5 years ago

Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve Based on Machine Learning for Risk Stratification of Non-Culprit Coronary Narrowings in Patients with Acute Coronary Syndrome

This study investigated the prognostic value of coronary computed tomography angiography (cCTA)-derived fractional flow reserve (CT-FFR) in patients with acute coronary syndrome (ACS) and multivessel disease to gauge significance and guide management of non-culprit lesions. We retrospectively analyzed data of 48 patients (56 ± 10 years, 60% men) who were admitted for symptoms suggestive of ACS and underwent dual-source cCTA followed by invasive coronary angiography with culprit lesion intervention. Culprit lesions were retrospectively identified on cCTA using images obtained during invasive coronary angiography. Non-culprit lesions with ≥25% luminal stenosis and deferred intervention were evaluated using a machine learning CT-FFR algorithm to determine lesion-specific ischemia (CT-FFR ≤0.80). Follow-up was performed. CT-FFR identified lesion-specific ischemia in 23 of 81 non-culprit lesions. After a median follow-up of 19.5 months, 14 patients (29%) had major adverse cardiac events (MACE). Univariate Cox regression analysis revealed that CT-FFR ≤0.80 (hazard ratio [HR] 3.77 [95% confidence interval 1.16 to 12.29], p = 0.027), Framingham risk score (FRS) (HR 2.96 [1.01 to 7.63], p = 0.038), and a CAD-RADS classification ≥3 (HR 3.12 [1.03 to 10.17], p = 0.051) were predictors of MACE. In a risk-adjusted model controlling for FRS and CAD-RADS ≥3, CT-FFR ≤0.80 remained a predictor of MACE (1.56 [1.01 to 2.83], p = 0.048). Receiver operating characteristics analysis including FRS, CAD-RADS ≥ 3, and CT-FFR ≤0.80 (area under the curve 0.78) showed incremental discriminatory power over FRS alone (area under the curve 0.66, p = 0.032). CT-FFR of non-culprit lesions in patients with ACS and multivessel disease adds prognostic value to identify risk of future MACE.

Publisher URL: www.sciencedirect.com/science

DOI: S0002914917311724

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.