Evaluation of femur of orchiectomized guinea pigs by bone densitometry using dual-energy x-ray absortiometry (DXA) and mechanical testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of effective number of pulses on the morphological structure of teeth and bovine femur after femtosecond laser ablation

Femtosecond lasers have been widely used in laser surgery as an instrument for contact-free tissue removal of hard dental, restorative materials, and osseous tissues, complementing conventional drilling or cutting tools. In order to obtain a laser system that provides an ablation efficiency comparable to mechanical instruments, the laser pulse rate must be maximal without causing thermal damage. The aim of this study was to compare the different morphological characteristics of the hard tissue after exposure to lasers operating in the femtosecond pulse regime. Two different kinds of samples were irradiated: dentin from human extracted teeth and bovine femur samples. Different procedures were applied, while paying special care to preserving the structures. The incubation factor S was calculated to be 0.788 +/- 0.004 for the bovine femur bone. These results indicate that the incubation effect is still substantial during the femtosecond laser ablation of hard tissues. The plasma-induced ablation has reduced side effects, i.e., we observe less thermal and mechanical damage when using a superficial femtosecond laser irradiation close to the threshold conditions. In the femtosecond regime, the morphology characteristics of the cavity were strongly influenced by the change of the effective number of pulses. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.JBO.17.4.048001]

Biomechanical Performance of Flexible Intramedullary Nails With End Caps Tested in Distal Segmental Defects of Pediatric Femur Models

Background: Unstable distal femoral fractures in children are challenging lesions with restricted surgical options for adequate stabilization. Elastic nails have become popular for treating femoral shaft fractures, yet they are still challenging for using in distal fractures. The aim of this study was to test whether end caps (CAP) inserted into the nail extremity improved the mechanical stabilization of a segmental defect at the distal femoral metaphyseal-diaphyseal junction created in an artificial pediatric bone model. Methods: Two 3.5-mm titanium elastic nails (TEN) were introduced intramedullary into pediatric femur models, and a 7.0-mm-thick segmental defect was created at the distal diaphyseal-metaphyseal junction. Nondestructive 4-point bending, axial-bending, and torsion tests were conducted. After this, the end caps were inserted into the external tips of the nails and then screwed into the bone cortex. The mechanical tests were repeated. Stiffness, displacement, and torque were analyzed using the Wilcoxon nonparametric test for paired samples. Results: In the combined axial-bending tests, the TEN + CAP combination was 8.75% stiffer than nails alone (P < 0.01); in torsion tests, the TEN + CAP was 14% stiffer than nails alone (P < 0.01). In contrast, the 4-point bending test did not show differences between the methods (P = 0.91, stiffness; P = 0.51, displacement). Thus, the end caps contributed to an increase in the construct stability for torsion and axial-bending forces but not for 4-point bending forces. Conclusions: These findings indicate that end caps fitted to elastic nails may contribute to the stabilization of fractures that our model mimics (small distal fragment, bone comminution, and distal bone fragment loss).

Study of the osteoconductive capacity of hydroxyapatite implanted into the femur of ovariectomized rats

Osteoporosis is a global public health that affects postmenopausal women due to the deficiency of estrogen, a hormone that plays an important role in the microarchitecture of bone tissue. Osteoporosis predisposes to pathological bone fracture that can be repaired by conventional methods. However, depending on the severity and quantity of bone loss, the use of autogenous grafts or biomaterials such as hydroxyapatite might be necessary. The latter has received increasing attention in the medical field because of its good biological properties such as osteoconductivity and biocompatibility with bone tissue. The objective of this study was to evaluate using histologic and radiographic analyses, the osteogenic capacity of hydroxyapatite implanted into the femur of rats with ovariectomy-induced osteoporosis. Eighteen rats were divided into three groups with six animals in each: group nonovariectomized, bilaterally ovariectomized not receiving estrogen replacement therapy, and bilaterally ovariectomized submitted to estrogen replacement therapy. Defects were created experimentally in the distal epiphysis of the femur with a surgical drill and filled with porous hydroxyapatite granules. The animals were sacrificed 8 weeks after surgery. The volume of newly formed bone in the implant area was quantified by morphometrical methods. The results were analyzed by ANOVA followed by the Tukey test (P < 0.05). The hydroxyapatite granules showed good radiopacity. Histological analysis revealed less quantity of newly formed bone in the ovariectomized group not submitted to hormone replacement therapy. In conclusion, bone neoformation can be expected even in bones compromised by estrogen deficiency, but the quantity and velocity of bone formation are lower. Microsc. Res. Tech., 2011. (c) 2011 Wiley Periodicals, Inc.

Diversity of the proximal femur in humans: morphological variations of the head-neck junction

The proximal femur is a high-diversity region of the human skeleton, especially at the anterior junction between head and neck, where various bony morphologies have been recognized since mid nineteenth century. Classical literature on this topic is chaotic and contradictory, making almost impossible the comparison of data from different researches. Starting from an extensive bibliographic review, the first standardized method to score these traits has been created. This method allows representing both the anatomical diversity of the region already described in literature and a part of variability not considered before, giving few and univocal definitions and allowing to collect comparable data. The method has been applied to three identified and five archaeological European skeletal collections, with the aim of investigating the distribution of these features by sex, age and side, in different places and time periods. It has also been applied to 3D digital reconstructions of femurs from CT scan files of coxo-femoral joints from fresh cadavers. In addition to the osseous traits described in the standardized method, the presence and frequency of some features known as herniation pits have been scored both on bones and on CT scans. The various osseous traits of the proximal femur are present at similar frequencies in skeletal samples from different countries and different historical periods, even if with clear local differentiation. Some of the features examined show significant trends related to their distribution by gender and age. Some hypotheses are proposed about the etiology of these morphologies and their possible implication with the acquisition of bipedalism in Humans. It is therefore highlighted the possible relation of some of these traits with the development of disorders of the hip joint. Moreover, it is not recommended the use of any of these features as a specific activity-related marker.

Validity of an automatic measure protocol in distal femur for allograft selection from a three-dimensional virtual bone bank system

Osteoarticular allograft is one possible treatment in wide surgical resections with large defects. Performing best osteoarticular allograft selection is of great relevance for optimal exploitation of the bone databank, good surgery outcome and patient’s recovery. Current approaches are, however, very time consuming hindering these points in practice. We present a validation study of a software able to perform automatic bone measurements used to automatically assess the distal femur sizes across a databank. 170 distal femur surfaces were reconstructed from CT data and measured manually using a size measure protocol taking into account the transepicondyler distance (A), anterior-posterior distance in medial condyle (B) and anterior-posterior distance in lateral condyle (C). Intra- and inter-observer studies were conducted and regarded as ground truth measurements. Manual and automatic measures were compared. For the automatic measurements, the correlation coefficients between observer one and automatic method, were of 0.99 for A measure and 0.96 for B and C measures. The average time needed to perform the measurements was of 16 h for both manual measurements, and of 3 min for the automatic method. Results demonstrate the high reliability and, most importantly, high repeatability of the proposed approach, and considerable speed-up on the planning.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

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.

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.