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A dynamic mitral valve simulator for surgical training and patient specific preoperative planning
Author(s): Nora Boone; John Moore; Olivia Ginty; Daniel Bainbridge; Mehdi Eskandari; Terry Peters
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Paper Abstract

Mitral valve disease affects 2% of the Canadian population and 10% of those over the age of 75. Mitral valve regurgitation is a common valve disease often requiring surgical intervention for repair or replacement. Repair is often preferred over replacement, as it is associated with improved outcomes. Current mitral valve repair training is typically limited primarily to intraoperative experience. Additionally, the outcome of complex repair procedures is often unknown preoperatively, and is particularly true of new, off-pump repair techniques. Further challenges include identifying the most effective repair technique based on patient pathology, as multiple approaches exist. We present a hemodynamically accurate mitral valve phantom for testing previously validated patient specific pathological mitral valves. The device can be used for surgical resident training as well as complex procedure planning. The simulator is validated using pressure measurements across the mitral valve demonstrating realistic hemodynamics across a range of heart rates , and by evaluating valve function using 2D and 3D transesophageal echocardiography (TEE).

Paper Details

Date Published: 8 March 2019
PDF: 8 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109510H (8 March 2019); doi: 10.1117/12.2509818
Show Author Affiliations
Nora Boone, Western Univ. (Canada)
Robarts Research Institute (Canada)
John Moore, Robarts Research Institute (Canada)
Olivia Ginty, Robarts Research Institute (Canada)
Daniel Bainbridge, Western Univ. (Canada)
Mehdi Eskandari, King’s College Hospital (United Kingdom)
Terry Peters, Robarts Research Institute (Canada)
Western Univ. (Canada)

Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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