A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

Abstract

We present a novel, cost-efficient methodology to simulate aortic haemodynamics in a patient-specific, compliant aorta using an MRI data fusion process. Based on a previously-developed Moving Boundary Method, this technique circumvents the high computational cost and numerous structural modelling assumptions required by traditional Fluid-Structure Interaction techniques. Without the need for Computed Tomography (CT) data, the MRI images required to construct the simulation can be obtained during a single imaging session. Black Blood MR Angiography and 2D Cine-MRI data were used to reconstruct the luminal geometry and calibrate wall movement specifically to each region of the aorta. 4D-Flow MRI and non-invasive pressure measurements informed patient-specific inlet and outlet boundary conditions. Simulated wall movement closely matched 2D Cine-MRI measurements throughout the aorta, and physiological pressure and flow distributions in CFD were achieved within 3.3% of patient-specific targets. Excellent agreement with 4D-Flow MRI velocity data was observed. Conversely, a rigid-wall simulation under-predicted peak flow rate and systolic maximum velocities whilst predicting a mean Time-Averaged Wall Shear Stress (TAWSS) 13% higher than the compliant simulation. The excellent agreement observed between compliant simulation results and MRI is testament to the accuracy and efficiency of this MRI-based technique.

The influence of minor aortic branches in Type-B Aortic Dissection: patient-specific flow simulations informed by 4D-Flow MRI

“…These differences exceed the reported magnitude of other modelling assumptions such as wall compliance 27 and suggest that modelling minor branch flow loss may be a vital consideration for simulation accuracy.…”

“…With target inlet pressure and mean outlet flow rates determined, WK3 parameters were tuned via a lumped parameter model of the aorta using our previously developed technique 27,5 .…”

“…The three-dimensional Navier-Stokes equations were solved numerically using the finitevolume solver ANSYS CFX 2020 R2. Walls were assumed to be rigid, both for computational efficiency and due to a lack of Cine-MRI data to tune patient-specific aortic compliance with our existing techniques 5,27 .…”

The Impact of 4D-Flow MRI Spatial Resolution on Patient-Specific CFD Simulations of the Thoracic Aorta

“…By combining 4D-Flow MRI and CFD techniques it is possible to run patient-specific simulations that have the potential to aid treatment planning, disease progression and further the understanding of the haemodynamics due to its predictive capabilities [19][20][21] . Patient-specific CFD simulations employ geometry and boundary conditions that are determined from 4D-Flow MRI data.…”

Accelerated sequences of 4D flow MRI using GRAPPA and compressed sensing: A comparison against conventional MRI and computational fluid dynamics

“…[19][20][21][22] This approach bypasses the experimental limitations inherent to MRI acquisitions, such as spatiotemporal resolution or noise, while satisfying the fluid mechanics laws. CFD coupled to MRI has already proven capable of providing the flow fields with high fidelity under well-controlled in vitro conditions, 23,24 whereas moderate correlations have been reported for patient-specific MRI-based simulations 25,26 or superresolution of 4D flow MRI using CFD 27 for velocity and flow rates. Indeed, the choice of the CFD strategy is crucial to accurately predict the hemodynamics, particularly in such flow regimes where boundary conditions 28 and turbulence models, 29,30 as well as numerical schemes, 31 have shown to greatly influence the resulting flow field.…”