Experimental and computational models for intracardiac flow analysis with blood speckle imaging

Abstract

Intracardiac flow analysis aims to evaluate blood flow patterns and associated parameters for the assessment of cardiac function. However, there is limited understanding as to how flow parameters are influenced by various sources, such as pressure upstream/downstream and cardiac chamber compliance. The objective of this study was to investigate experimental and computational tissue-mimicking models to be used alongside 2D Blood Speckle Imaging for intracardiac flow analysis. Two geometries, an axisymmetric swell and idealized left ventricle, were utilized. As an initial parameter of interest, the pressure-drop across each geometry was determined from tissue-mimicking phantoms using direct pressure measurements, blood speckle imaging, and 3D computational fluid dynamics simulations with fluid-structure interaction. The results indicate limited quantitative agreement between direct measurements, 2D blood speckle imaging, and 3D computational fluid dynamics, with qualitative agreement capturing a consistent shape of the pressure drop curve between methods. Additionally, the importance of phantom design is demonstrated due to the likely impact of gel thickness on flow patterns and their associated measurements. The findings of this study indicate that future work focusing on the optimization of BSI settings and increasing model complexity with the inclusion of cardiac valves and patient-specific geometries are still required. These models may then allow for further tuning of variables to better understand their effect on various intracardiac flow parameters, and ultimately their clinical applicability.