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.

X-Ray Diffraction Study of Boron Produced by Pyrolysis of Boron Tribromide

The goal of this research was to determine the composition of boron deposits produced by pyrolysis of boron tribromide, and to use the results to (a) determine the experimental conditions (reaction temperature, etc.) necessary to produce alpha-rhombohedral boron and (b) guide the development/refinement of the pyrolysis experiments such that large, high purity crystals of alpha-rhombohedral boron can be produced with consistency. Developing a method for producing large, high purity alpha-rhombohedral boron crystals is of interest because such crystals could potentially be used to achieve an alpha-rhombohedral boron based neutron detector design (a solid-state detector) that could serve as an alternative to existing neutron detector technologies. The supply of neutron detectors in the United States has been hampered for a number of years due to the current shortage of helium-3 (a gas used in many existing neutron detector technologies); the development of alternative neutron detector technology such as an alpha-rhombohedral boron based detector would help provide a more sustainable supply of neutron detectors in this country. In addition, the prospect/concept of an alpha-rhombohedral boron based neutron detector is attractive because it offers the possibility of achieving a design that is smaller, longer life, less power consuming, and potentially more sensitive than existing neutron detectors. The main difficulty associated with creating an alpha-rhombohedral boron based neutron detector is that producing large, high purity crystals of alpha-rhombohedral boron is extremely challenging. Past researchers have successfully made alpha-rhombohedral boron via a number of methods, but no one has developed a method for consistently producing large, high purity crystals. Alpha-rhombohedral boron is difficult to make because it is only stable at temperatures below around 1100-1200 °C, its formation is very sensitive to impurities, and the conditions necessary for its formation are not fully understood or agreed upon in the literature. In this research, the method of pyrolysis of boron tribromide (hydrogen reduction of boron tribromide) was used to deposit boron on a tantalum filament. The goal was to refine this method, or potentially use it in combination with a second method (amorphous boron crystallization), to the point where it is possible to grow large, high purity alpha-rhombohedral boron crystals with consistency. A pyrolysis apparatus was designed and built, and a number of trials were run to determine the conditions (reaction temperature, etc.) necessary for alpha-rhombohedral boron production. This work was focused on the x-ray diffraction analysis of the boron deposits; x-ray diffraction was performed on a number of samples to determine the types of boron (and other compounds) formed in each trial and to guide the choices of test conditions for subsequent trials. It was found that at low reaction temperatures (in the range of around 830-950 °C), amorphous boron was the primary form of boron produced. Reaction temperatures in the range of around 950-1000 °C yielded various combinations of crystalline boron and amorphous boron. In the first trial performed at a temperature of 950 °C, a mix of amorphous boron and alpha-rhombohedral boron was formed. Using a scanning electron microscope, it was possible to see small alpha-rhombohedral boron crystals (on the order of ~1 micron in size) embedded in the surface of the deposit. In subsequent trials carried out at reaction temperatures in the range of 950 °C – 1000 °C, it was found that various combinations of alpha-rhombohedral boron, beta-rhombohedral boron, and amorphous boron were produced; the results tended to be unpredictable (alpha-rhombohedral boron was not produced in every trial), and the factors leading to success/failure were difficult to pinpoint. These results illustrate how sensitive of a process producing alpha-rhombohedral boron can be, and indicate that further improvements to the test apparatus and test conditions (for example, higher purity/cleanliness) may be necessary to optimize the boron deposition. Although alpha-rhombohedral boron crystals of large size were not achieved, this research was successful in (a) developing a pyrolysis apparatus and test procedure that can serve as a platform for future testing, (b) determining reaction temperatures at which alpha-rhombohedral boron can form, and (c) developing a consistent process for analyzing the boron deposits and determining their composition. Further experimentation is necessary to achieve a pyrolysis apparatus and test procedure that can yield large alpha-rhombohedral boron crystals with consistency.

Seawater carbonate chemistry and trace element accumulation during experiments with common cuttlefish, Sepia officinalis, 2009

Cephalopods play a key role in many marine trophic networks and constitute alternative fisheries resources, especially given the ongoing decline in finfish stocks. Along the European coast, the eggs of the cuttlefish Sepia officinalis are characterized by an increasing permeability of the eggshell during development, which leads to selective accumulation of essential and non-essential elements in the embryo. Temperature and pH are two critical factors that affect the metabolism of marine organisms in the coastal shallow waters. In this study, we investigated the effects of pH and temperature through a crossed (3?2; pH 8.1 (pCO2, 400 ppm), 7.85 (900 ppm) and 7.6 (1400 ppm) at 16 and 19°C, respectively) laboratory experiment. Seawater pH showed a strong effect on the egg weight and non-significant impact on the weight of hatchlings at the end of development implying an egg swelling process and embryo growth disturbances. The lower the seawater pH, the more 110 mAg was accumulated in the tissues of hatchlings. The 109Cd concentration factor (CF) decreased with decreasing pH and 65Zn CF reached maximal values pH 7.85, independently of temperature. Our results suggest that pH and temperature affected both the permeability properties of the eggshell and embryonic metabolism. To the best of our knowledge, this is one of the first studies on the consequences of ocean acidification and ocean warming on metal uptake in marine organisms, and our results indicate the need to further evaluate the likely ecotoxicological impact of the global change on the early-life stages of the cuttlefish.

The microphysics of collisionless shock waves

Collisionless shocks, that is shocks mediated by electromagnetic processes, are customary in space physics and in astrophysics. They are to be found in a great variety of objects and environments: magnetospheric and heliospheric shocks, supernova remnants, pulsar winds and their nebulæ, active galactic nuclei, gamma-ray bursts and clusters of galaxies shock waves. Collisionless shock microphysics enters at different stages of shock formation, shock dynamics and particle energization and/or acceleration. It turns out that the shock phenomenon is a multi-scale non-linear problem in time and space. It is complexified by the impact due to high-energy cosmic rays in astrophysical environments. This review adresses the physics of shock formation, shock dynamics and particle acceleration based on a close examination of available multi-wavelength or in situ observations, analytical and numerical developments. A particular emphasis is made on the different instabilities triggered during the shock formation and in association with particle acceleration processes with regards to the properties of the background upstream medium. It appears that among the most important parameters the background magnetic field through the magnetization and its obliquity is the dominant one. The shock velocity that can reach relativistic speeds has also a strong impact over the development of the micro-instabilities and the fate of particle acceleration. Recent developments of laboratory shock experiments has started to bring some new insights in the physics of space plasma and astrophysical shock waves. A special section is dedicated to new laser plasma experiments probing shock physics.

A Search for Muon Neutrinos in Coincidence with Gamma-Ray Bursts in the Southern Hemisphere Sky Using the IceCube Neutrino Observatory

The origin of observed ultra-high energy cosmic rays (UHECRs, energies in excess of $10^{18.5}$ eV) remains unknown, as extragalactic magnetic fields deflect these charged particles from their true origin. Interactions of these UHECRs at their source would invariably produce high energy neutrinos. As these neutrinos are chargeless and nearly massless, their propagation through the universe is unimpeded and their detection can be correlated with the origin of UHECRs. Gamma-ray bursts (GRBs) are one of the few possible origins for UHECRs, observed as short, immensely bright outbursts of gamma-rays at cosmological distances. The energy density of GRBs in the universe is capable of explaining the measured UHECR flux, making them promising UHECR sources. Interactions between UHECRs and the prompt gamma-ray emission of a GRB would produce neutrinos that would be detected in coincidence with the GRB’s gamma-ray emission. The IceCube Neutrino Observatory can be used to search for these neutrinos in coincidence with GRBs, detecting neutrinos through the Cherenkov radiation emitted by secondary charged particles produced in neutrino interactions in the South Pole glacial ice. Restricting these searches to be in coincidence with GRB gamma-ray emis- sion, analyses can be performed with very little atmospheric background. Previous searches have focused on detecting muon tracks from muon neutrino interactions fromthe Northern Hemisphere, where the Earth shields IceCube’s primary background of atmospheric muons, or spherical cascade events from neutrinos of all flavors from the entire sky, with no compelling neutrino signal found. Neutrino searches from GRBs with IceCube have been extended to a search for muon tracks in the Southern Hemisphere in coincidence with 664 GRBs over five years of IceCube data in this dissertation. Though this region of the sky contains IceCube’s primary background of atmospheric muons, it is also where IceCube is most sensitive to neutrinos at the very highest energies as Earth absorption in the Northern Hemisphere becomes relevant. As previous neutrino searches have strongly constrained neutrino production in GRBs, a new per-GRB analysis is introduced for the first time to discover neutrinos in coincidence with possibly rare neutrino-bright GRBs. A stacked analysis is also performed to discover a weak neutrino signal distributed over many GRBs. Results of this search are found to be consistent with atmospheric muon backgrounds. Combining this result with previously published searches for muon neutrino tracks in the Northern Hemisphere, cascade event searches over the entire sky, and an extension of the Northern Hemisphere track search in three additional years of IceCube data that is consistent with atmospheric backgrounds, the most stringent limits yet can be placed on prompt neutrino production in GRBs, which increasingly disfavor GRBs as primary sources of UHECRs in current GRB models.

X-ray analysis of local mid-infrared selected Compton-thick AGN candidates

Cosmic X-ray background synthesis models (Gilli 2007) require a significant fraction of obscured AGN, some of which are expected to be heavily obscured (Compton-thick), but the number density of observationally found obscured sources is still an open issue (Vignali 2010, 2014). This thesis work takes advantage of recent NuSTAR data and is based on a multiwavelength research approach. Gruppioni et al. 2016 compared the AGN bolometric luminosity, for a sample of local 12 micron Seyfert galaxies, derived from the SED decomposition to the same quantity obtained by the 2-10 keV luminosity (IPAC-NED). A difference up to two orders of magnitude resulted between these quantities for some sources. Thus, the intrinsic X-ray luminosity obtained correcting for the obscuration may be underestimated. In this thesis we have tested this hypothesis by re-analysing the X-ray spectra of three of the sources (UGC05101, NGC1194 and NGC3079), for which observations from NuSTAR and Chandra and/or XMM-Newton were available. This is meant to extend our analysis to energies above 10 keV and thus estimate the AGN column density as reliable as possible. For spectral fitting we made use of both the commonly used XSPEC package and the two very recent MYtorus and BNtorus physical models. The available wide bandpass allowed us to achieve new and more solid insights into the X-ray spectral properties of these sources. The measured absorption column densities are highly suggestive of heavy obscuration. Once corrected the X-ray AGN luminosity for the obscuration estimated through our spectral analysis, we compared the L(X) values in the 2-10 keV band with those derived from the MIR band, by means of the relation by Gandhi, 2009. As expected, the values derived from this relation are in good agreement with those we measured, indicating that the column densities were underestimated in the previous literature works.

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.

X-ray your data with Rasch

By using the Rasch model, much detailed diagnostic information is available to developers of survey and assessment instruments and to the researchers who use them. We outline an approach to the analysis of data obtained from the administration of survey instruments that can enable researchers to recognise and diagnose difficulties with those instruments and then to suggest remedial actions that can improve the measurement properties of the scales included in questionnaires. We illustrate the approach using examples drawn from recent research and demonstrate how the approach can be used to generate figures that make the results of Rasch analyses accessible to non-specialists.

Zeolite from alkali modified kaolin increases NH4+ retention by sandy soil : column experiments

Sandy soils have low water and nutrient retention capabilities so that zeolite soil amendments are used for high value land uses including turf and horticulture to reduce leaching losses of NH4+ fertilisers. MesoLite is a zeolitic material made by caustic treatment of kaolin at 80-95oC. It has a moderately low surface area (9-12m2/g) and very high cation exchange capacity (494 cmol(+)/kg). Laboratory column experiments showed that an addition of 0.4% MesoLite to a sandy soil greatly (90%) reduced leaching of added NH4+ compared to an unamended soil and MesoLite is 11 times more efficient in retaining NH4+ than natural zeolite. Furthermore, NH4+-MesoLite slowly releases NH4+ to soil solution and is likely to be an effective slow release fertiliser.