Automated Measurement of Local Mechanical Activation on High Frame Rate Echocardiography

High Frame Rate Speckle Tracking Echocardiography (HFR-STE) offers a method to pinpoint the local onset of contraction in the left ventricle (LV) and generate mechanical activation maps. In this paper, a new patient-specific spatiotemporal approach is proposed to identify activation times on left ventricular strain rate (SR) curves automatically. Curves are collected from 2D HFR-STE according to the 16-segment model. Using a Locally Weighted Principal Component Analysis (LWPCA), the main pattern of each segment’s SR curve is extracted locally. The first positive-to-negative zero-crossing point on the first principal component is identified as the activation time. Validation with a dataset of 40 subjects (20 healthy volunteers and 20 patients) showed that 94% of estimated activation times closely matched the expert-identified times, differing by no more than 16ms. Quantitative and qualitative comparisons between LWPCA and (weighted) averaging are also reported. Also, the automatically generated activation maps closely resemble their manually created counterparts, demonstrating good visual similarity.

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Publication Details

Journal
IEEE Open Journal of Ultrasonics Ferroelectrics and Frequency Control
Published
2025-01-01
DOI
https://doi.org/10.1109/ojuffc.2025.3596042
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.67

Funders

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article

Automated Measurement of Local Mechanical Activation on High Frame Rate Echocardiography

K Papangelopoulou, M Orlowska, Hans Dierckx, Vahid Mohammadi Safarzadeh et al.
1 citations
IEEE Open Journal of Ultrasonics Ferroelectrics and Frequency Control
Non-Invasive Vital Sign Monitoring
0.67
article

Automated Measurement of Local Mechanical Activation on High Frame Rate Echocardiography

K Papangelopoulou, M Orlowska, Hans Dierckx, Vahid Mohammadi Safarzadeh, Jan D’hooge
article en
1 citations

Abstract

High Frame Rate Speckle Tracking Echocardiography (HFR-STE) offers a method to pinpoint the local onset of contraction in the left ventricle (LV) and generate mechanical activation maps. In this paper, a new patient-specific spatiotemporal approach is proposed to identify activation times on left ventricular strain rate (SR) curves automatically. Curves are collected from 2D HFR-STE according to the 16-segment model. Using a Locally Weighted Principal Component Analysis (LWPCA), the main pattern of each segment’s SR curve is extracted locally. The first positive-to-negative zero-crossing point on the first principal component is identified as the activation time. Validation with a dataset of 40 subjects (20 healthy volunteers and 20 patients) showed that 94% of estimated activation times closely matched the expert-identified times, differing by no more than 16ms. Quantitative and qualitative comparisons between LWPCA and (weighted) averaging are also reported. Also, the automatically generated activation maps closely resemble their manually created counterparts, demonstrating good visual similarity.

IEEE Open Journal of Ultrasonics Ferroelectrics and Frequency ControlVol. 5
University College West Flanders (BE), KU Leuven (BE)
KU Leuven
Openalex Percentile: Top 28%
Non-Invasive Vital Sign Monitoring
0.67
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