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Article

Combined Coronary CT-Angiography and TAVI Planning: Utility of CT-FFR in Patients with Morphologically Ruled-Out Obstructive Coronary Artery Disease

1
Department of Diagnostic and Interventional Radiology, Heart Center Leipzig at University of Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany
2
Medical Faculty, University of Leipzig, Liebigstr. 27, 04103 Leipzig, Germany
3
Department of Cardiology, Heart Center Leipzig at University of Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany
4
Department of Cardiac Surgery, Heart Center Leipzig at University of Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany
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Leipzig Heart Institute, Russenstr. 69a, 04289 Leipzig, Germany
6
Siemens Healthcare GmbH, Henkestr. 127, 91052 Erlangen, Germany
7
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Academic Editor: Dinesh K. Kalra
J. Clin. Med. 2022, 11(5), 1331; https://doi.org/10.3390/jcm11051331
Received: 9 January 2022 / Revised: 15 February 2022 / Accepted: 21 February 2022 / Published: 28 February 2022
(This article belongs to the Section Nuclear Medicine & Radiology)
Background: Coronary artery disease (CAD) is a frequent comorbidity in patients undergoing transcatheter aortic valve implantation (TAVI). If significant CAD can be excluded on coronary CT-angiography (cCTA), invasive coronary angiography (ICA) may be avoided. However, a high plaque burden may make the exclusion of CAD challenging, particularly for less experienced readers. The objective was to analyze the ability of machine learning (ML)-based CT-derived fractional flow reserve (CT-FFR) to correctly categorize cCTA studies without obstructive CAD acquired during pre-TAVI evaluation and to correlate recategorization to image quality and coronary artery calcium score (CAC). Methods: In total, 116 patients without significant stenosis (≥50% diameter) on cCTA as part of pre-TAVI CT were included. Patients were examined with an electrocardiogram-gated CT scan of the heart and high-pitch scan of the torso. Patients were re-evaluated with ML-based CT-FFR (threshold = 0.80). The standard of reference was ICA. Image quality was assessed quantitatively and qualitatively. Results: ML-based CT-FFR was successfully performed in 94.0% (109/116) of patients, including 436 vessels. With CT-FFR, 76/109 patients and 126/436 vessels were falsely categorized as having significant CAD. With CT-FFR 2/2 patients but no vessels initially falsely classified by cCTA were correctly recategorized as having significant CAD. Reclassification occurred predominantly in distal segments. Virtually no correlation was found between image quality or CAC. Conclusions: Unselectively applied, CT-FFR may vastly increase the number of false positive ratings of CAD compared to morphological scoring. Recategorization was virtually independently from image quality or CAC and occurred predominantly in distal segments. It is unclear whether or not the reduced CT-FFR represent true pressure ratios and potentially signifies pathophysiology in patients with severe aortic stenosis. View Full-Text
Keywords: aortic stenosis; computed tomography coronary angiography; coronary angiography; coronary artery disease; transcatheter aortic valve implantation; diagnostic accuracy; machine learning aortic stenosis; computed tomography coronary angiography; coronary angiography; coronary artery disease; transcatheter aortic valve implantation; diagnostic accuracy; machine learning
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MDPI and ACS Style

Gohmann, R.F.; Seitz, P.; Pawelka, K.; Majunke, N.; Schug, A.; Heiser, L.; Renatus, K.; Desch, S.; Lauten, P.; Holzhey, D.; Noack, T.; Wilde, J.; Kiefer, P.; Krieghoff, C.; Lücke, C.; Ebel, S.; Gottschling, S.; Borger, M.A.; Thiele, H.; Panknin, C.; Abdel-Wahab, M.; Horn, M.; Gutberlet, M. Combined Coronary CT-Angiography and TAVI Planning: Utility of CT-FFR in Patients with Morphologically Ruled-Out Obstructive Coronary Artery Disease. J. Clin. Med. 2022, 11, 1331. https://doi.org/10.3390/jcm11051331

AMA Style

Gohmann RF, Seitz P, Pawelka K, Majunke N, Schug A, Heiser L, Renatus K, Desch S, Lauten P, Holzhey D, Noack T, Wilde J, Kiefer P, Krieghoff C, Lücke C, Ebel S, Gottschling S, Borger MA, Thiele H, Panknin C, Abdel-Wahab M, Horn M, Gutberlet M. Combined Coronary CT-Angiography and TAVI Planning: Utility of CT-FFR in Patients with Morphologically Ruled-Out Obstructive Coronary Artery Disease. Journal of Clinical Medicine. 2022; 11(5):1331. https://doi.org/10.3390/jcm11051331

Chicago/Turabian Style

Gohmann, Robin Fabian, Patrick Seitz, Konrad Pawelka, Nicolas Majunke, Adrian Schug, Linda Heiser, Katharina Renatus, Steffen Desch, Philipp Lauten, David Holzhey, Thilo Noack, Johannes Wilde, Philipp Kiefer, Christian Krieghoff, Christian Lücke, Sebastian Ebel, Sebastian Gottschling, Michael A. Borger, Holger Thiele, Christoph Panknin, Mohamed Abdel-Wahab, Matthias Horn, and Matthias Gutberlet. 2022. "Combined Coronary CT-Angiography and TAVI Planning: Utility of CT-FFR in Patients with Morphologically Ruled-Out Obstructive Coronary Artery Disease" Journal of Clinical Medicine 11, no. 5: 1331. https://doi.org/10.3390/jcm11051331

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