General Prediction Theory for Anterior Cruciate Ligament Graft Sizing

Predicting hamstring graft size before anterior cruciate ligament (ACL) reconstruction is crucial to avoid subsequent graft failure. Our study aims to (1) develop a generalized algorithm to predict final ACL graft diameter for single- and double-tendon hamstring grafts consisting of any number of folds, (2) evaluate our algorithm with a regression model adjusting for patient and surgical factors, and (3) assess algorithm's specificity, sensitivity, and discriminative ability, defining adequate graft size as ≥9 mm.We conducted a retrospective review of 105 patients who underwent primary ACL reconstruction with either single- (semitendinosus or gracilis only) or double-tendon (both semitendinosus and gracilis) hamstring grafts from January 2023 to June 2024 at a tertiary institution. Magnetic resonance imaging (MRI) scans were independently measured by two junior members. The average of the measurements was taken. Predicted graft diameter is √(x·AB + y·CD), where A and B are the semitendinosus cross-sectional length and breadth, C and D are the gracilis cross-sectional length and breadth, and x and y are the number of semitendinosus and gracilis folds, respectively.Pearson correlation shows moderate correlation between predicted and actual graft diameters (<i>R</i> = 0.602, <i>p</i> < 0.01). Univariate and multivariate linear regression, adjusted for age, gender, body mass index (BMI), and graft type, indicate that males, overweight individuals, and those with single-tendon grafts are more likely to have larger actual graft diameters (<i>p</i> < 0.05). Our algorithm has a sensitivity of 95.8%, specificity of 69.7%, with excellent discriminative ability (AUC = 0.889). A high 82.9% agreement rate was achieved, with Cohen's kappa of 0.578 (<i>p</i> < 0.05).This study has demonstrated a practical generalized algorithm with high sensitivity (95.8%) to predict the final ACL graft diameter for single- and double-tendon hamstring grafts consisting of any number of folds using preoperative MRI measurements.