Optimization of a customized simultaneous algebraic reconstruction technique algorithm for phase-contrast breast computed tomography.

Objective.To introduce the optimization of a customized GPU-based simultaneous algebraic reconstruction technique (cSART) in the field of phase-contrast breast computed tomography (bCT). The presented algorithm features a 3D bilateral regularization filter that can be tuned to yield optimal performance for clinical image visualization and tissues segmentation.Approach.Acquisitions of a dedicated test object and a breast specimen were performed at Elettra, the Italian synchrotron radiation (SR) facility (Trieste, Italy) using a large area CdTe single-photon counting detector. Tomographic images were obtained at 5 mGy of mean glandular dose, with a 32 keV monochromatic x-ray beam in the free-space propagation mode. Three independent algorithms parameters were optimized by using contrast-to-noise ratio (CNR), spatial resolution, and noise texture metrics. The results obtained with the cSART algorithm were compared with conventional SART and filtered back projection (FBP) reconstructions. Image segmentation was performed both with gray scale-based and supervised machine-learning approaches.Main results.Compared to conventional FBP reconstructions, results indicate that the proposed algorithm can yield images with a higher CNR (by 35% or more), retaining a high spatial resolution while preserving their textural properties. Alternatively, at the cost of an increased image 'patchiness', the cSART can be tuned to achieve a high-quality tissue segmentation, suggesting the possibility of performing an accurate glandularity estimation potentially of use in the realization of realistic 3D breast models starting from low radiation dose images.Significance.The study indicates that dedicated iterative reconstruction techniques could provide significant advantages in phase-contrast bCT imaging. The proposed algorithm offers great flexibility in terms of image reconstruction optimization, either toward diagnostic evaluation or image segmentation.

Using Geant4 Monte Carlo toolkit to evaluate a low power X-ray tube generator configuration.

Monte Carlo technique has been widely used as an important tool to develop new irradiation equipment, prototype medical equipment parts, and test methodologies for dosimetry. In this manuscript, we present a methodology to design a low power X-ray tube generator using the Geant4 Monte Carlo toolkit. The simulations were performed considering a large number of variables, namely, the material composition of the target track, the window thickness, and the air pressure of the X-ray tube. The X-ray production was simulated considering monoenergetic electron beams impinging on targets of tungsten and copper with incident kinetic energies ranging from 20 keV to 60 keV and initial divergences from 5° to 30°. For the polyenergetic emission, a conservative approach with Gaussian energy distribution was adopted. The analysis indicates that among the evaluated parameters, the incident kinetic energy, and the target material produced the most notable changes in the spectra shape and conversion efficiency (CE), significantly impacting the X-ray tube design. The studies provide a reliable methodology to explore general configurations for X-ray tube generators, defining the best geometry, material compositions, and thicknesses to be used on spectroscopy applications.

Imaging performance of phase-contrast breast computed tomography with synchrotron radiation and a CdTe photon-counting detector.

PURPOSE: Within the SYRMA-CT collaboration based at the ELETTRA synchrotron radiation (SR) facility the authors investigated the imaging performance of the phase-contrast computed tomography (CT) system dedicated to monochromatic in vivo 3D imaging of the female breast, for breast cancer diagnosis. METHODS: Test objects were imaged at 38keV using monochromatic SR and a high-resolution CdTe photon-counting detector. Signal and noise performance were evaluated using modulation transfer function (MTF) and noise power spectrum. The analysis was performed on the images obtained with the application of a phase retrieval algorithm as well as on those obtained without phase retrieval. The contrast to noise ratio (CNR) and the capability of detecting test microcalcification clusters and soft masses were investigated. RESULTS: For a voxel size of (60µm)(3), images without phase retrieval showed higher spatial resolution (6.7mm(-1) at 10% MTF) than corresponding images with phase retrieval (2.5mm(-1)). Phase retrieval produced a reduction of the noise level and an increase of the CNR by more than one order of magnitude, compared to raw phase-contrast images. Microcalcifications with a diameter down to 130µm could be detected in both types of images. CONCLUSIONS: The investigation on test objects indicates that breast CT with a monochromatic SR source is technically feasible in terms of spatial resolution, image noise and contrast, for in vivo 3D imaging with a dose comparable to that of two-view mammography. Images obtained with the phase retrieval algorithm showed the best performance in the trade-off between spatial resolution and image noise.

Towards breast tomography with synchrotron radiation at Elettra: first images.

The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 µm)(3) CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR.

A two-layered classifier based on the radial basis function for the screening of thalassaemia.

The thalassaemias are blood disorders with hereditary transmission. Their distribution is global, with particular incidence in areas affected by malaria. Their diagnosis is mainly based on haematologic and genetic analyses. The aim of this study was to differentiate between persons with the thalassaemia trait and normal subjects by inspecting characteristics of haemochromocytometric data. The paper proposes an original method that is useful in screening activity for thalassaemia classification. A complete working system with a friendly graphical user interface is presented. A unique feature of the presented work is the adoption of a two-layered classification system based on Radial basis function, which improves the performance of the system.

Quantitative phase retrieval with picosecond X-ray pulses from the ATF Inverse Compton Scattering source.

Quantitative phase retrieval is experimentally demonstrated using the Inverse Compton Scattering X-ray source available at the Accelerator Test Facility (ATF) in the Brookhaven National Laboratory. Phase-contrast images are collected using in-line geometry, with a single X-ray pulse of approximate duration of one picosecond. The projected thickness of homogeneous samples of various polymers is recovered quantitatively from the time-averaged intensity of transmitted X-rays. The data are in good agreement with the expectations showing that ATF Inverse Compton Scattering source is suitable for performing phase-sensitive quantitative X-ray imaging on the picosecond scale. The method shows promise for quantitative imaging of fast dynamic phenomena.

Compact x-ray sources for mammographic applications: Monte Carlo simulations of image quality.

Thomson scattering x-ray sources can provide spectral distributions that are ideally suited for mammography with sufficient fluence rates. In this article, the authors investigate the effects of different spectral distributions on the image quality in simulated images of a breast mammographic phantom containing details of different compositions and thicknesses. They simulated monochromatic, quasimonochromatic, and polychromatic x-ray sources in order to define the energy for maximum figure of merit (signal-difference-to-noise ratio squared/mean glandular dose), the effect of an energy spread, and the effect of the presence of higher-order harmonics. The advantages of these sources with respect to conventional polychromatic sources as a function of phantom and detail thickness were also investigated. The results show that the energy for the figure of merit peak is between 16 and 27.4 keV, depending on the phantom thickness and detail composition and thickness. An energy spread of about 1 keV standard deviation, easily achievable with compact x-ray sources, does not appreciably affect the image quality.

Pleural nodule identification in low-dose and thin-slice lung computed tomography.

A completely automated system for the identification of pleural nodules in low-dose and thin-slice computed tomography (CT) of the lung has been developed. The directional-gradient concentration method has been applied to the pleura surface and combined with a morphological opening-based procedure to generate a list of nodule candidates. Each nodule candidate is characterized by 12 morphological and textural features, which are analyzed by a rule-based filter and a neural classifier. This detection system has been developed and validated on a dataset of 42 annotated CT scans. The k-fold cross validation has been used to evaluate the neural classifier performance. The system performance variability due to different ground truth agreement levels is discussed. In particular, the poor 44% sensitivity obtained on the ground truth with agreement level 1 (nodules annotated by only one radiologist) with six FP per scan grows up to the 72% if the underlying ground truth is changed to the agreement level 2 (nodules annotated by two radiologists).

Comparison of two portable solid state detectors with an improved collimation and alignment device for mammographic x-ray spectroscopy.

We describe a portable system for mammographic x-ray spectroscopy, based on a 2 X 2 X 1 mm3 cadmium telluride (CdTe) solid state detector, that is greatly improved over a similar system based on a 3 X 3 X 2 mm3 cadmium zinc telluride (CZT) solid state detector evaluated in an earlier work. The CdTe system utilized new pinhole collimators and an alignment device that facilitated measurement of mammographic x-ray spectra. Mammographic x-ray spectra acquired by each system were comparable. Half value layer measurements obtained using an ion chamber agreed closely with those derived from the x-ray spectra measured by either detector. The faster electronics and other features of the CdTe detector allowed its use with a larger pinhole collimator than could be used with the CZT detector. Additionally, the improved pinhole collimator and alignment features of the apparatus permitted much more rapid setup for acquisition of x-ray spectra than was possible on the system described in the earlier work. These improvements in detector technology, collimation and ease of alignment, as well as low cost, make this apparatus attractive as a tool for both laboratory research and advanced mammography quality control.

A Simulator for X-ray images.

A simulator for X-ray images is presented based on a virtual X-ray source and a virtual human body obtained from tomographic slices. In the simulator it is possible to modify the tube potential, the anodic current, the exposure time, the filtration and some geometric parameters such as source-skin distance, orientation and field size. The virtual body consists of a three-dimensional voxel matrix in which CT numbers for each point of the body are stored. The interactions of X rays passing through the body are evaluated using the pencil beam technique. The image is obtained by computing the dose absorbed by the detector and converting it into optical density using a proper response function. The image spatial resolution is limited by the voxel size. The influence of each parameter on the image quality can be observed interactively. The dose absorbed in each point of the body is an important parameter obtained as output of the simulator.

Direct analysis of molybdenum target generated x-ray spectra with a portable device.

In routine applications, information about the photon flux of x-ray tubes is obtained from exposure measurements and cataloged spectra. This approach relies mainly on the assumption that the real spectrum is correctly approximated by the cataloged one, once the main characteristics of the tube such as voltage, target material, anode angle, and filters are taken account of. In practice, all this information is not always available. Moreover, x-ray tubes with the same characteristics may have different spectra. We describe an apparatus that should be useful for quality control in hospitals and for characterizing new radiographic systems. The apparatus analyzes the spectrum generated by an x-ray mammographic unit. It is based on a commercial CZT produced by AMPTEK Inc. and a set of tungsten collimator disks. The electronics of the CZT are modified so as to obtain a faster response. The signal is digitized using an analog to digital converter with a sampling frequency of up to 20 MHz. The whole signal produced by the x-ray tube is acquired and analyzed off-line in order to accurately recognize pile-up events and reconstruct the emitted spectrum. The energy resolution has been determined using a calibrated x-ray source. Spectra were validated by comparison of the HVL measured using an ionization chamber.

A real-time classification system of thalassemic pathologies based on artificial neural networks.

Thalassemias are pathologies that derive from genetic defects of the globin genes. The most common defects among the population affect the genes that are involved in the synthesis of alpha and beta chains. The main aspects of these pathologies are well explained from a biochemical and genetic point of view. The diagnosis is fundamentally based on hematologic and genetic tests. A genetic analysis is particularly important to determine the carriers of alpha-thalassemia, whose identification by means of the hematologic parameters is more difficult in comparison with heterozygotes for alpha-thalassemia. This work investigates the use of artificial neural networks (ANNs) for the classification of thalassemic pathologies using the hematologic parameters resulting from hemochromocytometric analysis only. Different combinations of ANNs are reported, which allow thalassemia carriers to be discriminated from normals with 94% classification accuracy, 92% sensitivity, and 95% specificity. On the basis of these results, an automated system that allows real-time support for diagnoses is proposed. The automated system interfaces a hemochromo analyzer to a simple PC.

A new algorithm for computer tomographic reconstruction from partial view projections.

Conventional algorithms for tomographic reconstruction require the acquisition of a complete set of projections at uniform angular displacements. In many cases, however, the geometry of the sample or a loss of data can significantly reduce the range of the available projections. Several algorithms have been proposed in literature to handle such situations, but their performances are low or they require strong constraints and hypothesis about the nature of the sample or the data. Here a new method is proposed. It is based on a novel morphing technique, which affords in general terms the problem of curve matching and is here specialized to the case of tomographic reconstruction. The proposed algorithm is very fast in comparison to other approaches having similar effectiveness; furthermore, it allows one to obtain good quality images even when a significant fraction of the views is absent, without any hypothesis about the nature of the sample or the kind of measurement. The results obtained by applying this technique to the Shepp-Logan phantom and to a clinical scan are reported here and discussed.