Abstract
ACL surgery aims to repair or reconstruct the anterior cruciate ligament (ACL) by replacing the injured ligament with a graft. This paper presents an automated workflow for modeling, simulation, and analysis of the ACLR surgery relying on subject-specific data to assist orthopedists in the assessment of surgery options and in the complex task for the identification of the optimal combination of ACLR parameters for each patient, towards optimal ACLR surgery planning. The surgery modeling workflow includes an automatic pipeline which has been developed for modeling surgery parameters based on subject-specific geometries following the MRI segmentation and by considering different surgical techniques. A reference model of the intact knee has been developed and has been validated with data provided by the Open Knee(s) project, for the evaluation of effectiveness of ligament stiffness estimation directly from MRI, while responses with the reference model have been compared through the performance of “what-if” simulations. Results indicate reduced relative knee displacement due to increased graft pretension, correlation of graft radius and tension need to be considered, reduced knee laxity with graft fixation angle of 20∘, while single-versus double-bundle techniques demonstrate comparable performance in restraining knee translation. Developed numerical models have been made publicly available.