The shape of a bone scraper: an in vitro pilot study using porcine bone chips.

Bone scrapers are commonly used to harvest autologous bone in oral and implant surgery. The angle of the cutting blade is a variable that distinguishes bone scrapers. In the present study, the impact of the angle of the cutting blade on the in vitro characteristics of harvested bone was determined. Bone scrapers with blade angles of 15°, 25°, 35°, 45°, and 55° were used to harvest porcine cortical mandibular bone. The number and characteristics of the cells that grew out from the bone chips were examined. The data showed that, independent of the angle of the cutting blade, viable cells were barely detectable in fresh bone grafts. However, cells with a fibroblastic morphology appeared within 1 week in the culture dishes. After 21 days, the number of cells did not differ significantly between the five preparations. Moreover, cells responded to incubation with bone morphogenetic protein 7 (BMP-7) with an increased alkaline phosphatase activity, irrespective of the preparation. The data suggest that bone scrapers with different cutting angles produce bone chips with comparable in vitro characteristics.

Size and shape of the lunate surface in different types of pincer impingement: theoretical implications for surgical therapy.

OBJECTIVE Acetabular rim trimming is indicated in pincer hips with an oversized lunate surface but could result in a critically decreased size of the lunate surface in pincer hips with acetabular malorientation. There is a lack of detailed three-dimensional anatomy of lunate surface in pincer hips. Therefore, we questioned how does (1) size and (2) shape of the lunate surface differ among hips with different types of pincer impingement? METHOD We retrospectively compared size and shape of the lunate surface between acetabular retroversion (48 hips), deep acetabulum (34 hips), protrusio acetabuli (seven hips), normal acetabuli (30 hips), and hip dysplasia (45 hips). Using magnetic resonance imaging (MRI) arthrography with radial slices we measured size in percentage of the femoral head coverage and shape using the outer (inner) center-edge angles and width of lunate surface. RESULTS Hips with retroversion had a decreased size and deep hips had normal size of the lunate surface. Both had a normal shape of the outer acetabular rim. Protrusio hips had an increased size and a prominent outer acetabular rim. In all three types of pincer hips the acetabular fossa was increased. CONCLUSION Size and shape of the lunate surface differs substantially among different types of pincer impingement. In contrast to hips with protrusio acetabuli, retroverted and deep hips do not have an increased size of the lunate surface. Acetabular rim trimming in retroverted and deep hips should be performed with caution. Based on our results, acetabular reorientation would theoretically be the treatment of choice in retroverted hips.

Plotting regression coefficients and other estimates

Graphical display of regression results has become increasingly popular in presentations and in scientific literature because graphs are often much easier to read than tables. Such plots can be produced in Stata by the marginsplot command (see [R] marginsplot). However, while marginsplot is versatile and flexible, it has two major limitations: it can only process results left behind by margins (see [R] margins), and it can handle only one set of results at a time. In this article, I introduce a new command called coefplot that overcomes these limitations. It plots results from any estimation command and combines results from several models into one graph. The default behavior of coefplot is to plot markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce other types of graphs. I illustrate the capabilities of coefplot by using a series of examples.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Parent – environmental interactions shape acoustic signatures in tree swallows: a cross-fostering experiment.

Acoustic signatures are common components of avian vocalizations and are important for the recognition of individuals and groups. The proximate mechanisms by which these signatures develop are poorly understood, however. The development of acoustic signatures in nestling birds is of particular interest, because high rates of extra-pair paternity or egg dumping can cause nestlings to be unrelated to at least one of the adults that are caring for them. In such cases, nestlings might conceal their genetic origins, by developing acoustic signatures through environmental rather than genetic mechanisms. In a cross-fostering experiment with tree swallows Tachycineta bicolor, we investigated whether brood signatures of nestlings that were about to fledge were attributable to their genetic/maternal origins or to their rearing environment. We found that the calls of cross-fostered nestlings did not vary based on their genetic/maternal origin, but did show some variation based on their rearing environment. Control nestlings that were not swapped, however, showed stronger brood signatures than either experimental group, suggesting that acoustic signatures develop through an interaction between rearing environment and genetic/maternal effects.

Diffusion-weighted MR imaging of upper abdominal organs: field strength and intervendor variability of apparent diffusion coefficients

PURPOSE To determine the variability of apparent diffusion coefficient (ADC) values in various anatomic regions in the upper abdomen measured with magnetic resonance (MR) systems from different vendors and with different field strengths. MATERIALS AND METHODS Ten healthy men (mean age, 36.6 years ± 7.7 [standard deviation]) gave written informed consent to participate in this prospective ethics committee-approved study. Diffusion-weighted (DW) MR imaging was performed in each subject with 1.5- and 3.0-T MR systems from each of three vendors at two institutions. Two readers independently measured ADC values in seven upper abdominal regions (left and right liver lobe, gallbladder, pancreas, spleen, and renal cortex and medulla). ADC values were tested for interobserver differences, as well as for differences related to field strength and vendor, with repeated-measures analysis of variance; coefficients of variation (CVs) and variance components were calculated. RESULTS Interreader agreement was excellent (intraclass coefficient, 0.876). ADC values were (77.5-88.8) ×10(-5) mm(2)/sec in the spleen and (250.6-278.5) ×10(-5) mm(2)/sec in the gallbladder. There were no significant differences between ADC values measured at 1.5 T and those measured at 3.0 T in any anatomic region (P >.10 for all). In two of seven regions at 1.5 T (left and right liver lobes, P < .023) and in four of seven regions at 3.0 T (left liver lobe, pancreas, and renal cortex and medulla, P < .008), intervendor differences were significant. CVs ranged from 7.0% to 27.1% depending on the anatomic location. CONCLUSION Despite significant intervendor differences in ADC values of various anatomic regions of the upper abdomen, ADC values of the gallbladder, pancreas, spleen, and kidney may be comparable between MR systems from different vendors and between different field strengths.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Quantitative analysis of imprint shape and its relation to mechanical properties measured by microindentation in bone

Microindentation in bone is a micromechanical testing technique routinely used to extract material properties related to bone quality. As the analysis of microindentation data is based on assumptions about the contact between sample and surface, the aim of this study was to quantify the topological variability of indentations in bone and examine its relationship with mechanical properties. Indentations were performed in dry human and ovine bone in axial and transverse directions and their topology was measured by atomic force microscopy. Statistical shape modeling of the residual imprint allowed to define a mean shape and to describe the variability in terms of 21 principal components related to imprint depth, surface curvature and roughness. The indentation profile of bone was found to be highly consistent and free of any pile up while differing mostly by depth between species and direction. A few of the topological parameters, in particular depth, showed significant but rather weak and inconsistent correlations to variations in mechanical properties. The mechanical response of bone as well as the residual imprint shape was highly consistent within each category. We could thus verify that bone is rather homogeneous in its micromechanical properties and that indentation results are not strongly influenced by small deviations from an ideally flat surface.