Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Observational Study
. 2024 Sep 9;17(17):1980-1992.
doi: 10.1016/j.jcin.2024.06.027. Epub 2024 Aug 21.

Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography: The ACCURATE-CT Study

Affiliations
Observational Study

Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography: The ACCURATE-CT Study

Changling Li et al. JACC Cardiovasc Interv. .

Abstract

Background: AccuFFRct (ArteryFlow Technology) is a novel noninvasive method for calculating fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA). The accuracy of AccuFFRct has not been adequately assessed.

Objectives: This study sought to evaluate the diagnostic performance of AccuFFRct in detecting lesion-specific ischemia.

Methods: This prospective study enrolled 339 patients with 404 vessels. CCTA-derived FFR was calculated using an on-site computational fluid dynamics-based method and compared with invasive FFR. The performance of AccuFFRct was comprehensively analyzed in all lesions and subgroups, including "gray zone" lesions, various lesion classifications, clinical presentations, stenosis severities, and lesion locations.

Results: Using FFR ≤0.80 as a reference standard, the overall diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for AccuFFRct were 90.6% (95% CI: 87.3%-93.3%), 90.9% (95% CI: 85.1%-94.9%), 90.4% (95% CI: 86.1%-93.8%), 85.3% (95% CI: 79.8%-89.5%), and 94.2% (95% CI: 90.8%-96.4%), respectively. Good correlation and agreement were found between the computed AccuFFRct and measured FFR. AccuFFRct showed superior discrimination ability to CCTA (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.77 [95% CI: 0.72-0.81]; P < 0.001) and quantitative coronary angiography (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.89 [95% CI: 0.85-0.92]; P = 0.048) for identifying functionally significant stenosis. Notably, AccuFFRct maintained high diagnostic accuracy across the spectrum of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the "gray zone". Furthermore, in the cohort with ≥70% stenosis, AccuFFRct could significantly reduce the rate of un-necessary invasive tests (33.1% vs 6.6%; P < 0.001).

Conclusions: The study confirms the potential of AccuFFRct as a noninvasive alternative to invasive FFR for detecting ischemia in coronary artery disease and to risk stratify patients. The results highlight AccuFFRct's robust diagnostic ability across a wide range of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the "gray zone". (Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography [ACCURATE-CT]; NCT04426396).

Keywords: computed tomography; coronary artery disease; fractional flow reserve; ischemia.

PubMed Disclaimer

Conflict of interest statement

Funding Support and Author Disclosures This work was supported by Zhejiang Provincial Public Welfare Technology Research Project (grant LGF20H020012), National Natural Science Foundation of China (grant 82170332), Zhejiang Provincial Key Research and Development Plan (grants 2020C03016 and 2024C03095), and Hangzhou Leading Innovation and Entrepreneurship Team Project (grant TD2022007). Dr Koo has received institutional research grants from HeartFlow and AiMEDIC. Dr Wang serves as Editor-in-Chief for JACC: Asia. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Similar articles

Cited by

MeSH terms

Associated data