Comparison of Filtering Methods for Calculating ARFI log(VoA) to Delineate Carotid Plaque Features, In Vivo
SHUREED QAZI, KEERTHI S. ANAND, JONATHON W. HOMEISTER, MARK A. FARBER, CATERINA M. GALLIPPI

TL;DR
This study compares different filtering methods to calculate ARFI log(VoA) for identifying carotid plaque features in real patients, finding that the SOTD filter performs best.
Contribution
The study empirically evaluates and compares multiple filtering methods for ARFI log(VoA) calculation in vivo for carotid plaque assessment.
Findings
The SOTD filter consistently provided the highest generalized contrast-to-noise ratio for most plaque components.
Other filters like PCA, FIR, IIR, and MCS showed more variable performance in delineating plaque features.
Results were validated using spatially aligned histology for accuracy.
Abstract
Carotid atherosclerosis is a major cause of ischemic stroke, and the ability to non-invasively assess plaque composition and structure is critical to effective stroke risk assessment. Carotid plaque components are delineated noninvasively by Acoustic Radiation Force Impulse (ARFI)-derived Variance of Acceleration, evaluated as its decadic log (log(VoA)). To date, this log(VoA) parameter has been calculated by isolating the variance in ARFI-induced displacement profiles using the second-order time derivative (SOTD), a high-pass filtering operation. The purpose of this study was to compare the performance of the SOTD filter to various other filtering methods in application to delineating human carotid plaque components, in vivo. Specifically, the SOTD filter was compared to Principal Component Analysis (PCA), Finite Impulse Response (FIR), Infinite Impulse Response (IIR), and mean-center…
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Taxonomy
TopicsUltrasound Imaging and Elastography · Cardiovascular Health and Disease Prevention · Phonocardiography and Auscultation Techniques
