Abstract
ObjectivesWe evaluated the influence of image reconstruction kernels on the diagnostic accuracy of CT-derived fractional flow reserve (FFRCT) compared to invasive FFR in patients with coronary artery disease.MethodsSixty-nine patients, in whom coronary CT angiography was performed and who were further referred for invasive coronary angiography with FFR measurement via pressure wire, were retrospectively included. CT data sets were acquired using a third-generation dual-source CT system and rendered with medium smooth (Bv40) and sharp (Bv49) reconstruction kernels. FFRCT was calculated on-site using prototype software. Coronary stenoses with invasive FFR ≤ 0.80 were classified as significant. Agreement between FFRCT and invasive FFR was determined for both reconstruction kernels.ResultsOne hundred analyzed vessels in 69 patients were included. Twenty-five vessels were significantly stenosed according to invasive FFR. Using a sharp reconstruction kernel for FFRCT resulted in a significantly higher correlation with invasive FFR (r = 0.74, p < 0.01 vs. r = 0.58, p < 0.01; p = 0.04) and a higher AUC in ROC curve analysis to correctly identify/exclude significant stenosis (AUC = 0.92 vs. AUC = 0.82 for sharp vs. medium smooth kernel, respectively, p = 0.02). A FFRCT value of ≤ 0.8 using a sharp reconstruction kernel showed a sensitivity of 88% and a specificity of 92% for detecting ischemia-causing lesions, resulting in a diagnostic accuracy of 91%. The medium smooth reconstruction kernel performed worse (sensitivity 60%, specificity 89%, accuracy 82%).ConclusionCompared to invasively measured FFR, FFRCT using a sharp image reconstruction kernel shows higher diagnostic accuracy for detecting lesions causing ischemia, potentially altering decision-making in a clinical setting.Key Points• Image reconstruction parameters influence the diagnostic accuracy of simulated fractional flow reserve derived from coronary computed tomography angiography.• Using a sharp kernel image reconstruction algorithm delivers higher diagnostic accuracy compared to medium smooth kernel image reconstruction (gold standard invasive fractional flow reserve).
Highlights
Coronary computed tomography (CT) is an established anatomic imaging modality for exclusion and detection of coronary artery stenoses; it carries a “class I” indication for the workup of coronary artery disease (CAD) in specific patient populations
Out of 72 patients screened for inclusion in this analysis, 3 patients had to be excluded because of insufficient image quality of coronary computed tomography angiography (cCTA) for the calculation of FFRCT and one patient due to technical reasons with F FRCT measurement
To the best of our knowledge, this is the first study to evaluate the influence of the image reconstruction kernel on FFRCT values
Summary
Coronary computed tomography (CT) is an established anatomic imaging modality for exclusion and detection of coronary artery stenoses; it carries a “class I” indication for the workup of coronary artery disease (CAD) in specific patient populations. Assessment of the physiologic relevance of coronary stenoses based on anatomy remains difficult and ischemia testing for guiding revascularization decisions is recommended. In the absence of sufficient information from previous stress testing, the hemodynamic significance of coronary stenoses can be assessed with invasive fractional flow reserve (FFR). With the help of computational fluid dynamics, noninvasive FFR values are generated from coronary computed tomography angiography (cCTA) data sets (CT-derived FFR, FFRCT) and add hemodynamic information to pure anatomic images [6]. Compared to invasive FFR, the diagnostic accuracy of FFRCT for detecting ischemia-causing coronary lesions could be shown to be better than cCTA alone [7,8,9]. Minimizing artifacts and the use of nitroglycerin and beta blocker are key factors for achieving a high diagnostic accuracy of FFRCT [7,8,9]
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