Dose optimization approach to fast X-ray microtomography of the lung alveoli

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

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.

Mössbauer, X-ray and Magnetic Studies of Black Sand from the Italian Mediterranean Sea

The study of natural magnetic sands is instrumental to investigate the geological aspects of their formation and of the origin of their territory. In particular, Mössbauer spectroscopy provides unique information on their iron content and on the oxidation state of iron in their mineral composition. The Italian coast on the Mediterranean Sea near Rome is known for the presence of highly magnetic black sands of volcanic origin. A study of the room temperature Mössbauer spec- trum, powder X-ray diffraction, energy dispersive X-ray spectroscopy, and magnetic measurements of a sample of black magnetic sand collected on the seashore of the town of Ladispoli is performed. This study reveals magnetite as main constituent with iron in both tetrahedral and octahedral sites. Minor constituents are the iron minerals hematite and ilmenite, the iron containing minerals diopsite, gossular, and allanite, as well as ubiquitous sanidine, quartz, and calcite.

In situ dehydration behavior of zeolite-like cavansite: A single-crystal X-ray study

To track dehydration behavior of cavansite, Ca(VO)(Si4O10)·4H2O space group Pnma, a = 9.6329(2), b = 13.6606(2), c = 9.7949(2) Å, V = 1288.92(4) Å3 single-crystal X-ray diffraction data on a crystal from Wagholi quarry, Poona district (India) were collected up to 400 °C in steps of 25 °C up to 250 °C and in steps of 50 °C between 250 and 400 °C. The structure of cavansite is characterized by layers of silicate tetrahedra connected by V4+O5 square pyramids. This way a porous framework structure is formed with Ca and H2O as extraframework occupants. At room temperature, the hydrogen bond system was analyzed. Ca is eightfold coordinated by four bonds to O of the framework structure and four bonds to H2O molecules. H2O linked to Ca is hydrogen bonded to the framework and also to adjacent H2O molecules. The dehydration in cavansite proceeds in four steps.At 75 °C, H2O at O9 was completely expelled leading to 3 H2O pfu with only minor impact on framework distortion and contraction V = 1282.73(3) Å3. The Ca coordination declined from originally eightfold to sevenfold and H2O at O7 displayed positional disorder.At 175 °C, the split O7 sites approached the former O9 position. In addition, the sum of the three split positions O7, O7a, and O7b decreased to 50% occupancy yielding 2 H2O pfu accompanied by a strong decrease in volume V = 1206.89(8) Å3. The Ca coordination was further reduced from sevenfold to sixfold.At 350 °C, H2O at O8 was released leading to a formula with 1 H2O pfu causing additional structural contraction (V = 1156(11) Å3). At this temperature, Ca adopted fivefold coordination and O7 rearranged to disordered positions closer to the original O9 H2O site.At 400 °C, cavansite lost crystallinity but the VO2+ characteristic blue color was preserved. Stepwise removal of water is discussed on the basis of literature data reporting differential thermal analyses, differential thermo-gravimetry experiments and temperature dependent IR spectra in the range of OH stretching vibrations.

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).

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.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

Estimation of aortic pressure waveforms from 4D phase-contrast MRI

Several approaches for the non-invasive MRI-based measurement of the aortic pressure waveform over the heart cycle have been proposed in the last years. These methods are normally based on time-resolved, two-dimensional phase-contrast sequences with uni-directionally encoded velocities (2D PC-MRI). In contrast, three-dimensional acquisitions with tridirectional velocity encoding (4D PC-MRI) have been shown to be a suitable data source for detailed investigations of blood flow and spatial blood pressure maps. In order to avoid additional MR acquisitions, it would be advantageous if the aortic pressure waveform could also be computed from this particular form of MRI. Therefore, we propose an approach for the computation of the aortic pressure waveform which can be completely performed using 4D PC-MRI. After the application of a segmentation algorithm, the approach automatically computes the aortic pressure waveform without any manual steps. We show that our method agrees well with catheter measurements in an experimental phantom setup and produces physiologically realistic results in three healthy volunteers.