Project

A biomechanical analysis of shear wave elastography in pediatric heart models

Duration
01 January 2015 → 31 October 2018
Funding
Regional and community funding: IWT/VLAIO
Research disciplines
  • Medical and health sciences
    • Biomechanics
    • Cardiology
    • Medical imaging and therapy not elsewhere classified
  • Engineering and technology
    • Biomedical image processing
    • Numerical modelling and design
    • Continuum mechanics
    • Kinematics and dynamics
    • Tissue and organ biomechanics
Keywords
shear wave elastography finite element method cardiac function wave physics
 
Project description

Early detection of cardiac disease in children is essential to optimize treatment and follow-up, but also to reduce its associated mortality and morbidity. Various cardiac imaging modalities are available for the cardiologist, mainly providing information on tissue morphology and structure with high temporal and/or spatial resolution. However, none of these imaging methods is able to directly measure stresses or intrinsic mechanical properties of the heart, which are potential key diagnostic markers to distinguish between normal and abnormal physiology.

This project investigates the potential of a relatively new ultrasound-based technique, called shear wave elastography (SWE), to non-invasively measure myocardial stiffness. The technique generates an internal perturbation inside the tissue of interest, and consequently measures the propagation of the acoustically excited shear wave, of which the propagation speed is directly related to tissue stiffness. This allows SWE to identify regions with higher stiffness, which is associated with pathology. SWE has shown to be successful in detecting tumors in breast tissue and fibrosis in liver tissue, however application of SWE to the heart is more challenging due to the complex mechanical and structural properties of the heart. This project provides insights into the acoustically excited shear wave physics in the myocardium by using computer simulations in combination with experiments. Furthermore, these models also allow to assess the performance of currently used SWE-based material characterization algorithms.