3 March 2017 Patient-specific indirectly 3D printed mitral valves for pre-operative surgical modelling
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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.
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Olivia Ginty, Olivia Ginty, John Moore, John Moore, Wenyao Xia, Wenyao Xia, Dan Bainbridge, Dan Bainbridge, Terry Peters, Terry Peters, } "Patient-specific indirectly 3D printed mitral valves for pre-operative surgical modelling", Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 1013517 (3 March 2017); doi: 10.1117/12.2255567; https://doi.org/10.1117/12.2255567
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