Abstract
Introduction
The functional ante-inclination (AI) of the cup after total hip arthroplasty (THA) is a key component in the combined sagittal index (CSI) to predict joint stability after THA. To accurately predict AI, we deducted a mathematic algorithm between the radiographic anteversion (RA), radiographic inclincation (RI), pelvic tilting (PT), and AI. The current study aims (1) to validate the mathematic algorithm; (2) to convert the AI limits in the CSI index (standing AI ≤ 45°, sitting AI ≥ 41°) into coronal functional safe zone (CFSZ) and explore the influences of the stand-to-sit pelvic motion (PM) and pelvic incidence (PI) on CFSZ; (3) to locate a universal cup orientation that always fulfill the AI criteria of CSI safe zone for all patients or subgroups of PM(PM ≤ 10°, 10° < PM ≤ 30°, and PM > 30°) and PI (PI≤ 41°, 41°< PI ≤ 62°, and PI >62°), respectively.
Methods
A 3D printed phantom pelvic model was designed to simulate changing PT values. An acetabular cup was implanted with different RA, RI, and PT settings using robot assisted technique. We enrolled 100 consecutive patients who underwent robot assisted THA from April, 2019 to June, 2019 in our hospital. EOS images before THA and at 6-month follow-up were collected. AI angles were measured on the lateral view radiographs as the reference method. Mean absolute error (MAE), Bland-Altman analysis and linear regression were conducted to assess the accuracy of the AI algorithm for both the phantom and patient radiographic studies. The 100 patients were classified into three subgroups by PM and PI, respectively. Linear regression and ANOVA analysis were conducted to explore the relationship between the size of CFSZ, and PM and PI, respectively. Intersection of the CFSZ was conducted to identify if any universal cup orientation (RA, RI) existed for the CSI index.
Results
The mathematic algorithm for calculating AI based on RI, RA, and PT is highly accurate according to the phantom and patient radiographic study. CFSZ size corresponds linearly with PM (R² = 0.638) and PI (R² = 0.129), respectively. There are significant differences in the size of CFSZ, as well as in the intersection of CFSZ and LSZ, between the subgroups of PM and PI, respectively (P<0.017). There is no universal cup orientations could be identified to fulfill the AI limits of the CSI index for all the 100 patients or any of the three subgroups, according to either PM or PI.
Conclusions
The cup target orientation should be individualized. The validated algorithm between AI and RA, RI, and PT parameters can serve as the quantitative tool for patient-specific optimization of functional cup AI in different postures.
