Pressure-jump X-ray studies of liquid crystal transitions in lipids

In this paper, we give an overview of our studies by static and time-resolved X-ray diffraction of inverse cubic phases and phase transitions in lipids. In 1, we briefly discuss the lyotropic phase behaviour of lipids, focusing attention on non-lamellar structures, and their geometric/topological relationship to fusion processes in lipid membranes. Possible pathways for transitions between different cubic phases are also outlined. In 2, we discuss the effects of hydrostatic pressure on lipid membranes and lipid phase transitions, and describe how the parameters required to predict the pressure dependence of lipid phase transition temperatures can be conveniently measured. We review some earlier results of inverse bicontinuous cubic phases from our laboratory, showing effects such as pressure-induced formation and swelling. In 3, we describe the technique of pressure-jump synchrotron X-ray diffraction. We present results that have been obtained from the lipid system 1:2 dilauroylphosphatidylcholine/lauric acid for cubic-inverse hexagonal, cubic-cubic and lamellar-cubic transitions. The rate of transition was found to increase with the amplitude of the pressure-jump and with increasing temperature. Evidence for intermediate structures occurring transiently during the transitions was also obtained. In 4, we describe an IDL-based 'AXCESS' software package being developed in our laboratory to permit batch processing and analysis of the large X-ray datasets produced by pressure-jump synchrotron experiments. In 5, we present some recent results on the fluid lamellar-Pn3m cubic phase transition of the single-chain lipid 1-monoelaidin, which we have studied both by pressure-jump and temperature-jump X-ray diffraction. Finally, in 6, we give a few indicators of future directions of this research. We anticipate that the most useful technical advance will be the development of pressure-jump apparatus on the microsecond time-scale, which will involve the use of a stack of piezoelectric pressure actuators. The pressure-jump technique is not restricted to lipid phase transitions, but can be used to study a wide range of soft matter transitions, ranging from protein unfolding and DNA unwinding and transitions, to phase transitions in thermotropic liquid crystals, surfactants and block copolymers.

Retention Characteristics of CBTi144 Thin Films Explained by Means of X-Ray Photoemission Spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Time lags of the kilohertz quasi-periodic oscillations in the low-mass X-ray binaries 4U 1608−52 and 4U 1636−53

We studied the energy and frequency dependence of the Fourier time lags and intrinsic coherence of the kilohertz quasi-periodic oscillations (kHz QPOs) in the neutron-star lowmass X-ray binaries 4U 1608−52 and 4U 1636−53, using a large data set obtained with the Rossi X-ray Timing Explorer. We confirmed that, in both sources, the time lags of the lower kHz QPO are soft and their magnitude increases with energy. We also found that: (i) In 4U 1636−53, the soft lags of the lower kHz QPO remain constant at∼30 μs in the QPO frequency range 500–850 Hz, and decrease to ∼10 μs when the QPO frequency increases further. In 4U 1608−52, the soft lags of the lower kHz QPO remain constant at 40 μs up to 800 Hz, the highest frequency reached by this QPO in our data. (ii) In both sources, the time lags of the upper kHz QPO are hard, independent of energy or frequency and inconsistent with the soft lags of the lower kHz QPO. (iii) In both sources the intrinsic coherence of the lower kHz QPO remains constant at ∼0.6 between 5 and 12 keV, and drops to zero above that energy. The intrinsic coherence of the upper kHz QPO is consistent with being zero across the full energy range. (iv) In 4U 1636−53, the intrinsic coherence of the lower kHz QPO increases from ∼0 at ∼600 Hz to ∼1, and it decreases to ∼0.5 at 920 Hz; in 4U 1608−52, the intrinsic coherence is consistent with the same trend. (v) In both sources the intrinsic coherence of the upper kHz QPO is consistent with zero over the full frequency range of the QPO, except in 4U 1636−53 between 700 and 900 Hz where the intrinsic coherence marginally increases. We discuss our results in the context of scenarios in which the soft lags are either due to reflection off the accretion disc or up-/down-scattering in a hot medium close to the neutron star. We finally explore the connection between, on one hand the time lags and the intrinsic coherence of the kHz QPOs, and on the other the QPOs’ amplitude and quality factor in these two sources.

Background minimization issues for next generation hard X-ray focusing telescopes

The hard X-ray band (10 - 100 keV) has been only observed so far by collimated and coded aperture mask instruments, with a sensitivity and an angular resolution lower than two orders of magnitude as respects the current X-ray focusing telescopes operating below 10 - 15 keV. The technological advance in X-ray mirrors and detection systems is now able to extend the X-ray focusing technique to the hard X-ray domain, filling the gap in terms of observational performances and providing a totally new deep view on some of the most energetic phenomena of the Universe. In order to reach a sensitivity of 1 muCrab in the 10 - 40 keV energy range, a great care in the background minimization is required, a common issue for all the hard X-ray focusing telescopes. In the present PhD thesis, a comprehensive analysis of the space radiation environment, the payload design and the resulting prompt X-ray background level is presented, with the aim of driving the feasibility study of the shielding system and assessing the scientific requirements of the future hard X-ray missions. A Geant4 based multi-mission background simulator, BoGEMMS, is developed to be applied to any high energy mission for which the shielding and instruments performances are required. It allows to interactively create a virtual model of the telescope and expose it to the space radiation environment, tracking the particles along their path and filtering the simulated background counts as a real observation in space. Its flexibility is exploited to evaluate the background spectra of the Simbol-X and NHXM mission, as well as the soft proton scattering by the X-ray optics and the selection of the best shielding configuration. Altough the Simbol-X and NHXM missions are the case studies of the background analysis, the obtained results can be generalized to any future hard X-ray telescope. For this reason, a simplified, ideal payload model is also used to select the major sources of background in LEO. All the results are original contributions to the assessment studies of the cited missions, as part of the background groups activities.

Personal experience with whole-body, low-dosage, digital X-ray scanning (LODOX-Statscan) in trauma

BACKGROUND: Lodox-Statscan is a whole-body, skeletal and soft-tissue, low-dose X-ray scanner Anterior-posterior and lateral thoraco-abdominal studies are obtained in 3-5 minutes with only about one-third of the radiation required for conventional radiography. Since its approval by the Food and Drug Administration (FDA) in the USA, several trauma centers have incorporated this technology into their Advanced Trauma Life Support protocols. This review provides a brief overview of the system, and describes the authors' own experience with the system. METHODS: We performed a PubMed search to retrieve all references with 'Lodox' and 'Stat-scan' used as search terms. We furthermore used the google search engine to identify existing alternatives. To the best of our knowledge, this is the only FDA-approved device of its kind currently used in trauma. RESULTS AND CONCLUSION: The intention of our review has been to sensitize the readership that such alternative devices exist. The key message is that low dosage full body radiography may be an alternative to conventional resuscitation room radiography which is usually a prelude to CT scanning (ATLS algorithm). The combination of both is radiation intensive and therefore we consider any reduction of radiation a success. But only the future will show whether LS will survive in the face of low-dose radiation CT scanners and magnetic resonance imaging devices that may eventually completely replace conventional radiography.

Bone mineral density at distal tibia using dual-energy X-ray absorptiometry in normal women and in patients with vertebral osteoporosis or primary hyperparathyroidism

To assess the effect of age and disease on mineral distribution at the distal third of the tibia, bone mineral content (BMC) and bone mineral density (BMD) were measured at lumbar spine (spine), femoral neck (neck), and diaphysis (Dia) and distal epiphysis (Epi) of the tibia in 89 healthy control women of different age groups (20-29, n = 12; 30-39, n = 11; 40-44, n = 12; 45-49, n = 12; 50-54, n = 12; 55-59, n = 10; 60-69, n = 11; 70-79, n = 9), in 25 women with untreated vertebral osteoporosis (VOP), and in 19 women with primary hyperparathyroidism (PHPT) using dual-energy x-ray absorptiometry (DXA; Hologic QDR 1000 and standard spine software). A soft tissue simulator was used to compensate for heterogeneity of soft tissue thickness around the leg. Tibia was scanned over a length of 130 mm from the ankle joint, fibula being excluded from analysis. For BMC and BMD, 10 sections 13 mm each were analyzed separately and then pooled to define the epiphysis (Epi 13-52 mm) and diaphysis area (Dia 91-130 mm). Precision after repositioning was 1.9 and 2.1% for Epi and Dia, respectively. In the control group, at any site there was no significant difference between age groups 20-29 and 30-39, which thus were pooled to define the peak bone mass (PBM).(ABSTRACT TRUNCATED AT 250 WORDS)

Dual-energy X-ray absorptiometry for measuring total bone mineral content in the rat: study of accuracy and precision

Sequential studies of osteopenic bone disease in small animals require the availability of non-invasive, accurate and precise methods to assess bone mineral content (BMC) and bone mineral density (BMD). Dual-energy X-ray absorptiometry (DXA), which is currently used in humans for this purpose, can also be applied to small animals by means of adapted software. Precision and accuracy of DXA was evaluated in 10 rats weighing 50-265 g. The rats were anesthetized with a mixture of ketamine-xylazine administrated intraperitoneally. Each rat was scanned six times consecutively in the antero-posterior incidence after repositioning using the rat whole-body software for determination of whole-body BMC and BMD (Hologic QDR 1000, software version 5.52). Scan duration was 10-20 min depending on rat size. After the last measurement, rats were sacrificed and soft tissues were removed by dermestid beetles. Skeletons were then scanned in vitro (ultra high resolution software, version 4.47). Bones were subsequently ashed and dissolved in hydrochloric acid and total body calcium directly assayed by atomic absorption spectrophotometry (TBCa[chem]). Total body calcium was also calculated from the DXA whole-body in vivo measurement (TBCa[DXA]) and from the ultra high resolution measurement (TBCa[UH]) under the assumption that calcium accounts for 40.5% of the BMC expressed as hydroxyapatite. Precision error for whole-body BMC and BMD (mean +/- S.D.) was 1.3% and 1.5%, respectively. Simple regression analysis between TBCa[DXA] or TBCa[UH] and TBCa[chem] revealed tight correlations (n = 0.991 and 0.996, respectively), with slopes and intercepts which were significantly different from 1 and 0, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

GRO J1008−57: an (almost) predictable transient X-ray binary

A study of archival RXTE, Swift, and Suzaku pointed observations of the transient high-mass X-ray binary GRO J1008−57 is presented. A new orbital ephemeris based on pulse arrival-timing shows the times of maximum luminosities during outbursts of GRO J1008−57 to be close to periastron at orbital phase − 0.03. This makes the source one of a few for which outburst dates can be predicted with very high precision. Spectra of the source in 2005, 2007, and 2011 can be well described by a simple power law with high-energy cutoff and an additional black body at lower energies. The photon index of the power law and the black-body flux only depend on the 15–50 keV source flux. No apparent hysteresis effects are seen. These correlations allow us to predict the evolution of the pulsar’s X-ray spectral shape over all outbursts as a function of just one parameter, the source’s flux. If modified by an additional soft component, this prediction even holds during GRO J1008−57’s 2012 type II outburst.

An X-ray study of the SNR G344.7-0.1 and the central object CXOU J170357.8-414302

Aims. We report results of an X-ray study of the supernova remnant (SNR) G344.7-0.1 and the point-like X-ray source located at the geometrical center of the SNR radio structure. Methods. The morphology and spectral properties of the remnant and the central X-ray point-like source were studied using data from the XMM-Newton and Chandra satellites. Archival radio data and infrared Spitzer observations at 8 and 24 mu m were used to compare and study its multi-band properties at different wavelengths. Results. The XMM-Newton and Chandra observations reveal that the overall X-ray emission of G344.7-0.1 is extended and correlates very well with regions of bright radio and infrared emission. The X-ray spectrum is dominated by prominent atomic emission lines. These characteristics suggest that the X-ray emission originated in a thin thermal plasma, whose radiation is represented well by a plane-parallel shock plasma model (PSHOCK). Our study favors the scenario in which G344.7-0.1 is a 6 x 10^3 year old SNR expanding in a medium with a high density gradient and is most likely encountering a molecular cloud on the western side. In addition, we report the discovery of a soft point-like X-ray source located at the geometrical center of the radio SNR structure. The object presents some characteristics of the so-called compact central objects (CCO). However, its neutral hydrogen absorption column (N_H) is inconsistent with that of the SNR. Coincident with the position of the source, we found infrared and optical objects with typical early-K star characteristics. The X-ray source may be a foreground star or the CCO associated with the SNR. If this latter possibility were confirmed, the point-like source would be the farthest CCO detected so far and the eighth member of the new population of isolated and weakly magnetized neutron stars.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Machine Learning-based Techniques to Address Spectral Distortions in Photon Counting X-ray Computed Tomography

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Ethnic differences in the BMI-%BF relationships between young Japanese and Australian-Caucasian males living in Australia using dual-energy X-ray absorptiometry

The Body Mass Index (BMI) has been used worldwide as an indicator of fatness. However, the universal cut-off points by the World Health Organisation (WHO) classification may not be appropriate for every ethnic group when consider the relationship with their actual total body fatness(%BF). The application of population-specific classifications to assess BMI may be more relevant to public health. Ethnic differences in the BMI%BF relationship between 45 Japanese and 42 Australian-Caucasian males were assessed using whole body dual-energy X-ray absorptiometry (DXA) scan and anthropometry using a standard protocol. Japanese males had significantly (p<0.05) greater %BF at given BMI values than Australian males. When this is taken into account the newly proposed Asia-Pacific BMI classification of BMI 23 as overweight and 25 as obese may better assess the level of obesity that is associated increased health risks for this population. To clarify the current findings, further studies that compare the relationships across other Japanese populations are recommended.