Background: A fully automated artificial intelligence-based tool was developed to detect and quantify femoral component subsidence between serial radiographs. However, it did not account for measurement errors due to leg position differences, such as rotation or flexion, between comparative radiographs. If there are small differences in rotation or flexion of the leg between comparative radiographs, the impact on subsidence measurement is unclear.
Methods: Twenty-five primary total hip arthroplasty procedures were performed by 3 fellowship-trained arthroplasty surgeons using a direct anterior approach. A Hana table allowed precise changes in femur position. Final fluoroscopic images were collected with rotational and flexion changes applied to the femur without moving the C-arm. Subsidence values were manually measured and compared across different positions.
Results: Variations in greater trochanter to tip of the stem measurements between the neutral position and rotations were minimal, measuring <1 mm on an absolute scale and <1% on a relative scale. These differences decreased as the femur was rotated from an external rotation of 20° to an internal rotation of 20°. Notable variances exceeding 5 mm were observed in the 10° flexion position compared to neutral.
Conclusions: Minor changes (20° or less) in leg rotation between serial radiographs are unlikely to significantly affect the greater trochanter to tip of the stem measurement, whereas flexion is highly impactful. These findings suggest that the fully automated artificial intelligence-based tool for detecting and quantifying femoral component subsidence is robust against rotational variations but may be susceptible to significant measurement errors if there are considerable changes in leg flexion between comparative radiographs.
Keywords: Artificial intelligence; Automatic calculator; Prosthesis loosening; Radiographic measurements; Subsidence; Total hip arthroplasty.
© 2024 The Authors.