Christophe Chnafa

Image-based patient-specific simulation: a computational modelling of the human left heart haemodynamics.

The demand for early diagnosis of heart disease and more generally for a better quantitative knowledge of the heart flow dynamics is a continuous source of motivation for the development of non-inv...

On the quantification and visualization of transient periodic instabilities in pulsatile flows

Turbulent-like flows without cycle-to-cycle variations are more frequently being reported in studies of cardiovascular flows. The associated stimuli might be of mechanobiological relevance, but how to quantify them objectively is not obvious. Classical Reynolds decomposition, where the flow is separated into mean and fluctuating velocity components, is not applicable as the phase-average is zero. We therefore expanded on established techniques and present the idea, analogous to Reynolds decomposition, to decompose a flow with transient instabilities into low- versus high frequency components, respectively, to discriminate flow instabilities from the underlying cardiac pulsatility. Transient wall shear stress and velocity signals derived from computational fluid dynamic simulations were transferred to the frequency domain. A high-pass filter was applied to subtract the 99% most-energy-containing frequencies, which gave a cut-off frequency of 25Hz. We introduce here the spectral power index, and compute the fluctuating kinetic energy, based on the high-pass filtered velocity components, both being frequency-based operators. The efficacy was evaluated in an aneurysm model for multiple flow rates demonstrating transition to turbulent-like flows. The frequency-based operators were found to better correlate with the qualitatively observed flow instabilities compared to conventional descriptors, like time-averaged wall shear stress or oscillatory shear index. We demonstrate how the high frequencies beyond the physiological range could be analyzed and/or transferred back to the time domain for quantification and visualization purposes. We have introduced general frequency-based operators, easily extendable to other cardiovascular territories based on a posteriori heuristic filtering that allows for separation, isolation, and quantification of cycle-invariant turbulent-like flows.

Improved reduced-order modelling of cerebrovascular flow distribution by accounting for arterial bifurcation pressure drops

Reduced-order modelling offers the possibility to study global flow features in cardiovascular networks. In order to validate these models, previous studies have been conducted in which they compared 3D computational fluid dynamics simulations with reduced-order simulations. Discrepancies have been reported between the two methods. The loss of energy at the bifurcations is usually neglected and has been pointed out as a possible explanation for these discrepancies. We present distributed lumped models of cerebrovasculatures created automatically from 70 cerebrovascular networks segmented from 3D angiograms. The outflow rate repartitions predicted with and without modelling the energy loss at the bifurcations are compared against 3D simulations. When neglecting the energy loss at the bifurcations, the flow rates though the anterior cerebral arteries are overestimated by 4.7±6.8% (error relative to the inlet flow rate, mean ± standard deviation), impacting the remaining volume of flow going to the other vessels. When the energy loss is modelled, this error is dropping to 0.1±3.2%. Overall, over the total of 337 outlet vessels, when the energy losses at the bifurcations are not modelled the 95% of agreement is in the range of ±13.5% and is down to ±6.5% when the energy losses are considered. With minimal input and computational resources, the presented method can estimate the outflow rates reliably. This study constitutes the largest validation of a reduced-order flow model against 3D simulations. The impact of the energy loss at the bifurcations is here demonstrated for cerebrovasculatures but can be applied to other physiological networks.

Better Than Nothing: A Rational Approach for Minimizing the Impact of Outflow Strategy on Cerebrovascular Simulations

BACKGROUND AND PURPOSE: Computational fluid dynamics simulations of neurovascular diseases are impacted by various modeling assumptions and uncertainties, including outlet boundary conditions. Many studies of intracranial aneurysms, for example, assume zero pressure at all outlets, often the default (“do-nothing”) strategy, with no physiological basis. Others divide outflow according to the outlet diameters cubed, nominally based on the more physiological Murrays law but still susceptible to subjective choices about the segmented model extent. Here we demonstrate the limitations and impact of these outflow strategies, against a novel “splitting” method introduced here. MATERIALS AND METHODS: With our method, the segmented lumen is split into its constituent bifurcations, where flow divisions are estimated locally using a power law. Together these provide the global outflow rate boundary conditions. The impact of outflow strategy on flow rates was tested for 70 cases of MCA aneurysm with 0D simulations. The impact on hemodynamic indices used for rupture status assessment was tested for 10 cases with 3D simulations. RESULTS: Differences in flow rates among the various strategies were up to 70%, with a non-negligible impact on average and oscillatory wall shear stresses in some cases. Murray-law and splitting methods gave flow rates closest to physiological values reported in the literature; however, only the splitting method was insensitive to arbitrary truncation of the model extent. CONCLUSIONS: Cerebrovascular simulations can depend strongly on the outflow strategy. The default zero-pressure method should be avoided in favor of Murray-law or splitting methods, the latter being released as an open-source tool to encourage the standardization of outflow strategies.

3D phase contrast MRI: Partial volume correction for robust blood flow quantification in small intracranial vessels

Recent advances in 3D‐PCMRI (phase contrast MRI) sequences allow for measuring the complex hemodynamics in cerebral arteries. However, the small size of these vessels vs spatial resolution can lead to non‐negligible partial volume artifacts, which must be taken into account when computing blood flow rates. For this purpose, we combined the velocity information provided by 3D‐PCMRI with vessel geometry measured with 3DTOF (time of flight MRI) or 3DRA (3D rotational angiography) to correct the partial volume effects in flow rate assessments.

Using Image-based CFD to Investigate the Intracardiac Turbulence

A numerical framework designed to compute the blood flow in patient-specific human hearts is presented. The geometry of the heart cavities and associated wall motion are extracted from 4D medical images while the valves of the heart are accounted for thanks to low order geometrical models. The resulting blood flow equations are solved using a fourth-order low-dissipative finite-volume scheme and a mixed Aribtrary Lagrangian-Eulerian / Immersed Boundary framework. On top of retrieving the main fluid flow phenomena commonly observed in the left heart, the methodology allows studying the heart flow dynamics, including the turbulence characteristics and cycle-to-cycle variations.

Large-Eddy Simulation of Turbulence in Cardiovascular Flows

A 4th-order accurate, low dissipative flow solver is used to perform Large-Eddy Simulations of three typical hemodynamic situations: the flow through the idealized medical device proposed by the American Food and Drug Administration; the intracardiac flow within an actual human left heart whose morphology and deformations are deduced from medical imaging; the flow downstream of an artificial aortic valve which arises from the blood-leaflets interaction problem. In all the cases, the \({\varvec{\sigma }}\) subgrid scale model designed to handle wall-bounded transitional flows is successfully used and the numerical simulations compare favourably with the experimental data available. These results illustrate the potential of the Large-Eddy Simulation methodology to properly handle blood flows. They also support the idea that turbulence, even if not fully developed, may be present in cardiovascular flows, including under non pathological conditions.

Towards the Clinical utility of CFD for assessment of intracranial aneurysm rupture – a systematic review and novel parameter-ranking tool

Background Intracranial aneurysms (IAs) are vascular dilations on cerebral vessels that affect between 1%–5% of the general population, and can cause life-threatening intracranial hemorrhage when ruptured. Computational fluid dynamics (CFD) has emerged as a promising tool to study IAs in recent years, particularly for rupture risk assessment. However, despite dozens of studies, CFD is still far from clinical use due to large variations and frequent contradictions in hemodynamic results between studies. Purpose To identify key gaps in the field of CFD for the study of IA rupture, and to devise a novel tool to rank parameters based on potential clinical utility. Methods A Pubmed search identified 231 CFD studies for IAs. Forty-six studies fit our inclusion criteria, with a total of 2791 aneurysms. For included studies, study type, boundary conditions, solver resolutions, parameter definitions, geometric and hemodynamic parameters used, and results found were recorded. Data synthesis Aspect ratio, aneurysm size, low wall shear stress area, average wall shear stress, and size ratio were the parameters that correlate most strongly with IA rupture. Limitations Significant differences in parameter definitions, solver spatial and temporal resolutions, number of cycles between studies as well as frequently missing information such as inlet flow rates were identified. A greater emphasis on prospective studies is also needed. Conclusions Our recommendations will help increase standardization and bridge the gaps in the CFD community, and expedite the process of making CFD clinically useful in guiding the treatment of IAs.

Errors in power-law estimations of inflow rates for intracranial aneurysm CFD

Patient-specific inflow rates are rarely available for computational fluid dynamics (CFD) studies of intracranial aneurysms. Instead, inflow rates are often estimated from parent artery diameters via power laws, i.e. Q ∝ Dn, reflecting adaptation of conduit arteries to demanded flow. The present study aimed to validate the accuracy of these power laws. Internal carotid artery (ICA) flow rates were measured from 25 ICA aneurysm patients via 2D phase contrast MRI. ICA diameters, derived from 3D segmentation of rotational angiograms, were used to estimate inflow rates via power laws from the aneurysm CFD literature assuming the same inlet wall shear stress (WSS) (n = 3), velocity (n = 2) or flow rate (n = 0) for all cases. To illustrate the potential impact of errors in flow rate estimates, pulsatile CFD was carried out for four cases having large errors for at least one power law. Flow rates estimated by n = 3 and n = 0 power laws had significant (p < 0.01) mean biases of -22% to +32%, respectively, but with individual errors ranging from -78% to +120%. The n = 2 power law had no significant bias, but had non-negligible individual errors of -58% to +71%. CFD showed similarly large errors for time-averaged sac WSS; however, these were reduced after normalizing by parent artery WSS. High frequency WSS fluctuations, evident in 2/4 aneurysms, were also sensitive to inflow rate errors. Care should therefore be exercised in the interpretation of aneurysm CFD studies that rely on power law estimates of inflow rates, especially if absolute (vs. normalized) WSS, or WSS instabilities, are of interest.

A doppler-based regularization problem for intraventricular vector flow mapping

Recent studies suggest that the analysis of the intracardiac blood flow dynamics via vector imaging can provide relevant evaluation of cardiac dysfunction. In particular, the clinical importance of intraventricular vortex formation has been underlined. Cardiac magnetic resonance and contrast-enhanced ultrasound are commonly used. These approaches, however, cannot be integrated into routine clinical practice. For the purpose of offering robust and clinically-compatible intraventricular vector flow mapping (iVFM), we generalized the Doppler-based algorithm proposed in [10.1109/TMI.2010.2049656] by using a regularized least-squares method with automatic selection of the regularizing parameters.