Patient Specific Mitral Valve Modeling for Surgical Planning and Training

BACKGROUND Mitral valve disease is a common pathologic problem occurring in approximately 2% of the general population, but climbing to 10% in those over the age of 75 in Canada. Of this group, approximately 20% have a sufficiently severe form of the disease that may require surgical intervention to restore normal valve function and prevent early mortality [4]. Evidence indicates that the surgeon's individual volume of mitral valve repair cases performed is a determinant of not only successful mitral repair rates, but also freedom from reoperation, and patient survival. For patients previously deemed inoperable due to co-morbidities, new techniques to treat mitral valve disease are being developed. However, assessing the optimal approach and the point at which clinical benefit is exceeded by the poor value or futility of the procedure is one of the biggest clinical challenges for physicians.

In the past decade, 3D echocardiography has emerged as a standard of care in diagnostic and interventional imaging for cardiac surgery and cardiology. This, coupled with the emergence of inexpensive 3D printing technology has led researchers and clinicians to explore how improved imaging and additive manufacturing can be used to improve patient outcomes.

In this context, the investigators have completed a proof-of-concept workflow for creating dynamic, patient specific mitral valve models. In concert with a left ventricle simulator 8], these valve models can mimic patient valve pathologies both anatomically and dynamically, as shown in Doppler ultrasound. In a 10 patient retrospective study, the investigators have demonstrated the ability to accurately re-create patient pathology, perform realistic surgical repairs, and assess realistic valve function post repair. The study team's vision is to create a simulator that can be used to assess patient candidacy for percutaneous interventions, assess different repair options for both percutaneous and surgical interventions, and finally use the model as a simulator for competency-based MV interventions.

RATIONALE Based on our successful proof of concept, the goal is to translate this technology to clinical use by validating our valve models. There are two primary long term goals. First, to validate a system for using patient specific MV models to: 1- assess intervention options, and 2: plan repair strategies for improved patient outcomes. Second, by building a database of MV pathologies, create a competency based simulator/trainer to provide surgeons with increased experience in MV repair techniques.

OBJECTIVES

1. Validate the accuracy of patient specific MV pathologies and repairs in a prospective 65 patient study;
2. Optimize our work-flow for creating valve models, in terms of accuracy, manufacture time required, and expense;
3. Validate the accuracy of our patient models for both surgical cases and transcatheter MitraClip interventions;