Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis.

Si-Hyuck Kang Soo-Hyun Kim Sun-Hwa Kim Eun Ju Chun Woo-Young Chung Chang Hwan Yoon Sang-Don Park Chang Wook Nam Ki-Hwan Kwon Joon-Hyung Doh Young-Sup Byun Jang-Whan Bae Tae Jin Youn Si-Hyuck Kang

Published in: Journal of Korean medical science (2023)

This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

Keyphrases

image quality
machine learning
computed tomography
dual energy
contrast enhanced
deep learning
coronary artery
coronary artery disease
positron emission tomography
high throughput
magnetic resonance imaging
current status
magnetic resonance
heart failure
neural network
pet ct
transcatheter aortic valve replacement