Short-term outcome of artificial intelligence-assisted preoperative three-dimensional planning of total hip arthroplasty for developmental dysplasia of the hip compared to traditional surgery

Objectives: This study aims to assess the short-term outcome of total hip arthroplasty for treating developmental dysplasia of the hip (DDH) using artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning technology. Patients and methods: Between January 2020 and July 2022, a total of 61 patients with DDH (31 males, 30 females, mean age: 59.2 +/- 10.4 years; range, 35 to 78 years) were retrospectively analyzed. The patients were divided into two groups as those in the observation group of AI-assisted 3D preoperative planning technology (n=34) and the control group of traditional two-dimensional X-ray template planning technology (n=27). Perioperative data of the patients were recorded and analyzed. Results: All patients were followed for more than one year, and no hip dislocation, aseptic loosening, periprosthetic fracture, periprosthetic infection or revision occurred. The accuracy of the planning was based on the agreement between the preoperative planning model and the intraoperative model. The accuracy of preoperative planning for the acetabular prosthesis and femoral prosthesis in the observation group was significantly higher than in the control group. No statistically significant difference was found in the postoperative abduction (p= 0.416) and anteversion (p=0.225) between the groups. In the observation group, 91.2% of the acetabular cups were implanted within the Lewinnek safe zone (66.7% in the control group) and 88.2% were within the Callanan safe zone (63% in the control group). There was a statistically significant difference between the two groups in terms of the postoperative lower-limb length discrepancy (p=0.004), which was significantly improved in both groups compared to preoperative values (p<0.01 for all). The postoperative Harris hip score in both groups was significantly improved compared to preoperative scores (p< 0.01); however, there was no statistically significant difference between the two groups (p= 0.098). Conclusion: Our study results suggest that AI-assisted 3D preoperative planning is evidently more successful than traditional 2D X-ray template planning for predicting prosthesis size. This method seems to be advantageous in acetabular cup positioning, as well as in lower-limb length restoration.