A personalized insertion centers preoperative positioning method for minimally invasive surgery of cruciate ligament reconstruction.

In the surgery of knee cruciate ligament repair, how to accurately and personalized obtain cruciate ligament insertion centers is the key issue and a great challenge for surgeons. Current artificial judgment is often with deviation, which increases the risk of surgical failure, complications, and the need for a second surgery. Surgical failure can cause imbalanced force on the knee joint (even limping). In this paper, we propose a personalized preoperative positioning method framework of cruciate ligament insertion centers. We focus on locating the insertion centers and verifying the accuracy of the results. The main steps of the method are as follows. First, we propose a new network model W-UNet to better segment accurate bone regions and small ligament regions from MRI. Second, based on RANSAC algorithm and ICP algorithm, MRI bone model and CT bone model are registered. Third, based on the extracted bone and ligament models, we propose an accurate and personalized method for locating the insertion centers. Fourth, we propose a method based on the principle of calculus, using broken lines instead of curves, to solve the problem of ligament reconstruction blocked by intercondylar protrusions. Finally, the length of cruciate ligament with different flexion angles verifies the accuracy of insertion centers. Preoperative personalized insertion centers preoperative positioning can be performed according to the patient's MRI and CT images. Validation experiments proved the accuracy and robustness of this method. Surgeons can use this framework to accurately obtain personalized preoperative insertion centers location for target patients. This framework provides a reasonable and feasible technical means for locating and marking cruciate ligament insertion centers. It effectively solves the problem of difficult ligament centers localization in clinical surgery and reduces the risk of surgical failure. [ABSTRACT FROM AUTHOR]