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Accuracy analysis of artificial intelligence-assisted three-dimensional preoperative planning in total hip replacement

OBJECTIVES: This study aims to assess the outcome of total hip arthroplasty (THA) using artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning technology in terms of predicting prosthesis size, acetabular cup positioning, and lowerlimb length restoration. PATIENTS AND MET...

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Detalles Bibliográficos
Autores principales: Wu, Long, Zhao, Xin, Lu, Zhi-Dong, Yang, Yong, Ma, Long, Li, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bayçınar Medical Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546848/
https://www.ncbi.nlm.nih.gov/pubmed/37750257
http://dx.doi.org/10.52312/jdrs.2023.1059
Descripción
Sumario:OBJECTIVES: This study aims to assess the outcome of total hip arthroplasty (THA) using artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning technology in terms of predicting prosthesis size, acetabular cup positioning, and lowerlimb length restoration. PATIENTS AND METHODS: Between January 2020 and July 2022, a total of 161 patients (101 males, 60 females; mean age: 57.6±10.5 years; range, 31 to 80 years) who underwent primary unilateral THA were retrospectively analyzed. The patients were divided into two groups as those who were treated with AI-assisted 3D preoperative planning technology (the observation group, n=95) and patients who were treated with traditional two-dimensional (2D) X-ray template planning technology (the control group, n=66). RESULTS: The accuracy of the planning was based on the consistency of the preoperative planning and intraoperative models. The difference between the observation group and the control group was statistically significant in terms of the accuracy of the preoperative planning of acetabular prostheses (54% vs. 38%, p=0.048) and femoral prostheses (64% vs. 44%, p=0.011), with both values significantly higher in the observation group. The mean inclination angle, anteversion angle, and limb length discrepancy (LLD) in the observation group were 36.85°±4.82°, 12.10°±5.33°, and 2.18±2.70 mm, respectively, while those in the control group were 35.06°±6.07°, 10.95°±5.09°, and 4.42±3.85 mm, respectively. There was a statistically significant difference between the two groups in terms of inclination angle and LLD (p<0.05 for both), but there was no significant difference in terms of anteversion angle (p>0.05). In the observation group, 86.3% (82/95) of acetabular cups were implanted within the Lewinnek safe zone (72.7% [48/66] in the control group), while 83.2% (79/95) were within the Callanan safe zone (69.7% [46/66] in the control group), with both values higher in the observation group (p<0.05). CONCLUSION: Overall, AI-assisted 3D preoperative planning is superior to traditional 2D X-ray template planning for predicting prosthesis size, and it also has the advantage in terms of acetabular cup positioning and lower-limb length restoration.