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Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve.

ABSTRACT: In this work we propose to validate the predictive capabilities of one-dimensional (1D) blood flow models with full three-dimensional (3D) models in the context of patient-specific coronary hemodynamics in hyperemic conditions. Such conditions mimic the state of coronary circulation during the acquisition of the Fractional Flow Reserve (FFR) index. Demonstrating that 1D models accurately reproduce FFR estimates obtained with 3D models has implications in the approach to computationally estimate FFR. To this end, a sample of 20 patients was employed from which 29 3D geometries of arterial trees were constructed, 9 obtained from coronary computed tomography angiography (CCTA) and 20 from intra-vascular ultrasound (IVUS). For each 3D arterial model, a 1D counterpart was generated. The same outflow and inlet pressure boundary conditions were applied to both (3D and 1D) models. In the 1D setting, pressure losses at stenoses and bifurcations were accounted for through specific lumped models. Comparisons between 1D models (FFR_1D) and 3D models (FFR_3D) were performed in terms of predicted FFR value. Compared to FFR_3D, FFR_1D resulted with a difference of 0.00?±?0.03 and overall predictive capability AUC, Acc, Spe, Sen, PPV and NPV of 0.97, 0.98, 0.90, 0.99, 0.82, and 0.99, with an FFR threshold of 0.8. We conclude that inexpensive FFR_1D simulations can be reliably used as a surrogate of demanding FFR_3D computations.

SUBMITTER: Blanco PJ

PROVIDER: S-EPMC6250665 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve.

Blanco P J PJ Bulant C A CA Müller L O LO Talou G D Maso GDM Bezerra C Guedes CG Lemos P A PA Feijóo R A RA

Scientific reports 20181122 1

In this work we propose to validate the predictive capabilities of one-dimensional (1D) blood flow models with full three-dimensional (3D) models in the context of patient-specific coronary hemodynamics in hyperemic conditions. Such conditions mimic the state of coronary circulation during the acquisition of the Fractional Flow Reserve (FFR) index. Demonstrating that 1D models accurately reproduce FFR estimates obtained with 3D models has implications in the approach to computationally estimate ...[more]

PMID: 30467321

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Project description:BackgroundUntil recently, Russia did not utilize noninvasive fractional flow reserve (FFR) assessment. We developed an automated algorithm for noninvasive assessment of FFR based on a one-dimensional (1D) mathematical modeling.ObjectiveThe research aims to evaluate the diagnostic accuracy of this algorithm.MethodsThe study enrolled 80 patients: 16 of them underwent 64-slice computed tomography - included retrospectively, 64 - prospectively, with a 640-slice CT scan. Specialists processed CT images and evaluated noninvasive FFR. Ischemia was confirmed if FFR < 0.80 and disproved if FFR ≥ 0.80. The prospective group of patients was hospitalized for invasive FFR assessment as a reference standard. If ischemic, patients underwent stent implantation. In the retrospective group, patients already had invasive FFR values.Statistical analysis was performed using GraphPad Prism 8. We compared two methods using a Bland-Altman plot and per-vessel ROC curve analysis. Considering the abnormality of distribution by the Kolmogorov-Smirnov test, we have used Spearman's rank correlation coefficient.ResultsDuring data processing, three patients of the retrospective and 46 patients of the prospective group were excluded. The sensitivity of our method was 66.67% (95% CI: 46.71-82.03); the specificity was 78.95% (95% CI: 56.67-91.49), p = 0.0052, in the per-vessel analysis. In per-patient analysis, the sensitivity was 69.57% (95% CI: 49.13-84.40); the specificity was 87.50% (95% CI: 52.91-99.36), p = 0.0109. The area under the ROC curve in the per-vessel analysis was 77.52% (95% CI: 66.97-88.08), p < 0.0001.ConclusionThe obtained indices of sensitivity, specificity, PPV, and NPV are, in general, comparable to those in other studies. Moreover, the noninvasive values of FFR yielded a high correlation coefficient with the invasive values. However, the AUC was not high enough, 77.52 (95% CI: 66.97-88.08), p < 0.0001. The discrepancy is probably attributed to the initial data heterogeneity and low statistical power.

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Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve.

Publications

Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve.

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