Fluoroscopy-based tracking of femoral kinematics with statistical shape models

Precise knee kinematics assessment helps to diagnose knee pathologies and to improve the design of customized prosthetic components. The first step in identifying knee kinematics is to assess the femoral motion in the anatomical frame. However, no work has been done on pathological femurs, whose shape can be highly different from healthy ones

Component Placement in Hip and Knee Replacement Surgery: Device Development, Imaging and Biomechanics

Total joint replacement replaces the worn surfaces of arthritic joints with artificial components. This usually results in significant pain relief, but problems persist in some patients. An important contributor to postoperative complications following joint replacement is component malalignment. The goal of the work described is to improve component placement in total hip and knee arthroplasty. As one of the main objectives in this work, an adjustable mechanical device, called Optihip, was developed and tested to improve the accuracy of acetabular cup alignment in hip replacement surgery. An ex vivo study demonstrated the accuracy and feasibility of the device for guiding orientation and depth of the acetabular cup. With respect to knee replacement surgery, preoperative and postoperative weightbearing patellofemoral and tibiofemoral kinematics throughout the range of motion, using calibrated sequential-biplanar radiographic imaging at 8 flexion angles, are reported for nine subjects before and at least one year after total knee arthroplasty (TKA). Changes in the articular geometry of knee joints for the same nine subjects are also investigated by matching the three-dimensional (3D) implant models to the 3D bone-implant volume from computed-tomography (CT) imaging. Relationships between the subjects’ quality of life (QOL) and changes in knee articular geometry and kinematics are also evaluated. There were significant differences between pre-TKA and post-TKA kinematics in this pilot study, although not for all degrees of freedom. Patellofemoral and femoral analyses showed that the knee shape and geometry changed in numerous significant ways as a result of the TKA. There were also significant correlations between shape, kinematics and QOL parameters. Postoperative QOL in this cohort was better for a more lateralized proximal femoral groove, smaller changes in femoral condylar dimensions, more lateralized patellofemoral mediolateral translation and shift, less patellar tilt, more internal TF internal-external rotation and fewer individual shape and kinematic high/low values. Postoperative patellar tracking followed the femoral component groove more closely than the original preoperative tracking, suggesting that the femoral groove has more control over patellar tracking than the soft tissues

Restoration of articular geometry using current graft options for large glenoid bone defects in anterior shoulder instability

Purpose: The purpose of this cadaveric study was to compare standard and modified coracoid transfer procedures, bicortical and tricortical iliac crest autografts, and tibial plafond and glenoid allografts with respect to glenoid surface curvature restoration. Methods: Computed tomography scans of 8 cadaveric shoulders were acquired in 9 conditions: (1) intact, (2) 25% width defect, (3) classic Latarjet, (4) modified congruent-arc Latarjet, (5) tricortical iliac crest inner table, (6) outer table, (7) bicortical iliac crest, (8) distal tibia, and (9) glenoid allograft. Outcome measures included articular surface area, width, depth, axial and coronal radius of curvature, and subchondral articular step-off, analyzed in bone and soft-tissue window. Results: Reconstruction of the articular surface area was optimal with the glenoid allograft (99.4%), classic Latarjet (97.4%), and iliac crest bicortical graft (93.2%). Depth was best restored by the congruent-arc Latarjet (101.0%), tibial (98.9%), and glenoid (95.3%) allografts. Axial curvature was closely matched by the glenoid allograft (97.5%), classic Latarjet (108.7%), and iliac bicortical graft (91.2%). Coronal curvature was most accurately restored by the glenoid allograft (102.6%), the tibial allograft (115.0%), and the classic Latarjet (55.9%). The articular step-off was smallest using the glenoid allograft. Conclusions: Overall, glenoid allografts most accurately restored articular geometry. Alternative grafts provided restoration of some parameters but not others. Classic Latarjet performed well in axial and coronal curvature on average but exhibited large variability. Tibial allograft produced the poorest results in axial curvature, despite excellent coronal curvature reconstruction. The congruent-arc Latarjet did not restore the axial curvature accurately and overcorrected coronal curvature. Graft geometry must be weighed against availability, morbidity, and the role of additional stabilizers. Clinical Relevance: Accurate graft morphology may help prevent postoperative osteoarthritis. Grafts differ significantly regarding geometric parameters. The findings of this study will help surgeons select the most appropriate graft for glenoid reconstruction

Gaussian mixture models based 2D–3D registration of bone shapes for orthopedic surgery planning

In orthopedic surgery, precise kinematics assessment helps the diagnosis and the planning of the intervention. The correct placement of the prosthetic component in the case of knee replacement is necessary to ensure a correct load distribution and to avoid revision of the implant. 3D reconstruction of the knee kinematics under weight-bearing conditions becomes fundamental to understand existing in vivo loads and improve the joint motion tracking. Existing methods rely on the semiautomatic positioning of a shape previously segmented from a CT or MRI on a sequence of fluoroscopic images acquired during knee flexion. We propose a method based on statistical shape models (SSM) automatically superimposed on a sequence of fluoroscopic datasets. Our method is based on Gaussian mixture models, and the core of the algorithm is the maximization of the likelihood of the association between the projected silhouette and the extracted contour from the fluoroscopy image. We evaluated the algorithm using digitally reconstructed radiographies of both healthy and diseased subjects, with a CT-extracted shape and a SSM as the 3D model. In vivo tests were done with fluoroscopically acquired images and subject-specific CT shapes. The results obtained are in line with the literature, but the computational time is substantially reduced