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Published in: European Radiology 3/2021

01-03-2021 | CT Angiography | Computed Tomography

The effect of coronary calcification on diagnostic performance of machine learning–based CT-FFR: a Chinese multicenter study

Authors: Meng Di Jiang, Xiao Lei Zhang, Hui Liu, Chun Xiang Tang, Jian Hua Li, Yi Ning Wang, Peng Peng Xu, Chang Sheng Zhou, Fan Zhou, Meng Jie Lu, Jia Yin Zhang, Meng Meng Yu, Yang Hou, Min Wen Zheng, Bo Zhang, Dai Min Zhang, Yan Yi, Lei Xu, Xiu Hua Hu, Jian Yang, Guang Ming Lu, Qian Qian Ni, Long Jiang Zhang

Published in: European Radiology | Issue 3/2021

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Abstract

Objective

To investigate the effect of coronary calcification morphology and severity on the diagnostic performance of machine learning (ML)–based coronary CT angiography (CCTA)–derived fractional flow reserve (CT-FFR) with FFR as a reference standard.

Methods

A total of 442 patients (61.2 ± 9.1 years, 70% men) with 544 vessels who underwent CCTA, ML-based CT-FFR, and invasive FFR from China multicenter CT-FFR study were enrolled. The effect of calcification arc, calcification remodeling index (CRI), and Agatston score (AS) on the diagnostic performance of CT-FFR was investigated. CT-FFR ≤ 0.80 and lumen reduction ≥ 50% determined by CCTA were identified as vessel-specific ischemia with invasive FFR as a reference standard.

Results

Compared with invasive FFR, ML-based CT-FFR yielded an overall sensitivity of 0.84, specificity of 0.94, and accuracy of 0.90 in a total of 344 calcification lesions. There was no statistical difference in diagnostic accuracy, sensitivity, or specificity of CT-FFR across different calcification arc, CRI, or AS levels. CT-FFR exhibited improved discrimination of ischemia compared with CCTA alone in lesions with mild-to-moderate calcification (AUC, 0.89 vs. 0.69, p < 0.001) and lesions with CRI ≥ 1 (AUC, 0.89 vs. 0.71, p < 0.001). The diagnostic accuracy and specificity of CT-FFR were higher than CCTA alone in patients and vessels with mid (100 to 299) or high (≥ 300) AS.

Conclusion

Coronary calcification morphology and severity did not influence diagnostic performance of CT-FFR in ischemia detection, and CT-FFR showed marked improved discrimination of ischemia compared with CCTA alone in the setting of calcification.

Key Points

• CT-FFR provides superior diagnostic performance than CCTA alone regardless of coronary calcification.
• No significant differences in the diagnostic performance of CT-FFR were observed in coronary arteries with different coronary calcification arcs and calcified remodeling indexes.
• No significant differences in the diagnostic accuracy of CT-FFR were observed in coronary arteries with different coronary calcification score levels.
Appendix
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Metadata
Title
The effect of coronary calcification on diagnostic performance of machine learning–based CT-FFR: a Chinese multicenter study
Authors
Meng Di Jiang
Xiao Lei Zhang
Hui Liu
Chun Xiang Tang
Jian Hua Li
Yi Ning Wang
Peng Peng Xu
Chang Sheng Zhou
Fan Zhou
Meng Jie Lu
Jia Yin Zhang
Meng Meng Yu
Yang Hou
Min Wen Zheng
Bo Zhang
Dai Min Zhang
Yan Yi
Lei Xu
Xiu Hua Hu
Jian Yang
Guang Ming Lu
Qian Qian Ni
Long Jiang Zhang
Publication date
01-03-2021
Publisher
Springer Berlin Heidelberg
Keyword
CT Angiography
Published in
European Radiology / Issue 3/2021
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-020-07261-2

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