scholarly journals Influence of reconstruction kernels on the accuracy of CT-derived fractional flow reserve

2021 ◽  
Author(s):  
Fabian Ammon ◽  
Maximilian Moshage ◽  
Silvia Smolka ◽  
Markus Goeller ◽  
Daniel O. Bittner ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Diagnostic Accuracy ◽  
Fractional Flow Reserve ◽  
Invasive Coronary Angiography ◽  
Reconstruction Algorithm ◽  
Fractional Flow ◽  
Roc Curve Analysis ◽  
Flow Reserve ◽  
Smooth Kernel ◽  
Reconstruction Kernel

Abstract Objectives We 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. Methods Sixty-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. Results One 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%). Conclusion Compared 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).

scholarly journals Non-invasive imaging software to assess the functional significance of coronary stenoses: a systematic review and economic evaluation

2021 ◽  
Vol 25 (56) ◽  
pp. 1-230
Author(s):  
Ana Duarte ◽  
Alexis Llewellyn ◽  
Ruth Walker ◽  
Laetitia Schmitt ◽  
Kath Wright ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Diagnostic Accuracy ◽  
Fractional Flow Reserve ◽  
Invasive Coronary Angiography ◽  
Clinical Effectiveness ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Background QAngio® XA 3D/QFR® (three-dimensional/quantitative flow ratio) imaging software (Medis Medical Imaging Systems BV, Leiden, the Netherlands) and CAAS® vFFR® (vessel fractional flow reserve) imaging software (Pie Medical Imaging BV, Maastricht, the Netherlands) are non-invasive technologies to assess the functional significance of coronary stenoses, which can be alternatives to invasive fractional flow reserve assessment. Objectives The objectives were to determine the clinical effectiveness and cost-effectiveness of QAngio XA 3D/QFR and CAAS vFFR. Methods We performed a systematic review of all evidence on QAngio XA 3D/QFR and CAAS vFFR, including diagnostic accuracy, clinical effectiveness, implementation and economic analyses. We searched MEDLINE and other databases to January 2020 for studies where either technology was used and compared with fractional flow reserve in patients with intermediate stenosis. The risk of bias was assessed with quality assessment of diagnostic accuracy studies. Meta-analyses of diagnostic accuracy were performed. Clinical and implementation outcomes were synthesised narratively. A simulation study investigated the clinical impact of using QAngio XA 3D/QFR. We developed a de novo decision-analytic model to estimate the cost-effectiveness of QAngio XA 3D/QFR and CAAS vFFR relative to invasive fractional flow reserve or invasive coronary angiography alone. Scenario analyses were undertaken to explore the robustness of the results to variation in the sources of data used to populate the model and alternative assumptions. Results Thirty-nine studies (5440 patients) of QAngio XA 3D/QFR and three studies (500 patients) of CAAS vFFR were included. QAngio XA 3D/QFR had good diagnostic accuracy to predict functionally significant fractional flow reserve (≤ 0.80 cut-off point); contrast-flow quantitative flow ratio had a sensitivity of 85% (95% confidence interval 78% to 90%) and a specificity of 91% (95% confidence interval 85% to 95%). A total of 95% of quantitative flow ratio measurements were within 0.14 of the fractional flow reserve. Data on the diagnostic accuracy of CAAS vFFR were limited and a full meta-analysis was not feasible. There were very few data on clinical and implementation outcomes. The simulation found that quantitative flow ratio slightly increased the revascularisation rate when compared with fractional flow reserve, from 40.2% to 42.0%. Quantitative flow ratio and fractional flow reserve resulted in similar numbers of subsequent coronary events. The base-case cost-effectiveness results showed that the test strategy with the highest net benefit was invasive coronary angiography with confirmatory fractional flow reserve. The next best strategies were QAngio XA 3D/QFR and CAAS vFFR (without fractional flow reserve). However, the difference in net benefit between this best strategy and the next best was small, ranging from 0.007 to 0.012 quality-adjusted life-years (or equivalently £140–240) per patient diagnosed at a cost-effectiveness threshold of £20,000 per quality-adjusted life-year. Limitations Diagnostic accuracy evidence on CAAS vFFR, and evidence on the clinical impact of QAngio XA 3D/QFR, were limited. Conclusions Quantitative flow ratio as measured by QAngio XA 3D/QFR has good agreement and diagnostic accuracy compared with fractional flow reserve and is preferable to standard invasive coronary angiography alone. It appears to have very similar cost-effectiveness to fractional flow reserve and, therefore, pending further evidence on general clinical benefits and specific subgroups, could be a reasonable alternative. The clinical effectiveness and cost-effectiveness of CAAS vFFR are uncertain. Randomised controlled trial evidence evaluating the effect of quantitative flow ratio on clinical and patient-centred outcomes is needed. Future work Studies are required to assess the diagnostic accuracy and clinical feasibility of CAAS vFFR. Large ongoing randomised trials will hopefully inform the clinical value of QAngio XA 3D/QFR. Study registration This study is registered as PROSPERO CRD42019154575. Funding This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 25, No. 56. See the NIHR Journals Library website for further project information.

Referral of patients for fractional flow reserve using quantitative flow ratio

2018 ◽  
Vol 20 (11) ◽  
pp. 1231-1238 ◽  
Author(s):  
Jeff M Smit ◽  
Gerhard Koning ◽  
Alexander R van Rosendael ◽  
Mohammed El Mahdiui ◽  
Bart J Mertens ◽  
...  
Keyword(s):  
Coronary Angiography ◽  
Fractional Flow Reserve ◽  
Invasive Coronary Angiography ◽  
Quantitative Coronary Angiography ◽  
Coronary Intervention ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Abstract Aims Quantitative flow ratio (QFR) is a recently developed technique to calculate fractional flow reserve (FFR) based on 3D quantitative coronary angiography and computational fluid dynamics, obviating the need for a pressure-wire and hyperaemia induction. QFR might be used to guide patient selection for FFR and subsequent percutaneous coronary intervention (PCI) referral in hospitals not capable to perform FFR and PCI. We aimed to investigate the feasibility to use QFR to appropriately select patients for FFR referral. Methods and results Patients who underwent invasive coronary angiography in a hospital where FFR and PCI could not be performed and were referred to our hospital for invasive FFR measurement, were included. Angiogram images from the referring hospitals were retrospectively collected for QFR analysis. Based on QFR cut-off values of 0.77 and 0.86, our patient cohort was reclassified to ‘no referral’ (QFR ≥0.86), referral for ‘FFR’ (QFR 0.78–0.85), or ‘direct PCI’ (QFR ≤0.77). In total, 290 patients were included. Overall accuracy of QFR to detect an invasive FFR of ≤0.80 was 86%. Based on a QFR cut-off value of 0.86, a 50% reduction in patient referral for FFR could be obtained, while only 5% of these patients had an invasive FFR of ≤0.80 (thus, these patients were incorrectly reclassified to the ‘no referral’ group). Furthermore, 22% of the patients that still need to be referred could undergo direct PCI, based on a QFR cut-off value of 0.77. Conclusion QFR is feasible to use for the selection of patients for FFR referral.

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