Preoperative prediction of anterior cruciate ligament tibial footprint size by anthropometric variables

The purpose of this study was to evaluate whether the ACL tibial footprint size can be predicted by anthropometric variables including height, weight, leg length, femur length, tibia length, and anteroposterior and mediolateral diameters of proximal tibia.

This study included 209 out of the 378 eligible patients. The inclusion criterion was ACL with normal gross appearance. Patients with conditions that could have affected the measurement were excluded: torn ACL, osteophyte formation around the ACL tibial attachment, presence of inflammatory arthritis, or history of knee joint infection. According to the above criteria, 169 patients were excluded from this study; 138 had torn ACL, 24 had osteophyte around the ACL footprint, 5 had history of rheumatoid arthritis, and 2 had history of previous knee joint infection. The ACL tibial footprint was carefully dissected and measured during total knee arthroplasty. Anthropometric variables regarding bone lengths were measured on radiography. The association of the ACL tibial footprint size (length and width) with anthropometric variables was analysed using simple and multiple linear regression analyses.

The height, weight, leg length, femur length, tibia length, and the size of proximal tibia were associated with the ACL tibial footprint length and width. The ACL tibial footprint length could be predicted by the equation using tibia length: ACL tibial footprint length = −9.361 + 0.759 * (tibia length in cm) (R ² = 0.44, P < 0.001) and width by the equation using weight and tibia length: ACL tibial footprint width = −0.5615 + 0.279 * (tibia length in cm) + 0.0333 * (weight in kgs) (R ² = 0.17, P < 0.001). The concordance correlation coefficient for the measured and predicted values of ACL tibial footprint length and width showed moderate and low agreement, respectively (0.61, 95 % CI 0.53–0.68; 0.30, 95 % CI 0.21–0.38).

The ACL tibial footprint length and width are associated with anthropometric variables, especially with tibial length. The predictive equation developed from this study can serve as supplementary guides to determine the surgical techniques and graft options in preoperative planning of an individual ACL reconstruction.

IV.