Fast Surgical Simulation to Improve Mitral Valve Repair

author:Neil A. Tenenholtz
adviser:Robert D. Howe
year:2014
degree: Ph.D.
institution: Harvard University

Mitral valve repair, the preferred method of treating mitral regurgitation, is a demanding surgical procedure consisting of the resection and approximation of valve tissue. Operating on an arrested heart, the clinician is forced to predict closed valve shape and the effect of surgical modifications. The valve's complex morphology makes this a difficult task, and as a result, the procedure is underperformed by less experienced surgeons in lieu of the simpler, less effective valve replacement.

This thesis details the use of fast, computer-based simulation to ease this predictive task and facilitate valve repair. A computational model is first developed and optimized for speed of execution. Valve closure is simulated with sub-millimeter accuracy in less than one second, more than an order of magnitude faster than previous results. An intuitive surgical planning system is then constructed. To maximize ease of use, a haptic device, leveraging the models greater than three kilohertz update rate, serves as the primary means user interaction.

This interactive system was then used to assess and improve the ability of senior medical students in predicting closed valve shape. After initial studies revealed a success rate equivalent to random chance, far below that of the surgeons evaluated, simulator-based instruction was provided to investigate its efficacy as a pedagogical tool. More so than a leading surgical textbook, this alternative educational methodology was shown to result in improved user performance in both a virtual setting and ex-vivo porcine model.

Finally, through repeated simulation, the robustness of mitral valve repair in the treatment of ischemic mitral regurgitation was investigated. The existing standard of care was shown to exhibit a heightened response to small changes in cardiac geometry, thus explaining the common recurrence of regurgitation. A novel surgical technique was therefore assessed and optimized for reduced sensitivity to these variations.



Harvard BioRobotics Laboratory Home