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General Orthopaedics

ULTRASOUND BASED APP DETERMINATION FOR COMPUTER-ASSISTED THAS OPERATED IN LATERAL APPROACH

The International Society for Computer Assisted Orthopaedic Surgery (CAOS)



Abstract

Tracked B-mode ultrasound (US) potentially provides a non-invasive and radiation-free alternative to percutaneous pointer digitization for intra-operative determination of the anterior pelvis plane (APP). However, most of the published approaches demand a direct access to the corresponding landmarks, which can only be presumed for surgical approaches with the patient in supine position. In order to avoid any change of the clinical routine for total hip arthroplasties (THAs), we propose a new method to determine the pelvic orientation, which could be performed in lateral position.

Our proposed method is based on the acquisition of ultrasound images of the ipsilateral hemi-pelvis, namely the posterior superior iliac spines (PSISs) and iliac crest region. The US images are tracked by a navigation system and further processed to extract three-dimensional point clouds. As only one side of the pelvis is accessible, we estimate the symmetry plane (midsagittal plane) of the pelvis based on additionally digitized bilateral anterior superior iliac spine (ASIS) landmarks. This symmetry plane is further used to mirror the ipsilateral US-derived points to the contralateral side of the pelvis and to register and instantiate a pelvic SSM constructed from 30 CT-scans.

The proposed registration method was evaluated using two plastic pelvis models and two cadaveric pelvises together with special custom-made silicone phantoms to simulate the missing soft-tissue. In each trial, the required data were collected with the pelvis rigidly fixed in lateral decubitus position together with ground truth APP landmarks. A registration error of 3.48° ± 1.10° was found for the anteversion angle, while the inclination angle could be reconstructed with a mean error of 1.26° ± 1.62°.

The performed in-vitro experiments showed reasonably good results, taking the sparsity of the input point clouds into consideration.