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

  • Philipp L. von Knebel Doeberitz
  • Carlo N. De Cecco
  • U. Joseph SchoepfEmail author
  • Taylor M. Duguay
  • Moritz H. Albrecht
  • Marly van Assen
  • Maximilian J. Bauer
  • Rock H. Savage
  • J. Trent Pannell
  • Domenico De Santis
  • Addison A. Johnson
  • Akos Varga-Szemes
  • Richard R. Bayer
  • Stefan O. Schönberg
  • John W. Nance
  • Christian Tesche



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.


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.


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).


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.


Spiral computed tomography Coronary artery disease Angiography 



Area under the curve


Coronary artery disease


Coronary CT angiography


Fractional flow reserve from coronary CT angiography


Dual-source computed tomography


Fractional flow reserve


Invasive coronary angiography


Negative predictive value


Odds ratio


Plaque burden


Positive predictive value


Remodeling Index


Receiver operating characteristics



The authors state that this work has not received any funding.

Compliance with ethical standards


The scientific guarantor of this publication is U. Joseph Schoepf, MD.

Conflict of interest

Dr. Schoepf receives institutional research support from Astellas, Bayer, General Electric, and Siemens Healthineers. Dr. Schoepf has received honoraria for speaking and consulting from Bayer, Guerbet, HeartFlow Inc., and Siemens Healthineers. Dr. De Cecco is a consultant for/receives institutional research support from Bayer and Siemens. Dr. Varga-Szemes receives institutional research support from Siemens Healthineers. The other authors have no conflict of interest to disclose. Workstation-based flow computations of coronary blood flow are not currently approved by the US Food and Drug Administration. A software prototype (Coronary Plaque Analysis 4.2.0 syngo.via FRONTIER, Siemens) was used for the plaque analysis. The concepts and information presented are based on research and are not commercially available.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.


• Retrospective

• Observational study

• Performed at one institution


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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Philipp L. von Knebel Doeberitz
    • 1
    • 2
  • Carlo N. De Cecco
    • 1
  • U. Joseph Schoepf
    • 1
    • 3
    • 4
    Email author
  • Taylor M. Duguay
    • 1
  • Moritz H. Albrecht
    • 1
    • 5
  • Marly van Assen
    • 1
    • 6
  • Maximilian J. Bauer
    • 1
  • Rock H. Savage
    • 1
  • J. Trent Pannell
    • 1
  • Domenico De Santis
    • 1
    • 7
  • Addison A. Johnson
    • 1
  • Akos Varga-Szemes
    • 1
  • Richard R. Bayer
    • 3
  • Stefan O. Schönberg
    • 2
  • John W. Nance
    • 1
  • Christian Tesche
    • 1
    • 8
  1. 1.Division of Cardiovascular Imaging, Department of Radiology and Radiological ScienceMedical University of South CarolinaCharlestonUSA
  2. 2.Institute of Clinical Radiology and Nuclear Medicine, University Medical Center MannheimMedical Faculty Mannheim-Heidelberg UniversityMannheimGermany
  3. 3.Division of Cardiology, Department of MedicineMedical University of South CarolinaCharlestonUSA
  4. 4.Heart & Vascular Center, Ashley River TowerMedical University of South CarolinaCharlestonUSA
  5. 5.Center for Medical Imaging North East Netherlands, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
  6. 6.Department of Diagnostic and Interventional RadiologyUniversity Hospital FrankfurtFrankfurtGermany
  7. 7.Department of Radiological Sciences, Oncology and PathologyUniversity of Rome “Sapienza”RomeItaly
  8. 8.Department of Cardiology and Intensive Care MedicineHeart Center Munich-BogenhausenMunichGermany

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