Combined Coronary CT-angiography And TAVI-planning For Ruling-out Significant Coronary Artery Disease: Added Value Of Machine-Learning Based CT-FFR

Gohmann, Robin F.; Pawelka, K.; Seitz, Patrick; Majunke, Nicolas; Desch, Steffen; Lauten, Philipp; Holzhey, David; Noak, T.; Kiefer, Philipp; Krieghoff, Christian; Gottschling, Sebastian; Lücke, Christian; Wilde, Johannes; Ebel, Sebastian; Borger, M.A.; Thiele, H; Abdel‐Wahab, Mohamed; Gutberlet, Mathias

doi:10.1016/j.jcct.2021.06.202

Cited by 3 publications

(5 citation statements)

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“…However, its specificity and positive predictive value are somewhat limited, and its diagnostic accuracy decreases with increasing plaque burden as frequently encountered in elderly patients [ 29 ], including patients prior to TAVI. Though CT-FFR has been shown to increase specificity and diagnostic accuracy also in this patient group when applied for specific lesions [ 18 , 19 ], interpreting cCTA and deciding between obstructive and non-obstructive CAD in patients with higher plaque burden may be challenging and requires experience. Therefore, it would be most convenient if CT-FFR could not only guide the semiquantitative interpretation of cCTA [ 20 ] but rather render a discrete value indicative of hemodynamically relevant CAD, thus making the more subjective morphological interpretation unnecessary.…”

Section: Discussionmentioning

confidence: 99%

“…Image quality was assessed quantitatively and qualitatively as previously described [ 8 , 18 ]. Quantitatively, image quality was described as contrast opacification in the aortic sinus in Hounsfield units (HU) and as contrast to noise ratio (CNR)

.…”

Section: Methodsmentioning

confidence: 99%

“…Particularly, an elevated coronary artery calcium score (CAC) is likely to be a major contributing factor, being responsible for the high false positive rate and relatively low specificity of cCTA in this cohort [ 17 ]. CT-derived fractional flow reserve (CT-FFR) may increase the specificity and diagnostic accuracy, and has been described to do so also in patients prior to TAVI [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

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

Gohmann

Seitz

Pawelka

et al. 2022

JCM

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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.

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Section: Discussionmentioning

confidence: 99%

.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Gohmann

Seitz

Pawelka

et al. 2022

JCM

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“…Using invasive FFR as the reference standard, the AUC of CT-FFR in patients with severe aortic stenosis was 0.83, higher than CCTA and ICA. 115 Gohmann et al 81 showed that CT-FFR effectively excluded coronary heart disease in 44% (202/460) TAVR patients, thereby reducing ICA rates in older patients.…”

Section: Ct-ffr In Other Coronary-related Diseasementioning

confidence: 99%

“…The diagnostic performance of CT-FFR on bifurcation, severe tortuosity, tandem lesions, extensive diffuse lesions, microvascular disease, ostial stenosis, and heavy calcification have also not been fully evaluated (Table 1). 18–20,23,24,26,28,29,53–58,66–89…”

Section: Indications Of Ct-ffrmentioning

confidence: 99%

Coronary Computed Tomography Angiography–derived Fractional Flow Reserve

Zhang

Tang

et al. 2022

Journal of Thoracic Imaging

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Invasive fractional flow reserve (FFR) measured by a pressure wire is a reference standard for evaluating functional stenosis in coronary artery disease. Coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) uses advanced computational analysis methods to noninvasively obtain FFR results from a single conventional coronary computed tomography angiography data to evaluate the hemodynamic significance of coronary artery disease. More and more evidence has found good correlation between the results of noninvasive CT-FFR and invasive FFR. CT-FFR has proven its potential in optimizing patient management, improving risk stratification and prognosis, and reducing total health care costs. However, there is still a lack of standardized interpretation of CT-FFR technology in real-world clinical settings. This expert consensus introduces the principle, workflow, and interpretation of CT-FFR; summarizes the stateof-the-art application of CT-FFR; and provides suggestions and recommendations for the application of CT-FFR with the aim of promoting the standardized application of CT-FFR in clinical practice.

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Impact of machine-learning-based coronary computed tomography angiography–derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

et al. 2022

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Combined Coronary CT-angiography And TAVI-planning For Ruling-out Significant Coronary Artery Disease: Added Value Of Machine-Learning Based CT-FFR

Cited by 3 publications

References 0 publications

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

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

Coronary Computed Tomography Angiography–derived Fractional Flow Reserve

Impact of machine-learning-based coronary computed tomography angiography–derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

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