Systolic anterior motion after mitral valve repair: a predictive computational model.

Objectives: Systolic anterior motion (SAM) can be an insidious complication after mitral repair. Predicting SAM represents a challenge, even for very experienced mitral valve surgeons. The goal of this pilot work was to illustrate for the first time, a computational software able to calculate and prevent SAM during mitral repair.
Methods: Using MATLAB graphical user interface, a clinical software to predict SAM, we tested the performances of the software on 136 patients with degenerative mitral valves undergoing repair with standard techniques. A combination of 6 key echocardiographic parameters was used to calculate the SAM risk score. The discriminative performance of the model was assessed by the area under the receiver-operating characteristic curve. The receiver-operating characteristic was used to divide patients into low, medium and high risk for SAM. Simulation of virtual mitral repair (posterior leaflet resection and mitral ring annuloplasty) was also tested to reduce the risk of SAM.
Results: The incidence of SAM was 8.1%; 73% were detected as high risk by the software. The area under the receiver-operating characteristic model discriminant performance was 0.87 (95% confidence interval: 0.78-0.95). Simulating a posterior leaflet resection with the leaflet length fixed at 15 mm, the estimated SAM risk was updated, and all patients were then classified at low risk.
Conclusions: This software is the first computational model designed to predict SAM during mitral repair to show excellent discrimination. This software has the potential to predict SAM risk preoperatively and, after a virtual step-by-step mitral repair simulation, depending on the technique adopted, to always achieve a low-risk SAM profile.
(© The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)