Energetics of Cardiac Blood Flow in Hypertrophic Cardiomyopathy through Individualized Computational Modeling

Area of Science:

• Cardiovascular Physiology
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Hypertrophic cardiomyopathy (HCM) involves left ventricular (LV) wall thickening, potentially leading to cardiac dysfunction.
• Altered blood flow patterns in HCM may exacerbate disease progression, but this is not well understood.
• Patient-specific factors influencing these flow patterns remain largely unknown.

Purpose of the Study:

• To develop personalized computational fluid dynamics (CFD) models of the left ventricle (LV) using cardiac magnetic resonance (cMR) images.
• To investigate how cardiac hypertrophy and inter-patient variability affect intra-LV blood flow patterns.
• To quantify flow patterns and energetics in normal and HCM patient-specific models.

Main Methods:

• Generation of patient-specific CFD models of the LV from cMR imaging data.
• Simulation of blood flow within the LV models to determine velocity fields.
• Quantification of flow patterns, energy transfer timing, and kinetic energy distribution.

Main Results:

• HCM hearts displayed anomalous intra-LV blood flow patterns compared to normal hearts.
• A temporal mismatch in energy transfer from the LV wall to blood flow was observed in HCM.
• Kinetic energy flow patterns were altered in the hypertrophic cardiomyopathy models.

Conclusions:

• Personalized CFD modeling offers a promising approach for analyzing hemodynamics in HCM.
• Aberrant flow patterns and energy transfer dynamics in HCM may contribute to disease progression.
• This methodology could enhance clinical understanding and management of hypertrophic cardiomyopathy.