Coronary Computed Tomographic Angiography-Derived Radiomics Combing CT-Fractional Flow Reserve for Detecting Hemodynamically Significant Coronary Artery Disease.
10.3881/j.issn.1000-503X.16412
- Author:
Yan YI
1
;
Cheng XU
1
;
Wei WU
2
;
Ying-Qian GE
;
Ke-Ting XU
1
;
Xian-Bo YU
;
Yi-Ning WANG
1
Author Information
1. Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.
2. Department of Cardiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.
- Publication Type:Journal Article
- Keywords:
CT-derived fractional flow reserve;
computed tomography angiography;
coronary atherosclerotic disease;
hemodynamically significant coronary artery disease;
radiomics
- MeSH:
Coronary Angiography/methods*;
Tomography, X-Ray Computed;
Humans;
Hemodynamics;
Coronary Artery Disease/diagnostic imaging*;
Male;
Female;
Middle Aged;
Aged;
Radiomics;
Angina Pectoris/diagnostic imaging*;
China;
Image Processing, Computer-Assisted;
Coronary Vessels/diagnostic imaging*
- From:
Acta Academiae Medicinae Sinicae
2025;47(4):542-549
- CountryChina
- Language:English
-
Abstract:
Objective To develop a diagnostic model combining the CT angiography(CCTA)-derived myocardial radiomics signatures with the CT-derived fractional flow reserve(CT-FFR)based on coronary CCTA and investigate the diagnostic accuracy of the hybrid model for hemodynamically significant coronary artery disease(CAD).Methods The patients presenting stable angina pectoris,diagnosed with CAD,and clinically referred for CCTA examination and invasive coronary angiography were prospectively recruited.Radiomics features of the left ventricular myocardium were extracted from the three main perfusion territories demarcated according to the coronary blood supply.The extracted features were first selected by the minimum redundancy maximum relevance feature ranking method.A least absolute shrinkage and selection operator Logistic regression algorithm with leave-one-out cross-validation was then employed to construct a radiomics model.The CT-FFR value was generated for each blood vessel.The area under the receiver operating characteristics curve(AUC_ROC),sensitivity,and specificity were adopted to evaluate the performance of each model against the reference standard invasive coronary angiography/FFR.Results A total of 70 patients[42 men and 28 women;(61±10) years old] were included in this study and complemented CCTA examination,with 175 vessels and the corresponding myocardial territories undergoing invasive coronary angiography/FFR.A total of 1 656 specific radiomics parameters were extracted,from which 14 features were selected to establish the radiomics model.The AUC_ROC,sensitivity,and specificity were 0.797(95%CI=0.732-0.861),77.1%,and 73.7%for the radiomics model,0.892(95%CI=0.841-0.943),81.4%,and 88.8%for the CT-FFR model,and 0.928(95%CI=0.890-0.965),83.3%,and 88.4%for the hybrid model,respectively.The hybrid model outperformed the radiomics model and CT-FFR alone(P=0.040).Conclusions The radiomics signatures of the vessel-related myocardium from CCTA could provide incremental value to the diagnostic performance of CT-FFR and improve vessel-specific ischemia detection.The hybrid model combining CT-FFR with radiomics signatures is potentially feasible for improving the diagnostic accuracy for hemodynamically significant CAD.
