Showing papers by "Raúl A. Feijóo published in 2018"

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 (FFR1D) and 3D models (FFR3D) were performed in terms of predicted FFR value. Compared to FFR3D, FFR1D 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 FFR1D simulations can be reliably used as a surrogate of demanding FFR3D computations.

Mechanical Characterization of the Vessel Wall by Data Assimilation of Intravascular Ultrasound Studies

Abstract: Atherosclerotic plaque rupture and erosion are the most important mechanisms underlying the sudden plaque growth, responsible for acute coronary syndromes and even fatal cardiac events. Advances in the understanding of the culprit plaque structure and composition are already reported in the literature, however, there is still much work to be done toward in-vivo plaque visualization and mechanical characterization to assess plaque stability, patient risk, diagnosis and treatment prognosis. In this work, a methodology for the mechanical characterization of the vessel wall plaque and tissues is proposed based on the combination of intravascular ultrasound (IVUS) imaging processing, data assimilation and continuum mechanics models within a high performance computing (HPC) environment. Initially, the IVUS study is gated to obtain volumes of image sequences corresponding to the vessel of interest at different cardiac phases. These sequences are registered against the sequence of the end-diastolic phase to remove transversal and longitudinal rigid motions prescribed by the moving environment due to the heartbeat. Then, optical flow between the image sequences is computed to obtain the displacement fields of the vessel (each associated to a certain pressure level). The obtained displacement fields are regarded as observations within a data assimilation paradigm, which aims to estimate the material parameters of the tissues within the vessel wall. Specifically, a reduced order unscented Kalman filter is employed, endowed with a forward operator which amounts to address the solution of a hyperelastic solid mechanics model in the finite strain regime taking into account the axially stretched state of the vessel, as well as the effect of internal and external forces acting on the arterial wall. Due to the computational burden, a HPC approach is mandatory. Hence, the data assimilation and computational solid mechanics computations are parallelized at three levels: (i) a Kalman filter level; (ii) a cardiac phase level; and (iii) a mesh partitioning level. To illustrate the capabilities of this novel methodology toward the in-vivo analysis of patient-specific vessel constituents, mechanical material parameters are estimated using in-silico and in-vivo data retrieved from IVUS studies. Limitations and potentials of this approach are exposed and discussed.

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 ($\text{FFR}_{\text{1D}}$) and 3D models ($\text{FFR}_{\text{3D}}$) were performed in terms of predicted $\text{FFR}$ value. Compared to $\text{FFR}_{\text{3D}}$, $\text{FFR}_{\text{1D}}$ resulted with a difference of 0.00$\pm$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 $\text{FFR}_{\text{1D}}$ simulations can be reliably used as a surrogate of demanding $\text{FFR}_{\text{3D}}$ computations.

An efficient method for the numerical solution of blood flow in 3D bifurcated regions

Abstract: From the point of view of the potential clinical use of computational hemodynamic, it is mandatory to get the computational time of simulation each time closer to real clinical needs. Spending hours and even days to solve accurately one single cardiac cycle of the whole cardiovascular system is unfeasible on daily practice. In this sense, in this work we study the transversally enriched pipe element method (TEPEM) as an effective alternative to solve the Navier-Stokes equations in bifurcated domains with enough accuracy to provide clinically relevant information but at a significantly reduced time.

Coronary Flow Estimation for the Computational Assessment of Fractional Flow Reserve

Abstract: Nowadays, fractional flow reserve (FFR) is considered the gold standard technique to assess risk of myocardial ischemia in the presence of coronary artery disease. Moreover, FFR is an invasive procedure, which requires specialized cardiologist and dedicated medical instrumentation, i.e. it is far from being risk free and it is expensive. In this context, a tool to estimate FFR from computational fluid dynamics non-invasively could impact positively the patient experience, reducing economic costs and providing a new diagnostic tool for physicians. Although there are some studies proposing computational solutions for the estimation of FFR, they generally lack of sensitivity analysis of the hemodynamics parameters. In this work we are interested in assessing the effect of coronary flow reserve (CFR) in the outcomes of the numerical simulations of coronary blood flow. To this end we make use of a set of 24 coronary computed tomography angiography (CCTA) images from which the arterial network is segmented and utilized to perform blood flow simulations. The blood circulation is modeled using lumped mathematical representations in a steady state regime, with geometrical features retrieved from the CCTA images. At least one measurement of fractional flow reserve (FFR) is available for each patient, totaling 35 measurements. Some hemodynamic parameters for the simulations were found to be patient specific while others are calibrated with a single general value for all patients. The study focuses on the estimation of CFR that minimizes the difference between the in-vivo FFR measurements and the computational estimations. This strategy may shed light on the underlying mechanisms ruling territorial myocardial resistance.