Share Email Print
cover

Proceedings Paper

Patient-specific indirectly 3D printed mitral valves for pre-operative surgical modelling
Author(s): Olivia Ginty; John Moore; Wenyao Xia; Dan Bainbridge; Terry Peters
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Significant mitral valve regurgitation affects over 2% of the population. Over the past few decades, mitral valve (MV) repair has become the preferred treatment option, producing better patient outcomes than MV replacement, but requiring more expertise. Recently, 3D printing has been used to assist surgeons in planning optimal treatments for complex surgery, thus increasing the experience of surgeons and the success of MV repairs. However, while commercially available 3D printers are capable of printing soft, tissue-like material, they cannot replicate the demanding combination of echogenicity, physical flexibility and strength of the mitral valve. In this work, we propose the use of trans-esophageal echocardiography (TEE) 3D image data and inexpensive 3D printing technology to create patient specific mitral valve models. Patient specific 3D TEE images were segmented and used to generate a profile of the mitral valve leaflets. This profile was 3D printed and integrated into a mold to generate a silicone valve model that was placed in a dynamic heart phantom. Our primary goal is to use silicone models to assess different repair options prior to surgery, in the hope of optimizing patient outcomes. As a corollary, a database of patient specific models can then be used as a trainer for new surgeons, using a beating heart simulator to assess success. The current work reports preliminary results, quantifying basic morphological properties. The models were assessed using 3D TEE images, as well as 2D and 3D Doppler images for comparison to the original patient TEE data.

Paper Details

Date Published: 3 March 2017
PDF: 15 pages
Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 1013517 (3 March 2017); doi: 10.1117/12.2255567
Show Author Affiliations
Olivia Ginty, Western Univ. (Canada)
Robarts Research Institute, Western Univ. (Canada)
John Moore, Robarts Research Institute, Western Univ. (Canada)
Wenyao Xia, Robarts Research Institute, Western Univ. (Canada)
Dan Bainbridge, Western Univ. (Canada)
Terry Peters, Robarts Research Institute, Western Univ. (Canada)


Published in SPIE Proceedings Vol. 10135:
Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Baowei Fei, Editor(s)

© SPIE. Terms of Use
Back to Top