POLYTECH S.A. in cooperation with the Department of Medical Science of Health Sciences University of Thessaly, the Institute of Research and Technology of Thessaly (ΙΕΤΕΘ/ΕΚΕΤΑ) and the Information and Virtual Reality Visualization Team (VVR), department of Electrical Engineering & Computer Technology, University of Patras, will proceed with the implementation of the project “SafeACL – Decision support software for anterior cruciate ligament reconstruction based on individualized musculoskeletal computer models” after submitting the research proposal which was approved by the ESPA 2014-2020 “Research-Create-Innovate” business program.
The Problem
An anterior cruciate ligament (ACL) tear is a devastating injury to an athlete and unfortunately is one of the more common knee injuries in athletes involved in rapid deceleration moves. An ACL deficient knee has a very high risk of instability, subsequent injury, and long-term osteoarthritis. It is estimated that between 100,000 and 250,000 of these injuries occur each year in the United States (no data for Europe). Reconstruction of the ACL is commonly performed to restore stability to the knee and allow the patient to return to a healthy and active lifestyle. The past 2 decades have seen significant advancements in the ability to restore stability and function to an ACL deficient knee with a primary ACL reconstruction. Although the procedure and rehabilitation has become more predictable, it still requires many months of rehabilitation and time away from the sports. After committing the time, effort and expense of a primary ACL reconstruction, to have it then re-tear is not only a frustrating and discouraging event for all involved, but there is also growing evidence that the long-term health of the knee is then at even greater risk Recent prospective analysis of a multicenter cohort has shown failure rate after ACL reconstruction to be 3.0 % at 2 years and a systematic review of randomized- controlled trials showed this rate to be 3.6 % at short-term follow-up.
Revision ACL reconstruction is clinically challenging and associated with worse clinical outcomes than primary reconstructions, and a recent systematic review revealed a 13.7 % overall failure rate. Avoidable technical errors, including tunnel malposition, inadequate fixation, and failure to address concomitant malalignment and/or ligamentous injuries, have been implicated in 53–79 % of primary ACL graft failures. Due to the aforementioned reasons the development of an effective treatment to restore ACL function to avoid any postoperative complications is an important health and societal challenge. In current clinical practice, the ACL reconstruction plan is selected from a standard menu of options rather than customized to the unique characteristics of the patient. Furthermore, the treatment selection process is normally based on subjective clinical experience rather than objective prediction of post-treatment function. The net result is treatment methods that are less effective than desired at restoring lost knee joint’ s function. The aim of the present proposal is to develop a decision support system based on the integration of neuromusculoskeletal computer models with imaging (MRI, X-ray, ultrasound) and motion analysis data (kinematics, kinetics) to simulate the surgery and to improve customization, objectivity, and ultimately effectiveness of treatments for ACL reconstruction.
SafeACL Overall Objective
The aim of SafeACL project, is the development of a decision support system based on the integration of musculoskeletal computer models with imaging (MRI, Xray, ultrasound) and motion analysis data (kinematics, kinetics) to simulate the surgery and to improve customization, objectivity, and effectiveness of treatments for ACL reconstruction. The SafeACL system will allow the physician to operate in a virtual environment using an individualized musculoskeletal model that will be able to predict the effect of the surgery. The therapist will be able to test a variety of surgical scenarios (bone channel location, initial graft trend, graft fixation methodology, relative movement between the bone canal and graft) before performing the actual surgery. As a result, the customized surgical plan will be fed into a surgical assistant system that will guide the surgeon to reproduce the selected invasive scenario during the actual surgery.
With SafeACL, the orthopedic surgeon will be able to predict the outcome of a surgery in an innovative 3D environment (as opposed to two-dimensional images used in clinical practice), thus reducing surgical errors and postoperative complications of the patient.
The Project
The Approach
The development of the SafeACL medical decision support system will be implemented through a multidisciplinary approach aimed at developing state-of-the-art technology and exploiting the scientific knowledge of all the project partners.
During the first work package (WP1), the parameters, architecture and interfaces of the SafeACL system will be determined.
During the second work package (WP2) the validity of the human musculoskeletal models will be tested in dynamic athletic motions beyond walking using OpenSim’s musculoskeletal modeling software (www.simtk.org) and experimental motion analysis data in normal participants, using state-of-the-art scientific equipment.
Work package 3 (WP3) will develop an innovative three-dimensional image analysis technique that allows the extraction of the required parameters from clinical images for the production of personalized musculoskeletal models.
Work package 4 (WP4) will develop personalized musculoskeletal and finite element models. Then, a software for the interactive connection between the models and the surgeon physician will be developed in work package 5 (WP5) using virtual reality algorithms and three-dimensional imaging techniques. The surgeon will be able to parameterize each patient’s musculoskeletal model by simulating the intervention plan.
In WP5, the surgical effect of surgical intervention on the patient’s kinetic and kinematic model during daily and athletic activities will be assessed using individualized musculoskeletal models including the adjustments made to the knee joint after surgery. Predictions of the patient’s postoperative functioning are purely mathematical and therefore not usable by surgeons.
For this reason, an easy-to-use graphical environment will be created in work package 6 (WP6) to allow the orthopedic surgeon to interpret the results of surgical simulations.
Finally, a detailed feasibility study, work package 7 (WP7), will be developed by a specialized subcontractor for the new system, focusing on its optimal commercial exploitation and business models of exploitation.
Expected Impacts
For Physicians: simulation of surgery in a virtual environment; selection of the best procedure for the surgery, for each patient; assisted surgery.
- For Patients: personalized surgery, quicker restoration of ACL function, better qual- ity of life, reduced chance of failure of the surgery operation.
- For the Research community: development of innovative personalized musculoskel- etal models, development of interactive virtual surgical environment.
- For the National Health System: improvement of the services and products provided, reduction of hospitalization and rehabilitation costs.