No description available.

Purpose: Patient centred care and the ‘patient voice’ are core components of UK healthcare policy and practice guidance. This study explores how care is perceived and experienced within the high technology environment of CT. Methods and Materials: A two-phase approach of Critical Discourse Analysis (CDA) and adapted Grounded Theory (GT) methodology using semi structured interviews, was used to obtain primary data from CT radiographers and patients. Recruitment and data collection were performed at a 1200 bed teaching hospital over a 6-month period. Results: The radiographer patient relationship and the radiographer’s role in providing care within CT are complex and multifaceted. Both patients and radiographer’s perceive CT imaging to be an integral part of the overall patient care and treatment pathway. As such, the act of being imaged is perceived as a care process and while image acquisition is recognised as a task orientated and technical process, the human element of providing care is cognitive, dynamic and responsive to individual need. Importantly, patient confidence in the care received was influenced by the radiographer’s ability to build a trusting relationship and display technical competence and this in turn facilitated active compliance resulting in a technically accurate examination. Despite previous literature suggesting that the technical environment created a barrier to patient care, patients within this study confirmed that radiographers provide care commensurate to the nursing ideals represented by the 6C’s (Care; Compassion; Competence; Communication; Courage; Commitment). Conclusions: A co-constructed model of care encompassing both technical components and patient-centeredness has been identified. This model promotes a new vision of patient centred care based on care perceptions within the high technology environment of CT.

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Resumo: O objetivo neste estudo foi avaliar as diferenças no espaço aéreo faríngeo em crianças com diferentes padrões faciais. Foram avaliadas as tomografias computadorizadas de feixe cônico de 98 indivíduos em crescimento, com idade média de 8,9 anos, divididas por sexo e faixa etária, e subdivididas de acordo com o padrão de crescimento (horizontal, vertical normal e produtores) e tipo de má oclusão (Classe I e Classe II). Utilizando um programa tridimensional, foram analisados o volume, área sagital, menor área de seção transversal e as dimensões ântero-posteriores da faringe superior e inferior. As dimensões ântero-posterior da faringe superior e inferior foi significativamente menor em indivíduos com Classe II em crianças na faixa etária entre 9 a 11 anos e a faringe superior em foi significativamente menor em crianças na faixa etária entre 5 e 7 anos com padrão de crescimento vertical. Porém, quando a faringe foi avaliada tridimensionalmente, não foram encontradas diferenças nas demais dimensões sugerindo que diferenças no padrão vertical e no tipo de má oclusão ântero-posterior (Classe I e II) não influenciam as dimensões da faringe. Não foi encontrado dimorfismo sexual. A região de maior constrição da faringe esteve presente mais freqüentemente na orofaringe (86%). Embora as dimensões lineares possam variar entre os diferentes padrões faciais, quando avaliadas tridimensionalmente, elas não foram influenciadas pelas diferentes morfologias faciais / Abstract: The aim of this study was to assess the differences in pharyngeal airway space in children with different facial patterns. Cone-beam computed tomography records of 98 growing patients with mean age of 8.9 years divided by sex and age groups and subdivided according to growth pattern (horizontal, normal and vertical growers) and type of malloclusion (Class I and Class II) were evaluated .Using a 3-dimensional virtual program the volume, sagital area, smallest cross section area, anteroposterior dimensions of superior and inferior pharynx were obtained. The anteroposterior linear dimensions of superior and inferior pharynx in children with 9 to11 years was significant smaller in patients with Class II relationship but in 3D evaluation differences were not found suggesting that anteroposterior malocclusion do not influence pharynx dimensions. The anteroposterior linear dimensions of superior , pharynx in children with 5 to7 years was significant smaller in patients with vertical growth pattern when compared to normal growers, but in 3D evaluation differences were not found suggesting that vertical pattern do not influence pharynx dimensions. No sexual dimorphism was found. The most constricted region of pharynx were mostly found at oropharynx(96%).Although linear dimensions can vary among different facial patterns, the 3-dimensional dimensions weren't influenced by different facial morphologies / Orientador: Luiz Cesar de Moraes / Coorientador: Weber José da Silva Ursi / Banca: Jefferson Luis OshiroTanaka / Banca: Edmundo Medici Filho / Mestre

Computed Tomography (CT) is a medical imaging modality which acquires anatomical data via the unique x-ray attenuation of materials. Yet, some clinically important materials remain difficult to distinguish with current CT technology. Spectral CT is an emerging technology which acquires multiple CT datasets for specific x-ray spectra. These spectra provide a fingerprint that allow materials to be distinguished that would otherwise look the same on conventional CT. The unique characteristics of spectral CT data motivates research into novel visualization techniques. In this thesis, we aim to provide the foundation for visualizing spectral CT data. Our initial investigation of similar multi-variate data types identified intermixing as a promising visualization technique. This promoted the development of a generic, modular and extensible intermixing framework. Therefore, the contribution of our work is a framework supporting the construction, analysis and storage of algorithms for visualizing spectral CT studies. To allow evaluation, we implemented the intermixing framework in an application called MARSCTExplorer along with a standard set of volume visualization tools. These tools provide user-interaction as well as supporting traditional visualization techniques for comparison. We evaluated our work with four spectral CT studies containing materials indistinguishable by conventional CT. Our results confirm that spectral CT can distinguish these materials, and reveal how these materials might be visualized with our intermixing framework.

This dissertation presents the results of an investigation into the performance characteristics of a unique hemispherical SPECT (single-photon emission computed tomography) imaging system capable of producing three-dimensional (3D) tomographic images of the human brain. The system is completely stationary and collects all necessary views of the patient simultaneously, with no system motion. The imager consists of twenty small (10cm x 10cm crystal area), digital gamma cameras arranged in a hemispherical pattern around the patient's head and a hemispherical lead aperture. The hemispherical aperture is positioned between the cameras and the head and contains a large number of pinholes; in this way each camera sees a number of overlapping pinhole projections of the radioactive distribution within the patient's brain. The initial investigation of the performance characteristics of a 3D SPECT system of this design were carried out using a computer simulation in which effects due to radiometry, finite pinhole size, finite detector resolution, photon noise, and object attenuation were included. We used a digital 3D brain phantom as the test object and an iterative search algorithm to perform the reconstructions. The simulations were used to compare the performance of a variety of system configurations. Based upon the results of the simulation study, we constructed a laboratory prototype of the 3D SPECT system, which we used to further characterize the expected performance of a clinical imaging system of the same design. Prior to collecting SPECT data we calibrated the imaging system, which required that we efficiently measure and store the spatially variant system response function. These calibration data were then included in the reconstructions of the SPECT phantoms that we imaged. A number of different SPECT phantoms were imaged to demonstrate the system performance. We measured a reconstructed spatial resolution of 4.8mm full-width at half-maximum and a full-system sensitivity of 36cps/μCi, where both values were measured for a point source in air located at the center of the field of view. We also describe an analysis that we performed to determine the equivalent, non-multiplexed system sensitivity; using this method, we found that the equivalent sensitivity was 79% of the measured value for the system configuration and the particular task that we investigated.

The properties and imaging performance of the computed tomographicimaging spectrometer (CTIS) have been investigated with Fourierand wavelet crosstalk matrices. These matrices and theircorresponding datacube reconstruction algorithms explicitly usedsensitivity equations describing the CTIS imaging system. Theseequations derived from Franhofer diffraction theory of thecomputed generated hologram (CGH) disperser, serve as themathematical model of the CTIS.The Fourier crosstalk matrix (FCTM) was primarily used to analyzethe CTIS imaging system. The FCTM describes which spatial andspectral frequencies contribute to object cube data entering thesystem and whether or not these frequencies give distinctcontributions with respect to each other. Furthermore, since theCTIS is a limited angle tomographic imaging system the missingcone of frequencies which is a feature of this instrument isclearly shown using the FCTM. Subsequently, Fourier-basedestimates of the reconstructed object cube (i.e. the datacube)will be missing this frequency information even if the CTIS is aperfect optical system.The wavelet crosstalk matrix (WCTM) was used primarily for efficient datacubereconstruction only. The datacube reconstruction calculations areprimarily proof-of-concept and reproduce the Fourier results withsome absence of Fourier related artifacts. The waveletdecomposition of the object cube is useful for studying multipleobjects in a parallel processing environment withoutreconstructing the entire datacube, thus reducing overall complexity.Datacube reconstructions of actual astronomical observations withthe CTIS, using the techniques of this research, were consistentwith previous independent datacube estimates from the same datausing existing conventional techniques. Furthermore these objectsfurnish natural point-spread functions that supplementcomputational simulations of the CTIS by describing actual imagingsystem performance.The computational tools for the study ofthe CTIS imaging system provide the additional bonus of ananalysis of object detectability by the computation of receiveroperator characteristic (ROC) curves. We used a synthetic binarystar to simulate this in the presence of both detector and objectnoise.Some suggestions for future research directions are given.

Venous thromboembolism (VTE) is a common disease with a myriad of presentation. It is often difficult to diagnosis with symptoms which are shared with many other disorders. Because of the overlap in symptomatology with other pathologies it is both commonly overlooked when present and commonly considered when absent. The threshold for investigating suspected VTE has dropped over time, in part due to a greater awareness of the disease among clinicians, but also because of the greater availability of diagnostic tests which are both accurate at positively diagnosing VTE and are patient friendly. This has resulted in a mushrooming of the number of diagnostic tests being performed for suspected VTE in radiology departments. As such radiology provides a window into the disease in a way that no other speciality can. All branches of medicine having their share of VTE patients but radiology provides a unique opportunity to study VTE patients as, no matter from which speciality they arise when the disease is suspected, they will almost inevitably end up undergoing a definitive radiological test. There is much still to learn about VTE however developments in modern imaging and computerised databases have advanced our understanding of this common disease. The window that radiology provides into VTE has contributed towards those advances.

The aim of this study was to evaluate whether volumetric changes in persistent periapical lesions can be detected in follow-ups six months to five years after apicoectomy using cone-beam computed tomography. Patients with a previous treatment history of apicoectomy and for whom a pre-surgical CBCT scan was taken between November 2010 and December 2015 were invited to participate in the study. A post-surgical CBCT image of the treated tooth was obtained at the recall visit. Volumetric and linear measurements of periapical lesions on initial and postoperative CBCT images were performed using DiThreshGUI software and two calibrated examiners—a board-certified endodontist and a board-certified oral radiologist. Repeated-measures ANOVA were used to estimate the magnitude of reduction and to test for differences (at alpha=0.05). A total of 20 patients with 27 surgically treated teeth were recalled at an average interval of 37 months. Reduction in the size of lesions was observed in 24 teeth (88%); overall, the volumes significantly decreased as detected by software-assisted measurement of volume (P = .0002) and by calculation from linear measurements (P < .0001). Volumetric analysis detected a reduction of 86% in lesions while the linear-derived volume measurements yielded an average reduction of 96%. These two methods of lesion assessment were strongly correlated with one another in pre-surgical scans (r>0.88) when apical lesions are measurable.

<p>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. </p><p>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.</p><p>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.</p><p>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).</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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. </p><p>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.</p> / Dissertation