PURPOSE: Patient-specific heart and valve models have shown promise as training and planning tools for heart surgery, but physically realistic valve models remain elusive. Available proprietary, simulation-focused heart valve models are generic adult mitral valves and do not allow for patient-specific modeling as may be needed for rare diseases such as congenitally abnormal valves. We propose creating silicone valve models from a 3D-printed plastic mold as a solution that can be adapted to any individual patient and heart valve at a fraction of the cost of direct 3D-printing using soft materials. METHODS: Leaflets of a pediatric mitral valve, a tricuspid valve in a patient with hypoplastic left heart syndrome, and a complete atrioventricular canal valve were segmented from ultrasound images. A custom software was developed to automatically generate molds for each valve based on the segmentation. These molds were 3D-printed and used to make silicone valve models. The models were designed with cylindrical rims of different sizes surrounding the leaflets, to show the outline of the valve and add rigidity. Pediatric cardiac surgeons practiced suturing on the models and evaluated them for use as surgical planning and training tools. RESULTS: Five out of six surgeons reported that the valve models would be very useful as training tools for cardiac surgery. In this first iteration of valve models, leaflets were felt to be unrealistically thick or stiff compared to real pediatric leaflets. A thin tube rim was preferred for valve flexibility. CONCLUSION: The valve models were well received and considered to be valuable and accessible tools for heart valve surgery training. Further improvements will be made based on surgeons’ feedback.
Anna Ilina, Andras Lasso, Matthew A. Jolley, Brittany Wohler, Alex Nguyen, Adam Scanlan, Zachary Baum, Frank McGowan, and Gabor Fichtinger, "Patient-specific pediatric silicone heart valve models based on 3D ultrasound," Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 1013516 (Presented at SPIE Medical Imaging: February 16, 2017; Published: 3 March 2017); https://doi.org/10.1117/12.2255849.
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