The role of 3-dimensional preoperative planning for primary total hip arthroplasty based on artificial intelligence technology to different surgeons: A retrospective cohort study

Abstract

Preoperative planning with computed tomography (CT)-based 3-dimensiona (3D) templating has been achieved precise placement of hip components. This study investigated the role of the software (3-dimensional preoperative planning for primary total hip arthroplasty [THA] based on artificial intelligence technology, artificial intelligence hip [AIHIP]) for surgeons with different experience levels in primary THA. In this retrospective cohort study, we included patients, who had undergone THA with the help of the AIHIP, and matched to patients, who had undergone THA without the help of the AIHIP, by age and the doctor who operated on them. The subjects were divided into 4 groups, senior surgeon (Chief of Surgery) with AIHIP group, senior surgeon without AIHIP group, junior surgeon (Associate Chief of Surgery) with AIHIP group and junior surgeon without AIHIP group. The general data, imaging index, clinical outcomes and accuracy of stem size prediction and cup size prediction were retrospectively documented for all patients. There was a significant difference in discrepancy in leg length (P = .010), neck-shaft angle (P = .025) and femoral offset (P = .031) between the healthy side and the affected side, operation duration (P < .001), decrease in hemoglobin (Hb) per 24 hours (P = .046), intraoperative radiation exposure frequency (P < .050) and postoperative complications (overall P = .035) among the patients in junior surgeon group. No significant differences were found between senior surgeon groups with respect to discrepancy in leg length (P = .793), neck-shaft angle (P = .088)and femoral offset (P = .946) between the healthy side and the affected side, operation duration (P = .085), decrease in Hb per 24 hours (P = .952), intraoperative radiation exposure frequency (P = .094) and postoperative complications (overall P = .378). The stem sizes of 95% were accurately estimated to be within 1 stem size, and 97% of the cup size estimates were accurate to within 1 cup size in senior surgeon group with AIHIP. A total of 87% stem sizes were accurately estimated to be within 1 stem size, and 85% cup sizes were accurate to within 1 cup size in junior surgeon group with AIHIP. In conclusion, our study suggests that an AI-based preoperative 3D planning system for THA is a valuable adjunctive tool for junior doctor and should routinely be performed preoperatively.