Predicting anterior cruciate ligament failure load with T2* relaxometry and machine learning as a prospective imaging biomarker for revision surgery

Predicting anterior cruciate ligament failure load with T2* relaxometry and machine learning as a prospective imaging biomarker for revision surgery

Abstract Non-invasive methods to document healing anterior cruciate ligament (ACL) structural properties could potentially identify patients at risk for revision surgery. The objective was to evaluate machine learning models to predict ACL failure load from magnetic resonance images (MRI) and to det...

Full description

Bibliographic Details
Main Authors: Sean W. Flannery, Jillian E. Beveridge, Benedikt L. Proffen, Edward G. Walsh, BEAR Trial Team, Dennis E. Kramer, Martha M. Murray, Ata M. Kiapour, Braden C. Fleming
Format: Article
Language:English
Published: Nature Portfolio 2023-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-30637-5

Internet

https://doi.org/10.1038/s41598-023-30637-5

Similar Items