Computational Study on the Acoustic Footprint of Stenosis in Larger Arteries - Abdelnabi, Ahmed (AUC Knowledge Fountain, 2023)
We identify a new (acoustic) frequency-stenosis relations whose frequencies fall within the recommended auscultation threshold for stethoscopy (< 120 Hz) in this study. We demonstrate that these relations can be used to extend the application of phonoangiography (the measurement of the degree of stenosis from bruits) to stethoscopes that are broadly available. The First relationship is successfully identified using an analysis limited to the acoustic signature of the von Karman vortex street, which we automatically isolate using a metric based on an area-weighted average of the Q-criteria for the post-stenotic region. Specifically, we conduct LES-CFD simulations on simplified 2D internal flow geometries that represent blood vessels with varying degrees of stenosis. Then, using the Ffowcs Williams-Hawkings (FW-H) equation, we extract their emitted acoustic signals, which we subtract from a pure signal (stenosis-free) at the same heart rate. Next, we transform this differential signal to the frequency domain and meticulously classify its acoustic signatures according to six stenosis-invariant flow phases of a cardiac cycle. Using our Q-criterion-based metric, we then automatically restrict our acoustic analysis to the noises emitted by the von Karman vortex street (phase 4). Our analysis of its acoustic signature demonstrates a strong linear relationship between the degree of steno- sis and its dominant frequency, which differs significantly from the break frequency and heart rate (previously identified dominant frequencies). For the Second relationship, we develop a frequency-stenosis scaling law for particularly supravalvular aortic stenosis that falls within the preferred frequency range (30-120 Hz) for echocardiography. We expand to 3D patient specific geometry using Simulia’s Living Heart Human Model (LHHM), which has an anatomically accurate aorta geometry. This LHHM geometry is modified with stenoses ranging from 30 to 80 percent (moderate to severe). For physiologically consistent hemodynamic boundary conditions, we expand the study to employ the Windkessel model, which has been implemented on Fluent using UDF. We demonstrate that physiological boundary conditions reduce simulation time significantly compared to static boundary conditions. The FW-H model extracted the flow-generated acoustic signal of the stenotic geometries and analysed it at clinically relevant receiver locations. A preferred receiver location consistent with clinical practise is determined, and a correlation between the degree of stenosis and the prevalent acoustic frequency (within the frequency range of 70-120 Hz) is established. The obtained second scaling law is shown to be clinically reliable in assessing stenotic severity. Future research will investigate incorporating the vibroacoustic role of adjacent organs and tissue to expand the clinical applicability of our findings. Expansion of clinical and numerical datasets will be pursued in future research to enhance the reliability of our scaling law, possibly by leveraging much-needed ML-based acceleration schemes.