To review research progress on femoral attachment positioning during medial patellofemoral ligament (MPFL) reconstruction, so as to provide a reference for accurate positioning in clinic. The literature at home and abroad on femoral attachment positioning during MPFL reconstruction was extensively reviewed and summarized. MPFL is the main ligament that restricts patellar outward migration, so MPFL reconstruction is the main treatment for patellar dislocation, but the accuracy of intraoperative femoral attachment positioning will significantly affect the effectiveness. At present, there are three main methods for femoral attachment positioning in MPFL reconstruction, including imaging positioning, bony landmark positioning, and new technology. Among them, the main imaging positioning method is the "Schöttle point" method, but it has high requirements for fluoroscopic positioning, and can only be accurately positioned under standard lateral fluoroscopy of the femur. The bony landmark positioning method mainly locates the femoral attachment by touching or dissecting the bony landmarks such as adductor tubercles and medial epicondyle of femur, but its disadvantages are that the positioning is not accurate enough, the intraoperative visual field exposure requirements are high, and a large incision is required. In order to avoid the problem that the simple bony landmark positioning method, in recent years, the combination of bony landmarks combined with arthroscopy, three-dimensional (3D) printing technology, and robot-assisted positioning methods have begun to be used in clinical practice. New technology localization methods have shown good results by preparing guides before operation, planning positioning paths in advance, or directly using robots to assist positioning during operation. The accurate positioning of the femoral attachment in MPFL reconstruction is crucial, and the method of accurate and rapid intraoperative determination needs to be further improved and optimized. In the future, it is expected that the combination of computer image recognition correction technology and intraoperative position assistance will solve this problem.
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