Mitral Repair Simulation With Dynamic Patient-specific Valve Models
Olivia K. Ginty1, John T. Moore2, Patrick K. Carnahan1, Terry M. Peters2, Bob B. Kiaii1, Dan B. Bainbridge1, Michael W.A. Chu1.
1Western University, London, ON, Canada, 2Robarts Research Institute, London, ON, Canada.
Background: Although expertise in mitral repair continues to grow, most surgeons select general reparative strategies based on pre-operative imaging and defer repair specifics to intraoperative evaluation and decision making. Common examples of these deferred decisions include size of leaflet resection, exact location of neochordae placement, and cleft closures. We aim to optimize surgical decision making and efficiency by creating dynamic physical patient-specific models to permit the rehearsal, training, and validation for the exact mitral repair in each patient. Methods: In a prospective observational trial, we will enroll 60 patients undergoing repair or Mitraclip procedures and replicate patient-specific valve models. Our workflow involves isolating the mitral anatomy from echocardiography images through a semi-automatic segmentation, generating a 3D printed mold for tissue-mimicking silicone, and ultimately producing a flexible patient-specific model. Each model is incorporated into an apparatus with patient-specific papillary muscle tips and adjustable chordae organized by the scallop to which it anchors; and functionally evaluated in our echocardiography-compatible beating heart simulator. In a preliminary analysis of the first 10 patients enrolled, 9 anatomical and regurgitation measurements were evaluated using Phillips QLab and statistical analysis by paired two-tailed t-tests. Results: Analysis revealed accuracy between the models and patients across most measurements, including anterior, posterior and total 3D leaflet areas, annulus height and tenting volume (critical two-tail>t stat, p-values=0.18, 0.41, 0.17, 0.13, 0.65 respectively). The models were smaller than the patients in anterior-posterior and anterolateral-posteromedial diameters, and annular 3D-circumference (t critical two-tail<t stat, p-values=0.03, 0.0015, 0.0016 respectively). This feedback has directed the improvement of our annulus segmentation process in the transverse plane and has highlighted an improvement in leaflet replication. All models matched the respective patient reports when blindly evaluated by an expert, and underwent successful repair simulations, as there was a significant reduction in regurgitation vena contracta widths (t critical two-tail<t stat, p-value=1.02x10-4). Conclusions: This study shows potential in its ability to mediate the challenging complexity of mitral repair through high fidelity simulation. This initial evaluation of 10 patients shows promising results, and we aim to deepen our evaluation and expand its application to more than 50 different additional mitral repair patients.
LEGEND: Left to Right, Patient-specific model apparatus complete with organized chordae anchoring system and neochordae repair; case 004 model undergoing repair and then repaired in simulator; top row: 004 patient (left) and model (right) pre-repair 3D transesophageal echocardiography (TEE); bottom row: 004 model colour TEE pre-repair (left) and post-repair (right).
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