MO58. Linear Combination Of Mitral Valve And Machine Learning To Predict Mitral Annuloplasty Band Size in Endoscopic Mitral Valve Surgery
Presented During: Mini-Orals: Translational Research, Innovation, Predictive Modeling
Fondazione Toscana Gabriele Monasterio
Massa, Massa and Carrara
Italy - Contact Me
I am an cardiac surgeon interested in minimally invasive procedures. I do practice and my interest right now are focues on mitral valve surgery through minithoractomy endoscopicly guided.
Friday, May 5, 2023: 7:10 AM - 7:15 AM
5 Minutes
New York Hilton Midtown
Room: Petit Trianon
Description
Background: Endoscopic mitral valve surgery is becoming standard of care. However it has steep learning curve and annular sizing is difficult with conventional sizers.
Methods: A retrospective analysis was performed on 104 patients who underwent mitral repair at one institution from July 2015 to September 2022. 93 of them had CT scans suitable for mitral valvular apparatus measurements (intertrigonal distance, anterior leaflet max length, etc). A machine learning pipeline was created in order to predict annuloplasty band size (from 26 to 38 mm). Mitral measurements were done in MPR modality.
Results: A final model (best model among the trained) was able to predict the annular size with 72% accuracy. A linear combination (PCA fo two components) of intertrigonal distance and anterior leaflet lengths was the main linear combination in the model
Conclusions: Linear combination of mitral valve measurements can predict annular size in clinical setting. Its value is highly valuable for young and inexperienced groups.
Methods: A retrospective analysis was performed on 104 patients who underwent mitral repair at one institution from July 2015 to September 2022. 93 of them had CT scans suitable for mitral valvular apparatus measurements (intertrigonal distance, anterior leaflet max length, etc). A machine learning pipeline was created in order to predict annuloplasty band size (from 26 to 38 mm). Mitral measurements were done in MPR modality.
Results: A final model (best model among the trained) was able to predict the annular size with 72% accuracy. A linear combination (PCA fo two components) of intertrigonal distance and anterior leaflet lengths was the main linear combination in the model
Conclusions: Linear combination of mitral valve measurements can predict annular size in clinical setting. Its value is highly valuable for young and inexperienced groups.
Presentation Duration
3-minute presentation; 2-minute discussion