Diagnostic accuracy of a deep learning approach to calculate FFR from coronary CT angiography

Journal of Geriatric Cardiology : JGC
Zhi-Qiang WangYue-Ping Li

Abstract

The computational fluid dynamics (CFD) approach has been frequently applied to compute the fractional flow reserve (FFR) using computed tomography angiography (CTA). This technique is efficient. We developed the DEEPVESSEL-FFR platform using the emerging deep learning technique to calculate the FFR value out of CTA images in five minutes. This study is to evaluate the DEEPVESSEL-FFR platform using the emerging deep learning technique to calculate the FFR value from CTA images as an efficient method. A single-center, prospective study was conducted and 63 patients were enrolled for the evaluation of the diagnostic performance of DEEPVESSEL-FFR. Automatic quantification method for the three-dimensional coronary arterial geometry and the deep learning based prediction of FFR were developed to assess the ischemic risk of the stenotic coronary arteries. Diagnostic performance of the DEEPVESSEL-FFR was assessed by using wire-based FFR as reference standard. The primary evaluation factor was defined by using the area under receiver-operation characteristics curve (AUC) analysis. For per-patient level, taking the cut-off value ≤ 0.8 referring to the FFR measurement, DEEPVESSEL-FFR presented higher diagnostic performance in determining ...Continue Reading

Citations

Jul 4, 2020·The International Journal of Cardiovascular Imaging·Diana OpincariuImre Benedek
Feb 11, 2020·Frontiers in Cardiovascular Medicine·Nils HampeIvana Išgum
Sep 8, 2021·Frontiers in Cardiovascular Medicine·Panagiotis K SiogkasDimitrios I Fotiadis

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Methods Mentioned

BETA
imaging technique
coronary artery bypass

Software Mentioned

SPSS
ICA
DEEPVESSEL
FFR
- FFR
MedCalc

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