Advances in Live 3D Echocardiography

2008 ◽  
Vol 4 (2) ◽  
pp. 27
Author(s):  
Mauro Pepi ◽  
Adam Staron ◽  
Gloria Tamborini ◽  
◽  
◽  
...  
Keyword(s):  
3D Echocardiography

Minimized use of contrast agent and fluoroscopic time by 3D echocardiography in transapical TAVI procedures

2013 ◽  
Vol 61 (S 01) ◽  
Author(s):  
F Masseli ◽  
T Bostani ◽  
M Endlich ◽  
C Gestrich ◽  
D Sterner ◽  
...  
Keyword(s):  
Contrast Agent ◽  
3D Echocardiography ◽  
Fluoroscopic Time

Developments in 3D Echocardiography

2009 ◽  
Vol 5 (2) ◽  
pp. 10 ◽  
Author(s):  
Jose Luis Zamorano ◽  
Keyword(s):  
3D Echocardiography ◽  
Resonance Imaging ◽  
Clinical Tool ◽  
3D Images ◽  
Processing Power ◽  
2D Echocardiography ◽  
Automated Quantification ◽  
Heart Cycle ◽  
Functional Mechanisms ◽  
Full Volume

3D echocardiography (3DE) will gain increasing acceptance as a routine clinical tool as the technology evolves due to advances in technology and computer processing power. Images obtained from 3DE provide more accurate assessment of complex cardiac anatomy and sophisticated functional mechanisms compared with conventional 2D echocardiography (2DE), and are comparable to those achieved with magnetic resonance imaging. Many of the limitations associated with the early iterations of 3DE prevented their widespread clinical application. However, recent significant improvements in transducer and post-processing software technologies have addressed many of these issues. Furthermore, the most recent advances in the ability to image the entire heart in realtime and fully automated quantification have poised 3DE to become more ubiquitous in clinical routine. Realtime 3DE (RT3DE) systems offer further improvements in the diagnostic and treatment planning capabilities of cardiac ultrasound. Innovations such as the ability to acquire non-stitched, realtime, full-volume 3D images of the heart in a single heart cycle promise to overcome some of the current limitations of current RT3DE systems, which acquire images over four to seven cardiac cycles, with the need for gating and the potential for stitch artefacts.

Latest developments in 3D echocardiography. A novel tissue transparency tool

2021 ◽  
Author(s):  
Marina Pascual Izco ◽  
Covadonga Fernández-Golfín Lobán ◽  
José Luis Zamorano Gómez
Keyword(s):  
3D Echocardiography

scholarly journals Automated analysis of 3D-echocardiography using spatially registered patient-specific CMR meshes

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
D Zhao ◽  
E Ferdian ◽  
GD Maso Talou ◽  
GM Quill ◽  
K Gilbert ◽  
...  
Keyword(s):  
New Zealand ◽  
Interobserver Variability ◽  
Ground Truth ◽  
Automated Analysis ◽  
3D Echocardiography ◽  
Training Data ◽  
Patient Specific ◽  
Manual Analysis ◽  
Lv Mass ◽  
3D Echo

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart Foundation (NHF) of New Zealand Health Research Council (HRC) of New Zealand Artificial intelligence shows considerable promise for automated analysis and interpretation of medical images, particularly in the domain of cardiovascular imaging. While application to cardiac magnetic resonance (CMR) has demonstrated excellent results, automated analysis of 3D echocardiography (3D-echo) remains challenging, due to the lower signal-to-noise ratio (SNR), signal dropout, and greater interobserver variability in manual annotations. As 3D-echo is becoming increasingly widespread, robust analysis methods will substantially benefit patient evaluation.  We sought to leverage the high SNR of CMR to provide training data for a convolutional neural network (CNN) capable of analysing 3D-echo. We imaged 73 participants (53 healthy volunteers, 20 patients with non-ischaemic cardiac disease) under both CMR and 3D-echo (<1 hour between scans). 3D models of the left ventricle (LV) were independently constructed from CMR and 3D-echo, and used to spatially align the image volumes using least squares fitting to a cardiac template. The resultant transformation was used to map the CMR mesh to the 3D-echo image. Alignment of mesh and image was verified through volume slicing and visual inspection (Fig. 1) for 120 paired datasets (including 47 rescans) each at end-diastole and end-systole. 100 datasets (80 for training, 20 for validation) were used to train a shallow CNN for mesh extraction from 3D-echo, optimised with a composite loss function consisting of normalised Euclidian distance (for 290 mesh points) and volume. Data augmentation was applied in the form of rotations and tilts (<15 degrees) about the long axis. The network was tested on the remaining 20 datasets (different participants) of varying image quality (Tab. I). For comparison, corresponding LV measurements from conventional manual analysis of 3D-echo and associated interobserver variability (for two observers) were also estimated. Initial results indicate that the use of embedded CMR meshes as training data for 3D-echo analysis is a promising alternative to manual analysis, with improved accuracy and precision compared with conventional methods. Further optimisations and a larger dataset are expected to improve network performance. (n = 20) LV EDV (ml) LV ESV (ml) LV EF (%) LV mass (g) Ground truth CMR 150.5 ± 29.5 57.9 ± 12.7 61.5 ± 3.4 128.1 ± 29.8 Algorithm error -13.3 ± 15.7 -1.4 ± 7.6 -2.8 ± 5.5 0.1 ± 20.9 Manual error -30.1 ± 21.0 -15.1 ± 12.4 3.0 ± 5.0 Not available Interobserver error 19.1 ± 14.3 14.4 ± 7.6 -6.4 ± 4.8 Not available Tab. 1. LV mass and volume differences (means ± standard deviations) for 20 test cases. Algorithm: CNN – CMR (as ground truth). Abstract Figure. Fig 1. CMR mesh registered to 3D-echo.

Relation of Left Atrial Maximal Volume Measured by Real-Time 3D Echocardiography to Demographic, Clinical, and Doppler Variables

2008 ◽  
Vol 101 (9) ◽  
pp. 1347-1352 ◽  
Author(s):  
Stefano De Castro ◽  
Stefano Caselli ◽  
Emanuele Di Angelantonio ◽  
Sara Del Colle ◽  
Francesca Mirabelli ◽  
...  
Keyword(s):  
Real Time ◽  
Left Atrial ◽  
3D Echocardiography ◽  
Maximal Volume

scholarly journals Epicardial and transverse sinus fat pad near left atrium appendage; role of 3D echocardiography

2020 ◽  
Author(s):  
Reza Mohseni‐badalabadi ◽  
Mohammad Sahebjam ◽  
Mehdi Mohseni‐badalabadi ◽  
Kaveh Hosseini
Keyword(s):  
Left Atrium ◽  
Transverse Sinus ◽  
3D Echocardiography ◽  
Fat Pad
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