Cardiac shear wave speed estimation in 3D: an in silico and in vivo study

Селиверстова, Е Н; Caenen, Annette; Santos, Paulo F.; Papangelopoulou, K; D’hooge, Jan

doi:10.1109/ius54386.2022.9957145

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…1 and 2. walls was observed in H3 and H4, similar to recent findings [10]. However, the wave source in the inferior/inferolateral wall was identified to be located in the apex, which is considered non-physiological.…”

Section: A Mw Propagationsupporting

confidence: 88%

“…12, analyzes 3D propagation, Mline, and M-mode together. Previous studies have visualized 3D wave propagation and M-line, but to our knowledge, the M-line has not been adjusted based on the observed wave direction [9], [10].…”

Section: A Mw Propagationmentioning

confidence: 99%

“…Since then, numerous studies have invested in this field. The main disadvantages of natural waves are their complex origins and propagation patterns, as well as fixed temporal and spatial incidence [9], [10]. Fortunately, successful velocity estimation of the mentioned wave sources can yield valuable insights into the myocardium during key phases: end diastole (MVC), end systole (AVC), and early filling (AK).…”

Section: Introductionmentioning

confidence: 99%

“…With high-frame-rate (HFR) 3D cardiac imaging based on broad-beam emission and parallel beamforming, detecting MW propagation in 3D is now feasible [9], [10], [16] (∼ 600-1100 volumes/s). Salles et al conducted a feasibility study using the gradient of TOF of the AK wave to calculate 3D wave propagation velocity, enabling evaluation of the entire myocardium [16].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Automated 3D Velocity Estimation of Natural Mechanical Wave Propagation in the Myocardium

Mohajery,

Salles,

Espeland

et al. 2023

IEEE Open J. Ultrason., Ferroelect., Freq. Contr.

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The mechanical wave (MW) propagation velocity in the heart is related to the tissue stiffness and its measurement mainly relies on manual evaluation of the 1D wave projection. This study presents an automated method for 3D wave visualization and velocity estimation in the heart using 3D ultrasound imaging of the left ventricle (LV). High-quality (HQ, 19 vps) and high-frame-rate (HFR, 823 vps) volumes were acquired. Deep learning models automatically segmented the LV and extracted the apical standard views from the HQ data which were used to derive the anatomical M-lines and myocardial segmentation. The clutter filter wave imaging (CFWI) and tissue Doppler imaging (TDI) generated wave propagation maps from HFR data, and the aortic valve closure (AVC) and atrial contraction/kick (AK) waves were automatically detected. LV segmentation and anatomical M-lines were used for 3D wave propagation extraction and its 1D projection, respectively. The 1D wave propagation velocity was determined through automatic slope detection, while the 3D velocity map was derived from the gradient of the time-offlight (TOF) map. Results showed varying 1D velocity across views and myocardial regions, with the AVC propagation velocity surpassing that of the AK wave. The pipeline remained stable and generated results consistent with expert measurements. Comparing 3D and 1D propagation highlighted errors from 1D projection and demonstrated the benefits of the 3D method in assessing regional velocities and the validity of the 1D approach. This study demonstrated an automatic evaluation of 3D MW propagation velocities in the entire LV, leading to improved accuracy and standardized measurements of myocardial tissue properties.INDEX TERMS Aortic valve closure wave, Atrial kick wave, Cardiac elstography, Mechanical wave imaging, Natural mechanical waves, Shear wave imaging.

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Section: A Mw Propagationsupporting

confidence: 88%

Section: A Mw Propagationmentioning

confidence: 99%