Artificially Intelligent Three-Dimensionally-Printed Patient-Specific Instrument Improves Total Hip Arthroplasty Accuracy

Abstract

BackgroundPatient-specific instrumentation (PSI) has the potential to improve the accuracy of implant positioning in total hip arthroplasty (THA). This prospective clinical study aimed to develop artificial intelligence to increase PSI production efficiency and assess accuracy, clinical outcomes, and learning curves. MethodsA convolutional neural network was applied to automatically process computer tomography images. PSI size and position were designed to guide the acetabular preparation and femoral neck resection. Thirty patients who underwent PSI-assisted THAs were matched to thirty patients who underwent free-hand THAs, and the component positions, as well as radiographic and clinical outcomes were analyzed. ResultsPSI-assisted THA was significantly more accurate than free-hand THA at achieving the target component position. The mean absolute errors of cup inclination (P = .004) and anteversion (P < .001) were significantly smaller in the PSI group with fewer outliers. Calcar length (P = .002) and neck length (P = .026) were also more accurate in the PSI group. The leg length discrepancy was significantly lower in the PSI group (P = .002). There were no significant differences in operation time, blood loss, leg length discrepancy, or cup position among the first, second, and last 10 cases. ConclusionPSI-assisted THA offered more accurate component positions and better radiographic outcomes than free-hand THA. There was no evidence of a learning curve. Our findings suggest that PSI is a convenient and practical option to help surgeons achieve accurate surgical outcomes.