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Three-dimensional color Doppler ultrasound simulation to mimic paravalvular regurgitation
Author(s): Sandro Queirós; Hang Gao; Gianluca De Santis; Alexandros Papachristidis; Jaime C. Fonseca; João L. Vilaça; Jan D'hooge
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Paper Abstract

Despite its high success rate, transcatheter aortic valve implantation (TAVI) is still associated with numerous complications, among which paravalvular regurgitation (PVR, which has been associated to long-term outcome. Assessment of PVR remains challenging in clinical routine; it lacks a solid reference method and the clinically used echocardiographic-based parameters have numerous limitations. Moreover, the development/validation of novel automated PVR quantification methods is hampered by the absence of ground truth data. In this sense, this study proposes the use of an ultrasound simulation-based pipeline to generate synthetic 3D color Doppler ultrasound images that mimic retrograde blood flow in cases of PVR in TAVI patients. These synthetic volumes are created using flow fields obtained from computational fluid dynamics (CFD) simulations, in which the underlying regurgitant volume (RV) is known. Besides the CFD-based flow field, the pipeline requires also an anatomical model of the aortic tract wall to simulate both B-mode and color Doppler volumes. The presented pipeline was used to generate twenty simulated volumes mimicking transesophageal echocardiographic images of cases with distinct levels of PVR severity, showing a visually similar appearance to clinical images. Interestingly, PVR severity scores estimated from the synthetic volumes correlated well with the known CFD-based RV, as well as against post-implantation angiography-based severity scores. Overall, these results demonstrate the pipeline’s potential to generate synthetic images to be used for the validation of automated PVR quantification software and/or other clinical PVR-related studies.

Paper Details

Date Published: 15 March 2019
PDF: 10 pages
Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 109550X (15 March 2019); doi: 10.1117/12.2512785
Show Author Affiliations
Sandro Queirós, Life and Health Sciences Research Institute (Portugal)
PT Government Associate Lab. (Portugal)
KU Leuven/Univ. of Minho (Portugal)
Hang Gao, KU Leuven (Belgium)
Gianluca De Santis, FEops NV (Belgium)
Alexandros Papachristidis, King's College Hospital (United Kingdom)
Jaime C. Fonseca, Univ. of Minho (Portugal)
João L. Vilaça, Instituto Politécnico do Cávado e do Ave (Portugal)
Jan D'hooge, KU Leuven (Belgium)


Published in SPIE Proceedings Vol. 10955:
Medical Imaging 2019: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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