Statistically Deformable 2D/3D Registration for Estimating Post-operative Cup Orientation from a Single Standard AP X-ray Radiograph

Abstract

The widely used procedure of estimating post-operative cup orientation based on a single standard AP X-ray radiograph is known inaccurate, largely due to the wide variability in individual pelvic orientation relative to X-ray plate. CT-based 2D/3D rigid image registration methods have been developed to measure post-operative cup orientation. Although encouraging results have been reported, their extensive usage in clinical routine is still limited. This may be explained by their requirement of having a CT study of the patient at some point during treatment, which is not available for vast majority of Total Hip Arthroplasty procedures performed nowadays. To address this limitation, this article proposes a statistically deformable 2D/3D registration approach for estimating post-operative cup orientation. No CT study of the patient is required any more. Compared to ground truths established from post-operative CT images, the cup orientations measured by the present technique in a cadaver experiment showed differences of 1.7 +/- 1.4 degrees for anteversion and difference of 1.5 +/- 1.5 degrees for inclination. When the present technique was evaluated on patients' datasets, differences of 2.2 +/- 1.3 degrees and differences of 2.0 +/- 0.8 degrees were found for the anteversion and the inclination, respectively. The experimental results, though still preliminary, demonstrated the efficacy of the present approach.

Advanced Computational Framework for the Automatic Analysis of the Acetabular Morphology from the Pelvic Bone Surface for Hip Arthroplasty Applications

“…In addition ad hoc acquisition protocols are mandatory to increase the bone-tissue interface contrast. It should be remarked that some recent studies on automated methodologies for bone surface reconstruction from CT scans 11,20 and even from low dose digital stereoradiography 21,41 showed accuracy comparable to manual contouring. In particular, a methodology based on statistical shape models and deformable registration was recently proposed, which discloses the possibility of reconstruct the 3D geometry of the pelvis bone from a single standard AP X-ray radiograph.…”

“…In particular, a methodology based on statistical shape models and deformable registration was recently proposed, which discloses the possibility of reconstruct the 3D geometry of the pelvis bone from a single standard AP X-ray radiograph. 41 In conclusion, the proposed CF yields the automatic and repeatable estimation of the acetabular parameters, features a standardization of the parameter measurement, dramatically reduces outliers, sensibly decreases detection time and indirectly equalizes the detection performance among operators (thus minimizing the difference between experienced and novice operators). In synthesis, the outcome of this work is consistent with innovative methodologies emerging in orthopedic applications, which disclose automatic surgery planning procedures with a number of benefits with respect to conventional clinical practice.…”

Mean-shifted surface curvature algorithm for automatic bone shape segmentation in orthopedic surgery planning: a sensitivity analysis

“…Statistical models of bone structures have been investigated extensively with the aim of enhancing automation in CT and MR image segmentation [6][7][8][9][10][11][12] and reconstructing patientspecific shape models from a small number of X-ray images or even from a single image [13][14][15]. Innovative methods for bone shape analysis have been applied to 3D mesh segmentation and clinical feature detection [16][17][18][19][20][21].…”

A Survey on Statistical Modeling and Machine Learning Approaches to Computer Assisted Medical Intervention: Intraoperative Anatomy Modeling and Optimization of Interventional Procedures

“…Among them, Zheng et al combined SSMs (Mahalanobis regularization) with the regularization using Mercer kernels [26] to further improve the reconstruction accuracy [24]. More recently, 3D shape reconstruction from a single uncalibrated X-ray image was developed for the pelvis [27], [28] and vertebra [29].…”