3D printed mitral valve models: affordable simulation for robotic mitral valve repair.

OBJECTIVES

3D printed mitral valve (MV) models that capture the suture response of real tissue may be utilized as surgical training tools. Leveraging clinical imaging modalities, 3D computerized modelling and 3D printing technology to produce affordable models complements currently available virtual simulators and paves the way for patient- and pathology-specific preoperative rehearsal.

METHODS

We used polyvinyl alcohol, a dissolvable thermoplastic, to 3D print moulds that were casted with liquid platinum-cure silicone yielding flexible, low-cost MV models capable of simulating valvular tissue. Silicone-moulded MV models were fabricated for 2 morphologies: the normal MV and the P2 flail. The moulded valves were plication and suture tested in a laparoscopic trainer box with a da Vinci Si robotic surgical system. One cardiothoracic surgery fellow and 1 attending surgeon qualitatively evaluated the ability of the valves to recapitulate tissue feel through surveys utilizing the 5-point Likert-type scale to grade impressions of the valves.

RESULTS

Valves produced with the moulding and casting method maintained anatomical dimensions within 3% of directly 3D printed acrylonitrile butadiene styrene controls for both morphologies. Likert-type scale mean scores corresponded with a realistic material response to sutures (5.0/5), tensile strength that is similar to real MV tissue (5.0/5) and anatomical appearance resembling real MVs (5.0/5), indicating that evaluators 'agreed' that these aspects of the model were appropriate for training. Evaluators 'somewhat agreed' that the overall model durability was appropriate for training (4.0/5) due to the mounting design. Qualitative differences in repair quality were notable between fellow and attending surgeon.

CONCLUSIONS

3D computer-aided design, 3D printing and fabrication techniques can be applied to fabricate affordable, high-quality educational models for technical training that are capable of differentiating proficiency levels among users.