Radiographic assessment of the cup orientation after total hip arthroplasty: a literature review.

Optimal acetabular cup orientation is of substantial importance to good long-term function and low complication rates after total hip arthroplasty (THA). The radiographic anteversion (RA) and inclination (RI) angles of the cup are typically studied due to the practicability, simplicity, and ease of interpretation of their measurements. A great number of methods have been developed to date, most of which have been performed on pelvic or hip anteroposterior radiographs. However, there are primarily two influencing factors for these methods: X-ray offset and pelvic rotation. In addition, there are three types of pelvic rotations about the transverse, longitudinal, and anteroposterior axes of the body. Their effects on the RA and RI angles of the cup are interactively correlated with the position and true orientation of the cup. To date, various fitted or analytical models have been established to disclose the correlations between the X-ray offset and pelvic rotation and the RA and RI angles of the cup. Most of these models do not incorporate all the potential influencing parameters. Advanced methods for performing X-ray offset and pelvic rotation corrections are mainly performed on a single pelvic AP radiograph, two synchronized radiographs, or a two-dimensional/three-dimensional (2D-3D) registration system. Some measurement systems, originally developed for evaluating implant migration or wear, could also be used for correcting the X-ray offset and pelvic rotation simultaneously, but some drawbacks still exist with these systems. Above all, the 2D-3D registration technique might be an alternative and powerful tool for accurately measuring cup orientation. In addition to the current methods used for postoperative assessment, navigation systems and augmented reality are also used for the preoperative planning and intraoperative guidance of cup placement. With the continuing development of artificial intelligence and machine learning, these techniques could be incorporated into robot-assisted orthopaedic surgery in the future.