Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

Eur Radiol. 2019 May;29(5):2378-2387. doi: 10.1007/s00330-018-5834-z. Epub 2018 Dec 6.

Abstract

Objectives: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.

Methods: Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning-based CT-FFR. The discriminatory value of plaque markers and CT-FFR to identify lesion-specific ischemia on a per-vessel basis was evaluated using invasive FFR as the reference standard.

Results: One hundred three lesion-containing vessels were investigated. 32/103 lesions were hemodynamically significant by invasive FFR. In a multivariate analysis (adjusted for Framingham risk score), the following markers showed predictive value for lesion-specific ischemia (odds ratio [OR]): lesion length (OR 1.15, p = 0.037), non-calcified plaque volume (OR 1.02, p = 0.007), napkin-ring sign (OR 5.97, p = 0.014), and CT-FFR (OR 0.81, p < 0.0001). A receiver operating characteristics analysis showed the benefit of identifying plaque markers over cCTA stenosis grading alone, with AUCs increasing from 0.61 with ≥ 50% stenosis to 0.83 with addition of plaque markers to detect lesion-specific ischemia. Further incremental benefit was realized with the addition of CT-FFR (AUC 0.93).

Conclusion: Coronary CTA-derived plaque markers portend predictive value to identify lesion-specific ischemia when compared to cCTA stenosis grading alone. The addition of CT-FFR to plaque markers shows incremental discriminatory power.

Key points: • Coronary CT angiography (cCTA)-derived quantitative plaque markers of atherosclerosis portend high discriminatory power to identify lesion-specific ischemia. • Coronary CT angiography-derived fractional flow reserve (CT-FFR) shows superior diagnostic performance over cCTA alone in detecting lesion-specific ischemia. • A combination of plaque markers with CT-FFR provides incremental discriminatory value for detecting flow-limiting stenosis.

Keywords: Angiography; Coronary artery disease; Spiral computed tomography.

MeSH terms

  • Computed Tomography Angiography / methods*
  • Coronary Angiography / methods*
  • Coronary Stenosis / diagnosis*
  • Coronary Stenosis / etiology
  • Coronary Stenosis / physiopathology
  • Diagnosis, Computer-Assisted / methods*
  • Female
  • Fractional Flow Reserve, Myocardial / physiology*
  • Humans
  • Machine Learning*
  • Male
  • Middle Aged
  • Plaque, Atherosclerotic / complications
  • Plaque, Atherosclerotic / diagnosis*
  • Plaque, Atherosclerotic / physiopathology
  • ROC Curve
  • Retrospective Studies