A clinically aligned experimental approach for quantitative characterization of patient-specific cardiovascular models

Ana Paula Narata,Charles A Sennoga,Ignacio Larrabide,Fernando Silva De Moura,Alberto Marzo,Fréderic Patat,Cecile Perrault,Ayache Bouakaz,Jean-Marc Gregoire

doi:10.1063/1.5141350

Abstract

Recent improvements in computational tools opened the possibility of patient-specific modeling to aid clinicians during diagnosis, treatment, and monitoring. One example is the modeling of blood flow for surgical planning, where modeling can help predict the prognosis. Computational analysis is used to extract hemodynamic information about the case; however, these methods are sensitive to assumptions on blood properties, boundary conditions, and appropriate geometry accuracy. When available, experimental measurements can be used to validate the results and, among the modalities, ultrasound-based methods are suitable due to their relative low cost and non-invasiveness. This work proposes a procedure to create accurate patient-specific silicone replicas of blood vessels and a power Doppler compatible experimental setup able to simulate and measure realistic flow conditions. The assessment of silicone model geometry shows small discrepancies between these and the target geometries (median of surface error lies within 57 µm and 82 μm). Power Doppler measurements were compared against computational fluid dynamics results, showing discrepancies within 10% near the wall. The experimental approach offers a setup to quantify flow in in vitro systems and provide more accurate results where other techniques (e.g., particle image velocimetry and particle tracking velocimetry) have shown limitations due to the interference of the interface.

Highlights

Patient-specific modeling has gained new momentum over the past two decades, mainly driven by improvements in computer power, modeling software, the availability of high-resolution medical imaging techniques, and the potential of biomechanical measurements for clinical decision-making and surgical planning.1 Of fundamental importance for a successful translation of such modeling approaches toward clinical utility is their reliability in providing robust and accurate predictions, a requisite that can be achieved through a process of verification, validation, and assessment of the impact of data uncertainty on the model outputs
In cardiovascular studies, many experimental approaches have been proposed by the scientific community for validation of modeled data ranging from optical-based techniques, such as Particle Image Velocimetry (PIV)2,3 and Particle Tracking Velocimetry (PTV), to measurements obtained using approaches that are more aligned with current clinical procedures such as ultrasound (US)/echo Doppler and MRI for quantification of blood flows in vitro and in vivo
The aim of this study is to develop closely matching experimental patient-specific 3D anatomical replicas and evaluate ultrasound power Doppler (PD) flow measurements as a way to characterize the flow in these replicas

Summary

Introduction

Patient-specific modeling has gained new momentum over the past two decades, mainly driven by improvements in computer power, modeling software, the availability of high-resolution medical imaging techniques, and the potential of biomechanical measurements for clinical decision-making and surgical planning. Of fundamental importance for a successful translation of such modeling approaches toward clinical utility is their reliability in providing robust and accurate predictions, a requisite that can be achieved through a process of verification, validation, and assessment of the impact of data uncertainty (variable, noisy, or missing data) on the model outputs. In an attempt to provide a more quantitative and accurate approach for the analysis of flow in 2D images, de Senneville et al. proposed a combination of contrast-enhanced ultrasound (CEUS) with modeling to enhance measurement accuracy. This led to improved accuracy of the measured data compared to more traditional ultrasound-based approaches, paving the way to the establishment of such techniques for quantitative analysis of blood flows. Geometry quality assessment is performed to quantify the quality of the models, and PD measurements are compared against the Computational Fluid Dynamics (CFD) analysis to quantify the discrepancy between the results

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