Synchrotron x ray induced axonal transections in the brain of rats assessed by high-field diffusion tensor imaging tractography

Since approximately two thirds of epileptic patients are non-eligible for surgery, local axonal fiber transections might be of particular interest for them. Micrometer to millimeter wide synchrotron-generated X-ray beamlets produced by spatial fractionation of the main beam could generate such fiber disruptions non-invasively. The aim of this work was to optimize irradiation parameters for the induction of fiber transections in the rat brain white matter by exposure to such beamlets. For this purpose, we irradiated cortex and external capsule of normal rats in the antero-posterior direction with a 4 mm×4 mm array of 25 to 1000 µm wide beamlets and entrance doses of 150 Gy to 500 Gy. Axonal fiber responses were assessed with diffusion tensor imaging and fiber tractography; myelin fibers were examined histopathologically. Our study suggests that high radiation doses (500 Gy) are required to interrupt axons and myelin sheaths. However, a radiation dose of 500 Gy delivered by wide minibeams (1000 µm) induced macroscopic brain damage, depicted by a massive loss of matter in fiber tractography maps. With the same radiation dose, the damage induced by thinner microbeams (50 to 100 µm) was limited to their paths. No macroscopic necrosis was observed in the irradiated target while overt transections of myelin were detected histopathologically. Diffusivity values were found to be significantly reduced. A radiation dose ≤ 500 Gy associated with a beamlet size of < 50 µm did not cause visible transections, neither on diffusion maps nor on sections stained for myelin. We conclude that a peak dose of 500 Gy combined with a microbeam width of 100 µm optimally induced axonal transections in the white matter of the brain.

In-situ X-ray micro-diffraction studies of heterogeneous interfaces between cementitious materials and geological formations

In the present study the challenge of analyzing complex micro X-ray diffraction (microXRD) patterns from cement–clay interfaces has been addressed. In order to extract the maximum information concerning both the spatial distribution and the crystal structure type associated with each of the many diffracting grains in heterogeneous, polycrystalline samples, an approach has been developed in which microXRD was applied to thin sections which were rotated in the X-ray beam. The data analysis, performed on microXRD patterns collected from a filled vein of a cement–clay interface from the natural analogue in Maqarin (Jordan), and a sample from a two-year-old altered interface between cement and argillaceous rock, demonstrate the potential of this method.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

Microstructural and mechanical characterization of contemporary lingual orthodontic brackets.

OBJECTIVES To investigate the composition and the microstructural and mechanical characterization of three different types of lingual brackets. MATERIALS AND METHODS Incognito™ (3M Unitek), In-Ovation L (DENTSPLY GAC) and STb™ (Light Lingual System, ORMCO) lingual brackets were studied under the scanning electron microscope employing backscattered electron imaging and their elemental composition was analysed by energy-dispersive X-ray microanalysis. Additionally, Vickers hardness was assessed using a universal hardness-testing machine, and the indentation modulus was measured according to instrumented indentation test. Two-way analysis of variance was conducted employing bracket type and location (base and wing) as discriminating variable. Significant differences among groups were allocated by post hoc Student-Newman-Keuls multiple comparison analysis at 95% level of significance. RESULTS Three different phases were identified for Incognito and In-Ovation L bracket based on mean atomic number contrast. On the contrary, STb did not show mean atomic contrast areas and thus it is recognized as a single phase. Incognito is a one-piece bracket with the same structure in wing and base regions. Incognito consists mainly of noble metals while In-Ovation L and STb show similar formulations of ferrous alloys in wing and base regions. No significant differences were found between ferrous brackets in hardness and modulus values, but there were significant differences between wing and base regions. Incognito illustrated intermediate values with significant differences from base and wing values of ferrous brackets. CONCLUSIONS/IMPLICATIONS Significant differences exist in microstructure, elemental composition, and mechanical properties among the brackets tested; these might have a series of clinical implications during mechanotherapy.

X-ray image calibration and its application to clinical orthopedics.

X-ray imaging is one of the most commonly used medical imaging modality. Albeit X-ray radiographs provide important clinical information for diagnosis, planning and post-operative follow-up, the challenging interpretation due to its 2D projection characteristics and the unknown magnification factor constrain the full benefit of X-ray imaging. In order to overcome these drawbacks, we proposed here an easy-to-use X-ray calibration object and developed an optimization method to robustly find correspondences between the 3D fiducials of the calibration object and their 2D projections. In this work we present all the details of this outlined concept. Moreover, we demonstrate the potential of using such a method to precisely extract information from calibrated X-ray radiographs for two different orthopedic applications: post-operative acetabular cup implant orientation measurement and 3D vertebral body displacement measurement during preoperative traction tests. In the first application, we have achieved a clinically acceptable accuracy of below 1° for both anteversion and inclination angles, where in the second application an average displacement of 8.06±3.71 mm was measured. The results of both applications indicate the importance of using X-ray calibration in the clinical routine.

Stress-induced cortisol secretion impairs detection performance in x-ray baggage screening for hidden weapons by screening novices

Aviation security strongly depends on screeners' performance in the detection of threat objects in x-ray images of passenger bags. We examined for the first time the effects of stress and stress-induced cortisol increases on detection performance of hidden weapons in an x-ray baggage screening task. We randomly assigned 48 participants either to a stress or a nonstress group. The stress group was exposed to a standardized psychosocial stress test (TSST). Before and after stress/nonstress, participants had to detect threat objects in a computer-based object recognition test (X-ray ORT). We repeatedly measured salivary cortisol and X-ray ORT performance before and after stress/nonstress. Cortisol increases in reaction to psychosocial stress induction but not to nonstress independently impaired x-ray detection performance. Our results suggest that stress-induced cortisol increases at peak reactivity impair x-ray screening performance.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

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.

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Cephalometric analysis is an essential clinical and research tool in orthodontics for the orthodontic analysis and treatment planning. This paper presents the evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge, held at the IEEE International Symposium on Biomedical Imaging 2014 with an on-site competition. The challenge was set to explore and compare automatic landmark detection methods in application to cephalometric X-ray images. Methods were evaluated on a common database including cephalograms of 300 patients aged six to 60 years, collected from the Dental Department, Tri-Service General Hospital, Taiwan, and manually marked anatomical landmarks as the ground truth data, generated by two experienced medical doctors. Quantitative evaluation was performed to compare the results of a representative selection of current methods submitted to the challenge. Experimental results show that three methods are able to achieve detection rates greater than 80% using the 4 mm precision range, but only one method achieves a detection rate greater than 70% using the 2 mm precision range, which is the acceptable precision range in clinical practice. The study provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.