Proper component alignment is crucial for a successful total hip arthroplasty (THA). Some studies found safe cup orientations and corresponding stem antetorsions based on a defined desired range of motion (ROM) suitable for activities of daily living. These studies either used complex and time consuming 3D simulations or more simple mathematical formulas which cannot be extended to combined motions.

With the method introduced in this work, any arbitrary motion can be applied. The ROM specified as the ROM of the femur relative to the pelvis is transformed into the ROM of the prosthesis neck relative to the cup for each cup orientation. For this transformation, the orientation and design of the stem are considered. The comparison of the neck and cup orientations is done using a 2D mapping of a 3D spherical surface which reduces the complexity of the calculation.

We found that the femoral antetorsion as well as the neutral stem flexion and adduction have an influence on the resulting safe zone. The result is not just a combined anteversion but a combined orientation. For validating the plausibility of the algorithm, the resulting safe zones are compared to literature. Same results can be achieved using the same input data. Using this technique, a patient-specific safe zone based on the ROM can be derived and adjusted to the stem orientation.

For a successful total knee arthroplasty (TKA) and long prosthesis lifespan, correct alignment of the implant components as well as proper soft tissue balancing are of major importance. In order to overcome weaknesses of existing imaging modalities for TKA planning such as radiation exposure and lack of soft tissue visualisation (X-ray and CT) and high cost, long acquisition times and geometric distortion (MRI), it is investigated if ultrasound (US) imaging is a suitable alternative.

Currently, a reconstruction method of the bony knee morphology based on US imaging is developed at our research institute. For capturing the mechanical axis, being crucial for TKA planning, different approaches could be implemented. This work investigates whether a weight-bearing full leg X-ray registered with the local 3D-US knee dataset can be used for this purpose. Also, the impact of incorrect calibration data (i.e. uncalibrated X-rays) on the accuracy of the estimated mechanical axis is investigated.

A 3D-2D projective, feature-based registration algorithm was used to spatially align the 3D US-based model to the 2D X-ray image before transferring the mechanical axis from the X-ray to the model. For validation, a CT-based local model and its projection were used and an initial error in translation and rotation was added. Also, calibration parameters such as the centre ray position and the source-to-image-detector distance were altered. The estimation error of the mechanical axis was less than 1°, the median error lower than 0.1° in the frontal plane. Even if the calibration data is not available, the accuracy remains sufficient for TKA planning. In this study, idealised 2D and 3D image information was used. In the future, this method should be tested using clinical X-ray images and 3D-US data.