Major cardiovascular diseases (CVDs) are associated with (regional) dysfunction of the left ventricle. Despite the 3-D nature of the heart and its dynamics, the assessment of myocardial function is still largely based on 2-D ultrasound imaging, thereby making diagnosis heavily susceptible to the operator's expertise. Unfortunately, to date, 3-D echocardiography cannot provide adequate spatiotemporal resolution in real-time. Hence, tri-plane imaging has been introduced as a compromise between 2-D and true volumetric ultrasound imaging. However, tri-plane imaging typically requires high-end ultrasound systems equipped with fully populated matrix array probes embedded with expensive and little flexible electronics for two-stage beamforming. This article presents an advanced ultrasound system for real-time, high frame rate (HFR), and tri-plane echocardiography based on low element count sparse arrays, i.e., the so-called spiral arrays. The system was simulated, experimentally validated, and implemented for real-time operation on the ULA-OP 256 system. Five different array configurations were tested together with four different scan sequences, including multi-line and planar diverging wave transmission. In particular, the former can be exploited to achieve, in tri-plane imaging, the same temporal resolution currently used in clinical 2-D echocardiography, at the expenses of contrast (-3.5 dB) and signal-to-noise ratio (SNR) (-8.7 dB). On the other hand, the transmission of planar diverging waves boosts the frame rate up to 250 Hz, but further compromises contrast (-10.5 dB), SNR (-9.7 dB), and lateral resolution (+46%). In conclusion, despite an unavoidable loss in image quality and sensitivity due to the limited number of elements, HFR tri-plane imaging with spiral arrays is shown to be feasible in real-time and may enable real-time functional analysis of all left ventricular segments of the heart.
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http://dx.doi.org/10.1109/TUFFC.2019.2940289 | DOI Listing |
Eur Heart J Imaging Methods Pract
May 2023
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, NTNU, Box 8905, 7491 Trondheim, Norway.
Aims: Apical foreshortening leads to an underestimation of left ventricular (LV) volumes and an overestimation of LV ejection fraction and global longitudinal strain. Real-time guiding using deep learning (DL) during echocardiography to reduce foreshortening could improve standardization and reduce variability. We aimed to study the effect of real-time DL guiding during echocardiography on measures of LV foreshortening and inter-observer variability.
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