title: Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging.
abstract: Statistical shape modelling potentially provides a powerful tool for generating patient-specific, 3D representations of bony anatomy for computer-aided orthopaedic surgery (CAOS) without the need for a preoperative CT scan. Furthermore, freehand 3D ultrasound (US) provides a non-invasive method for digitising bone surfaces in the operating theatre that enables a much greater region to be sampled compared with conventional direct-contact (i.e., pointer-based) digitisation techniques. In this paper, we describe how these approaches can be combined to simultaneously generate and register a patient-specific model of the femur and pelvis to the patient during surgery. In our implementation, a statistical deformation model (SDM) was constructed for the femur and pelvis by performing a principal component analysis on the B-spline control points that parameterise the freeform deformations required to non-rigidly register a training set of CT scans to a carefully segmented template CT scan. The segmented template bone surface, represented by a triangulated surface mesh, is instantiated and registered to a cloud of US-derived surface points using an iterative scheme in which the weights corresponding to the first five principal modes of variation of the SDM are optimised in addition to the rigid-body parameters. The accuracy of the method was evaluated using clinically realistic data obtained on three intact human cadavers (three whole pelves and six femurs). For each bone, a high-resolution CT scan and rigid-body registration transformation, calculated using bone-implanted fiducial markers, served as the gold standard bone geometry and registration transformation, respectively. After aligning the final instantiated model and CT-derived surfaces using the iterative closest point (ICP) algorithm, the average root-mean-square distance between the surfaces was 3.5mm over the whole bone and 3.7mm in the region of surgical interest. The corresponding distances after aligning the surfaces using the marker-based registration transformation were 4.6 and 4.5mm, respectively. We conclude that despite limitations on the regions of bone accessible using US imaging, this technique has potential as a cost-effective and non-invasive method to enable surgical navigation during CAOS procedures, without the additional radiation dose associated with performing a preoperative CT scan or intraoperative fluoroscopic imaging. However, further development is required to investigate errors using error measures relevant to specific surgical procedures.
authors.affiliation: Centre for Medical Image Computing, Department of Medical Physics and Bioengineering, 2nd Floor, Malet Place Engineering Building, University College London, Gower Street, London WC1E 6BT, United Kingdom. d.barratt@ucl.ac.uk
authors.forename: Dean C
authors.initials: DC
authors.lastname: Barratt
authors.forename: Carolyn S K
authors.initials: CS
authors.lastname: Chan
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Edwards
authors.forename: Graeme P
authors.initials: GP
authors.lastname: Penney
authors.forename: Mike
authors.initials: M
authors.lastname: Slomczykowski
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Carter
authors.forename: David J
authors.initials: DJ
authors.lastname: Hawkes
mesh_terms: D002102:Cadaver; D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional; D015233:Models, Statistical; D010388:Pelvis / Q000000981:diagnostic imaging*; D011859:Radiography; D014463:Ultrasonography