Zero-dose fluoroscopy-based close reduction and osteosynthesis of diaphyseal fracture of femurs

This paper presents a novel technique to create a computerized fluoroscopy with zero-dose image updates for computer-assisted fluoroscopy-based close reduction and osteosynthesis of diaphyseal fracture of femurs. With the novel technique, repositioning of bone fragments during close fracture reduction will lead to image updates in each acquired imaging plane, which is equivalent to using several fluoroscopes simultaneously from different directions but without any X-ray radiation. Its application facilitates the whole fracture reduction and osteosynthesis procedure when combining with the existing leg length and antetorsion restoration methods and may result in great reduction of the X-ray radiation to the patient and to the surgical team. In this paper, we present the approach for achieving such a technique and the experimental results with plastic bones.

Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.

Minimization of Intra-Operative Shaping of Orthopaedic Fixation Plates: A Population-Based Design

In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.

Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Comparison of six radiographic projections to assess femoral head/neck asphericity

Early radiographic detection of femoroacetabular impingement might prevent initiation and progression of osteoarthritis. The structural abnormality in femoral-induced femoroacetabular impingement (cam type) is frequently asphericity at the anterosuperior head/neck contour. To determine which of six radiographic projections (anteroposterior, Dunn, Dunn/45 degrees flexion, cross-table/15 degrees internal rotation, cross-table/neutral rotation, and cross-table/15 degrees external rotation) best identifies femoral head/neck asphericity, we studied 21 desiccated femurs; 11 with an aspherical femoral head/neck contour and 10 with a spherical femoral head/neck contour. To radiographically quantify femoral head asphericity, we measured the angle where the femoral head/neck leaves sphericity (angle alpha). The aspherical femoral head/neck contours had a greater maximum angle alpha (70 degrees ) compared with the spherical head/neck contours (50 degrees ). The angle alpha varied depending on the radiographic projection: it was greatest in the Dunn view with 45 degrees hip flexion (71 degrees +/- 10 degrees ) and least in the cross-table view in 15 degrees external rotation (51 degrees +/- 7 degrees ). Diagnosis of a pathologic femoral head/neck contour depends on the radiologic projection. The Dunn view in 45 degrees or 90 degrees flexion or a cross-table projection in internal rotation best show femoral head/neck asphericity, whereas anteroposterior or externally rotated cross-table views are likely to miss asphericity. Level of Evidence: Prognostic study, level II-1 (retrospective study).

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression

Reconstruction of shape and intensity from 2D x-ray images has drawn more and more attentions. Previously introduced work suffers from the long computing time due to its iterative optimization characteristics and the requirement of generating digitally reconstructed radiographs within each iteration. In this paper, we propose a novel method which uses a patient-specific 3D surface model reconstructed from 2D x-ray images as a surrogate to get a patient-specific volumetric intensity reconstruction via partial least squares regression. No DRR generation is needed. The method was validated on 20 cadaveric proximal femurs by performing a leave-one-out study. Qualitative and quantitative results demonstrated the efficacy of the present method. Compared to the existing work, the present method has the advantage of much shorter computing time and can be applied to both DXA images as well as conventional x-ray images, which may hold the potentials to be applied to clinical routine task such as total hip arthroplasty (THA).

End caps prevent nail migration in elastic stable intramedullary nailing in paediatric femoral fractures: a biomechanical study using synthetic and cadaveric bones.

End caps are intended to prevent nail migration (push-out) in elastic stable intramedullary nailing. The aim of this study was to investigate the force at failure with and without end caps, and whether different insertion angles of nails and end caps would alter that force at failure. Simulated oblique fractures of the diaphysis were created in 15 artificial paediatric femurs. Titanium Elastic Nails with end caps were inserted at angles of 45°, 55° and 65° in five specimens for each angle to create three study groups. Biomechanical testing was performed with axial compression until failure. An identical fracture was created in four small adult cadaveric femurs harvested from two donors (both female, aged 81 and 85 years, height 149 cm and 156 cm, respectively). All femurs were tested without and subsequently with end caps inserted at 45°. In the artificial femurs, maximum force was not significantly different between the three groups (p = 0.613). Push-out force was significantly higher in the cadaveric specimens with the use of end caps by an up to sixfold load increase (830 N, standard deviation (SD) 280 vs 150 N, SD 120, respectively; p = 0.007). These results indicate that the nail and end cap insertion angle can be varied within 20° without altering construct stability and that the risk of elastic stable intramedullary nailing push-out can be effectively reduced by the use of end caps.

Osteotomy of the distal femur. Surgical technique using the LCP Pediatric Condylar Plate 90°.

OBJECTIVE Correction of all kind of deformities at the distal part of the femur (supracondylar). INDICATIONS Flexion, extension osteotomies, and varus or valgus, and external or internal rotation osteotomies, and shortening osteotomies of the distal femur or combined surgical procedures (e.g., extension and de-rotation osteotomy). CONTRAINDICATIONS Osteotomy through unknown bony process. SURGICAL TECHNIQUE LCP system provides angular stable fixation. POSTOPERATIVE MANAGEMENT Without concomitant surgical procedures of soft tissue (e.g., patellar tendon shortening), early functional rehabilitation is possible with immediate weight bearing (35 kg for small fragment plates and 70 kg for large fragment plates). RESULTS The surgical procedure is safe and is associated with few complications. Overall complication rate in this series of patients was 3%.

Fully Automatic Segmentation of Hip CT Images

Automatic segmentation of the hip joint with pelvis and proximal femur surfaces from CT images is essential for orthopedic diagnosis and surgery. It remains challenging due to the narrowness of hip joint space, where the adjacent surfaces of acetabulum and femoral head are hardly distinguished from each other. This chapter presents a fully automatic method to segment pelvic and proximal femoral surfaces from hip CT images. A coarse-to-fine strategy was proposed to combine multi-atlas segmentation with graph-based surface detection. The multi-atlas segmentation step seeks to coarsely extract the entire hip joint region. It uses automatically detected anatomical landmarks to initialize and select the atlas and accelerate the segmentation. The graph based surface detection is to refine the coarsely segmented hip joint region. It aims at completely and efficiently separate the adjacent surfaces of the acetabulum and the femoral head while preserving the hip joint structure. The proposed strategy was evaluated on 30 hip CT images and provided an average accuracy of 0.55, 0.54, and 0.50 mm for segmenting the pelvis, the left and right proximal femurs, respectively.

Biomechanical Role of Bone Anisotropy Estimated on Clinical CT Scans by Image Registration

Image-based modeling is a popular approach to perform patient-specific biomechanical simulations. Accurate modeling is critical for orthopedic application to evaluate implant design and surgical planning. It has been shown that bone strength can be estimated from the bone mineral density (BMD) and trabecular bone architecture. However, these findings cannot be directly and fully transferred to patient-specific modeling since only BMD can be derived from clinical CT. Therefore, the objective of this study was to propose a method to predict the trabecular bone structure using a µCT atlas and an image registration technique. The approach has been evaluated on femurs and patellae under physiological loading. The displacement and ultimate force for femurs loaded in stance position were predicted with an error of 2.5% and 3.7%, respectively, while predictions obtained with an isotropic material resulted in errors of 7.3% and 6.9%. Similar results were obtained for the patella, where the strain predicted using the registration approach resulted in an improved mean squared error compared to the isotropic model. We conclude that the registration of anisotropic information from of a single template bone enables more accurate patient-specific simulations from clinical image datasets than isotropic model.

Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model

This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.