Standardizing ACL tunnel placement: an automated method for knee quadrant computation

Anatomical tunnel placement in the anterior cruciate ligament (ACL) reconstruction is essential for better functional recovery and reduced complications. However, subjective factors and ambiguous definitions reduce the accuracy and efficiency of quantifying ACL position on 3D models. This study aims to develop and validate a fully automated framework for standardized 3D quadrant coordinate computation of femoral and tibial ACL footprints, enabling objective preoperative planning and postoperative evaluation.

An nnUNet-based foundation network was fine-tuned to reconstruct distal femur and proximal tibia 3D models from CT or MRI data. Automated template registration and morphological analysis were used to determine anatomical planes and generate individualized quadrant coordinate systems. The pipeline was validated on both CT and MRI datasets, comparing location accuracy, calculation repeatability, and time efficiency against manual methods.

The 3D distances between the actual and automatic predicted centroids were 1.72 ± 0.94 mm and 1.47 ± 1.06 mm for femur and tibia, respectively, while the errors of manual method were 1.89 ± 1.42 mm and 2.11 ± 1.27 mm. The method achieved an average repeatability of 0.992 in quadrant calculations with different initializations, while the ICCs of two manual annotation were 0.961 (A), 0.946 (B), and 0.882 (A&B). The processing time for generating quadrant coordinate systems was significantly reduced to an average of 4.7 ± 1.3 s, compared to 8.5 ± 2.1 min for manual annotation.

This study presented the first fully automated, modality-independent method for 3D quadrant coordinate computation in knee surgery. The proposed framework delivers robust and standardized ACL anatomical locations across both CT and MRI data, enhancing the clinical efficiency of the preoperative planning and postoperative assessment of ACL reconstruction.