal of Radiology 医学-核医学

CiteScore

5.30

自引率

3.80%

发文量

330

审稿时长

2-4 weeks

期刊介绍： BJR is the international research journal of the British Institute of Radiology and is the oldest scientific journal in the field of radiology and related sciences. Dating back to 1896, BJR’s history is radiology’s history, and the journal has featured some landmark papers such as the first description of Computed Tomography "Computerized transverse axial tomography" by Godfrey Hounsfield in 1973. A valuable historical resource, the complete BJR archive has been digitized from 1896. Quick Facts: - 2015 Impact Factor – 1.840 - Receipt to first decision – average of 6 weeks - Acceptance to online publication – average of 3 weeks - ISSN: 0007-1285 - eISSN: 1748-880X Open Access option