Radiation dose optimized lateral expansion of the field of view in synchrotron radiation X-ray tomographic microscopy

Volumetric data at micrometer level resolution can be acquired within a few minutes using synchrotron-radiation-based tomographic microscopy. The field of view along the rotation axis of the sample can easily be increased by stacking several tomograms, allowing the investigation of long and thin objects at high resolution. On the contrary, an extension of the field of view in the perpendicular direction is non-trivial. This paper presents an acquisition protocol which increases the field of view of the tomographic dataset perpendicular to its rotation axis. The acquisition protocol can be tuned as a function of the reconstruction quality and scanning time. Since the scanning time is proportional to the radiation dose imparted to the sample, this method can be used to increase the field of view of tomographic microscopy instruments while optimizing the radiation dose for radiation-sensitive samples and keeping the quality of the tomographic dataset on the required level. This approach, dubbed wide-field synchrotron radiation tomographic microscopy, can increase the lateral field of view up to five times. The method has been successfully applied for the three-dimensional imaging of entire rat lung acini with a diameter of 4.1 mm at a voxel size of 1.48 microm.

X-ray phase contrast imaging of metallized and non-metallized biological samples

Imaging of biological samples has been performed with a variety of techniques for example electromagnetic waves, electrons, neutrons, ultrasound and X-rays. Also conventional X-ray imaging represents the basis of medical diagnostic imaging, it remains of limited use in this application because it is based solely on the differential absorption of X-rays by tissues. Coherent and bright photon beams, such as those produced by third-generation synchrotron X-ray sources, provide further information on subtle X-ray phase changes at matter interfaces. This complements conventional X-ray absorption by edge enhancement phenomena. Thus, phase contrast imaging has the potential to improve the detection of structures on images by detecting those structures that are invisible with X-ray absorption imaging. Images of a weakly absorbing nylon fibre were recorded in in-line holography geometry using a high resolution low-noise CCD camera at the ESRF in Grenoble. The method was also applied to improve image contrast for images of biological tissues. This paper presents phase contrast microradiographs of vascular tree casts and images of a housefly. These reveal very fine structures, that remain invisible with conventional absorption contrast only.

Irradiation of intracerebral 9L gliosarcoma by a single array of microplanar x-ray beams from a synchrotron: balance between curing and sparing

The purpose of this work was the understanding of microbeam radiation therapy at the ESRF in order to find the best compromise between curing of tumors and sparing of normal tissues, to obtain a better understanding of survival curves and to report its efficiency. This method uses synchrotron-generated x-ray microbeams. Rats were implanted with 9L gliosarcomas and the tumors were diagnosed by MRI. They were irradiated 14 days after implantation by arrays of 25 microm wide microbeams in unidirectional mode, with a skin entrance dose of 625 Gy. The effect of using 200 or 100 microm center-to-center spacing between the microbeams was compared. The median survival time (post-implantation) was 40 and 67 days at 200 and 100 microm spacing, respectively. However, 72% of rats irradiated at 100 microm spacing showed abnormal clinical signs and weight patterns, whereas only 12% of rats were affected at 200 microm spacing. In parallel, histological lesions of the normal brain were found in the 100 microm series only. Although the increase in lifespan was equal to 273% and 102% for the 100 and 200 microm series, respectively, the 200 microm spacing protocol provides a better sparing of healthy tissue and may prove useful in combination with other radiation modalities or additional drugs.

Differences between dual X-ray absorptiometry using pencil beam and fan beam modes and their determinants in vivo and in vitro

The aim of this study was to determine the influence of individual factors on differences in bone mineral density (BMD) using dual X-ray absorptiometry pencil beam (PB) and fan beam (FB) modes in vivo and in vitro. PB.BMD and FB.BMD of 63 normal Caucasian females ages 21-80 yr were measured at the lumbar spine and hip. Residuals of the FB/PB regression were used to assess the impact of height, weight, adiposity index (AI) (= weight/height(3/2)), back tissue thickness, and PB.BMD, respectively, on FB/PB difference. The Hologic Anthropomorphic Spine Phantom (ASP) was measured using the PB and FB modes at two different levels to assess the impact of scanning mode and focus distance. The European Spine Phantom (ESP) prototype, a geometrically well-defined phantom with known vertebral densities, was measured using PB and FB modes and analyzed manually to determine the impact of bone density on FB/PB difference and automatically to determine the impact of edge detection on FB/PB difference. Population BMD results were perfectly correlated, but significantly overestimated by 1.5% at the lumbar spine and underestimated by 0.7% at the neck, 1.8% at the trochanter, and 2.0% at the total hip, respectively, when using the FB compared with PB mode. At the lumbar spine, the FB/PB residual correlated negatively with height (r = 0.34, p < 0.01) and PB.BMD (r = 0.48, p <: 0. 0001) and positively with AI (r = 0.26, p < 0.05). At the hip, residual of trochanter correlated positively with weight (r = 0.36, p < 0.01) and AI (r = 0.36, p < 0.01). The FB mode significantly increased ASP BMD by 0.7% compared with PB. Using the FB mode, increasing focus distance significantly (p < 0.001) decreased area and bone mineral content, but not BMD. By contrast, increasing focus distance significantly decreased PB.BMD by 0.7%. With the ESP, the PB mode supplied accurate projected are of the bone (AREA) results but significant underestimation of specified BMD in the manual analysis. The FB mode significantly underestimated PB. AREA by 2.9% but fitted specified BMD quite well. FB/PB overestimation was larger for the low-density (+8.7%) than for the high-density vertebra (+4. 9%). The automated analysis resulted in more than 14% underestimation of PB. AREA (low-density vertebra) and an almost 13% overestimation of PB.BMD (high-density vertebra) using FB. In conclusion, FB and PB measurements are highly correlated at the lumbar spine and hip with small but significant BMD differences related to height, adiposity, and BMD. In clinical practice, it can be erroneous to switch from one method to another, especially in women with low bone density.

Visualization and stereological characterization of individual rat lung acini by high-resolution X-ray tomographic microscopy

The small trees of gas-exchanging pulmonary airways which are fed by the most distal purely conducting airways are called acini and represent the functional gas-exchanging units. The three-dimensional architecture of the acini has a strong influence on ventilation and particle deposition. Due to the difficulty to identify individual acini on microscopic lung sections the knowledge about the number of acini and their biological parameters like volume, surface area, and number of alveoli per acinus are limited. We developed a method to extract individual acini from lungs imaged by high-resolution synchrotron radiation based X-ray tomographic microscopy and estimated their volume, surface area and number of alveoli. Rat acini were isolated by semiautomatically closing the airways at the transition from conducting to gas-exchanging airways. We estimated a mean internal acinar volume of 1.148mm(3), a mean acinar surface area of 73.9mm(2), and a mean of 8470 alveoli per acinus. Assuming that the acini are similarly sized throughout different regions of the lung, we calculated that a rat lung contains 5470±833 acini. We conclude that our novel approach is well suited for the fast and reliable characterization of a large number of individual acini in healthy, diseased, or transgenic lungs of different species including humans.

Fully automatic X-ray image segmentation via joint estimation of image displacements.

We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.

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).

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

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.

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.

Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging.

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.

XMapTools: a MATLAB©-based program for electron microprobe X-ray image processing and geothermobarometry

XMapTools is a MATLAB©-based graphical user interface program for electron microprobe X-ray image processing, which can be used to estimate the pressure–temperature conditions of crystallization of minerals in metamorphic rocks. This program (available online at http://www.xmaptools.com) provides a method to standardize raw electron microprobe data and includes functions to calculate the oxide weight percent compositions for various minerals. A set of external functions is provided to calculate structural formulae from the standardized analyses as well as to estimate pressure–temperature conditions of crystallization, using empirical and semi-empirical thermobarometers from the literature. Two graphical user interface modules, Chem2D and Triplot3D, are used to plot mineral compositions into binary and ternary diagrams. As an example, the software is used to study a high-pressure Himalayan eclogite sample from the Stak massif in Pakistan. The high-pressure paragenesis consisting of omphacite and garnet has been retrogressed to a symplectitic assemblage of amphibole, plagioclase and clinopyroxene. Mineral compositions corresponding to ~165,000 analyses yield estimates for the eclogitic pressure–temperature retrograde path from 25 kbar to 9 kbar. Corresponding pressure–temperature maps were plotted and used to interpret the link between the equilibrium conditions of crystallization and the symplectitic microstructures. This example illustrates the usefulness of XMapTools for studying variations of the chemical composition of minerals and for retrieving information on metamorphic conditions on a microscale, towards computation of continuous pressure–temperature-and relative time path in zoned metamorphic minerals not affected by post-crystallization diffusion.