Functional Evaluation of Intermediate Coronary Lesions with Integrated Computed Tomography Angiography and Invasive Angiography in Patients with Stable Coronary Artery Disease

Jingyi Xue; Jianqiang Li; Danghui Sun; Li Sheng; Yongtai Gong; Dingyu Wang; Song Zhang; Yilun Zou; Jing Shi; Wei Xu; Mengnan An; Chenguang Dai; Weimin Li; Linqun Zheng; Asiia Vinograd; Guangzhong Liu; Yihui Kong; Yue Li

doi:10.2478/jtim-2022-0018

Functional Evaluation of Intermediate Coronary Lesions with Integrated Computed Tomography Angiography and Invasive Angiography in Patients with Stable Coronary Artery Disease

J Transl Int Med. 2022 Jun 10;10(3):255-263. doi: 10.2478/jtim-2022-0018. eCollection 2022 Sep.

Authors

Jingyi Xue^{1

2}, Jianqiang Li¹, Danghui Sun¹, Li Sheng¹, Yongtai Gong¹, Dingyu Wang¹, Song Zhang¹, Yilun Zou¹, Jing Shi¹, Wei Xu¹, Mengnan An¹, Chenguang Dai¹, Weimin Li¹, Linqun Zheng³, Asiia Vinograd¹, Guangzhong Liu¹, Yihui Kong¹, Yue Li¹

Affiliations

¹ Department of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
² Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510000, Guangdong Province, China.
³ Molecular and Translational Cardiology, Hannover Medical University, Hannover 30625, Germany.

Abstract

Background and objectives: The hemodynamic evaluation of coronary stenoses undergoes a transition from wire-based invasive measurements to image-based computational assessments. However, fractional flow reserve (FFR) values derived from coronary CT angiography (CCTA) and angiography-based quantitative flow ratio have certain limitations in accuracy and efficiency, preventing their widespread use in routine practice. Hence, we aimed to investigate the diagnostic performance of FFR derived from the integration of CCTA and invasive angiography (FFR_CT-angio) with artificial intelligence assistance in patients with stable coronary artery disease (CAD).

Methods: Forty stable CAD patients with 67 target vessels (50%-90% diameter stenosis) were included in this single-center retrospective study. All patients underwent CCTA followed by coronary angiography with FFR measurement within 30 days. Both CCTA and angiographic images were combined to generate a three-dimensional reconstruction of the coronary arteries using artificial intelligence. Subsequently, functional assessment was performed through a deep learning algorithm. FFR was used as the reference.

Results: FFR_CT-angio values were significantly correlated with FFR values (r = 0.81, P < 0.001, Spearman analysis). Per-vessel diagnostic accuracy of FFR_CT-angio was 92.54%. Sensitivity and specificity in identifying ischemic lesions were 100% and 88.10%, respectively. Positive predictive value and negative predictive value were 83.33% and 100%, respectively. Moreover, the diagnostic performance of FFR_CT-angio was satisfactory in different target vessels and different segment lesions.

Conclusions: FFR_CT-angio exhibits excellent diagnostic performance of identifying ischemic lesions in patients with stable CAD. Combining CCTA and angiographic imaging, FFR_CT-angio may represent an effective and practical alternative to invasive FFR in selected patients.

Keywords: CT angiography-derived fractional flow reserve; artificial intelligence; fractional flow reserve; quantitative flow ratio; stable coronary artery disease.

© 2022 Jingyi Xue, Jianqiang Li, Danghui Sun, Li Sheng, Yongtai Gong, Dingyu Wang, Song Zhang, Yilun Zou, Jing Shi, Wei Xu, Mengnan An, Chenguang Dai, Weimin Li, Linqun Zheng, Asiia Vinograd, Guangzhong Liu, Yihui Kong, Yue Li, published by Sciendo.