Skeletal status and soft tissue composition in astronauts. Tissue and fluid changes by radionuclide absorptiometry in vivo

A device has been constructed and tested which provides immediate readout of bone mineral content and bone width from absorptiometric scans with low energy radionuclides. The basis of this analog system is a logarithmic converter-integrator coupled with a precision linear ratemeter. The system provided accurate and reliable results on standards and ashed bone sections. Clinical measurements were made on about 100 patients with the direct readout system, and these were highly correlated with the results from digital scan data on the same patients. The direct readout system has been used successfully in field studies and surveys as well as for clinical observations

Investigation of Statistical and Imaging Methods for Luminescence Detection of Irradiated Ingredients

This project investigated two potential approaches to improving the reliability of lumines-cence methods for detecting minor irradiated ingredients in foods. Whereas in the 1980’s there were no validated methods for laboratory detection of irradiated foods, work conducted in the UK and elsewhere by the mid 1990’s had resulted in the development of a series of physical, chemical and biological methods capable of detecting a range of irradiated food classes. Of these the luminescence methods embodied in EN1788 (Thermoluminescence) and EN13751 (Photostimulated luminescence) standards have been applied to detection of a vari-ety of products including herbs and spices, and seafood. In common with the other EN stan-dard methods almost all validation work had been originally conducted using pure irradiated or unirradiated ingredients. Yet application experience had shown the presence of mixed products containing both irradiated and unirradiated ingredients. A short study was commis-sioned by MAFF to investigate the impact of blending on standard EN1788 methods, and on the provisional draft EN13751 (the standard having been published in the meantime) method. This showed the impact of dilution of irradiated material between 10% and 0.1% concentra-tions on detection rates, which unsurprisingly are reduced by extreme dilution. UK labelling regulation, both before and after adoption of the European Directive on Food Irradiation, call for labelling of all irradiated ingredients regardless of concentration or origin within the final product. This study was therefore motivated by the recognition of the long term need for im-proved methods to improve reliability at low concentrations. Two complementary approaches were investigated. The project first examined whether TL data collected using the EN1788 method could be enhanced using advanced statistical proce-dures. Data sets from the SURRC TL archive, and from project CSA4790 were used both to define the characteristics of irradiated and unirradiated end members, and to assess classifica-tion methods using the controlled blending experimental data sets of CSA 4790. Multivariate analyses, based on principal components analysis and discriminant analysis of glow curve data; kinetic deconvolution approaches coupled to PCA and DA, and neural analyses were investigated and compared with detection rates achieved using expert visual classification. To complement this experiments were undertaken to explore the potential of using focussed laser stimulation to produce spatially resolved measurements from mineral grains separated from foods. Two systems were evaluated based on IR and visible band lasers. Work was under-taken to explore sample presentation and to assess the ability of this approach to distinguish mixtures of irradiated and unirradiated grains. The statistical work was successful in developing three approaches which could be used for objective identification of irradiated materials. Pure irradiated and unirradiated data sets from 150 sample pairs were obtained having searched the SUERC archive of more than 3500 lu-minescence analyses. These were used to set up multivariate analyses based on the ap-proaches outlined above. Performance in recognising irradiated ingredients using these meth-ods was then assessed with data drawn from the MAFF blending investigation, comprising 160 permutations of irradiated and unirradiated herbs and spices at 10%, 1% and 0.1% con-centrations. It was possible to achieve good detection rates with alatistical approaches, the best approaches inigated being the use of glow curve deconvolution coupwith li discrimination, and the use of neural appros. The absolute performance achieved matched that opert visual clfication utilising the revised EN1788 criterwhich were adopted within the international standauring course of this project. The use of ad-vancedtistical methods, while not adding performance, can pde objective support to visual classifications. During performance assessment it was aloted that theformance of all methods wasficiently close to infer that detections rates are most dependent on the statistical presence or absence of irradiated grains within the extracted samples used for TL analysis. This raises practical suggestions for improving detection rates at low concentrations based on the use of larger samples and more specific mineral separation approaches. These may be worth investigating further. Laser scanning approaches were also investigated using highly focussed laser beams to stimulated luminescence sequentially from different parts of separated mineral samples. Work was conducted using a system which had been developed in earlier work at SUERC, and then followed by additional investigation using an improved instrument built during the project. Initial work confirmed the feasibility of using laser scanning approaches to obtain spatially resolved luminescence data at or near the dimensions of individual mineral grains. Practical obstacles included the recognition that laser scattering from surfaces coated with mineral grains introduced an element of cross-talk between different parts of the sample, and difficulties in accurate re-positioning of the sample using the first generation prototype in-strument. Work was conducted to investigate a series of different sample presentation media to improve the former, and to incorporate high precision mechanical and optoelectronic means of re-positioning samples between initial measurements, external irradiation, and sub-sequent re-measurement. Both IR and visible band semiconductor lasers were investigated with successful production of single grain images. The short and medium term reliability of the lasers used was acceptable. The lasers used both however eventually failed, which sug-gests that long term lifetime may be an issue for further work. Of the two lasers the IR laser in particular gave a good signal to background ratio for discriminating between irradiated and unirradiated grains. Quantitative analysis of the grain resolved images confirms the potential of this approach in identifying minor irradiated components. The overall conclusions of the work are that both statistical approaches and imaging instru-ments are able to enhance current methods. The observation that visual classification can match the performance even of deconvolution or neural approaches suggests that future effort should be directed more towards improvement of grain statistics in conventional measure-ments, and in further development and investigation of imaging approaches. In these ways it can anticipated that the performance of standard luminescence methods for detecting dilute mixtures of irradiated and unirradiated food ingredients could be significantly improved. To do so would further enhance work conducted by FSA and other bodies to ensure that regula-tions governing the use of irradiation in food processing and the labelling of imported foods are followed

Analysis of a Gluonic Penguin Decay with the BaBar Detector

This thesis presents a branching fraction analysis of the neutral B meson decay channel B → ϕK0s where the K0s decays to π0π0. The decay is dominated by gluonic penguin transitions, which have been very important for the main program of BABAR: the search for physics beyond the Standard Model. The decay channel has been established and is included in the CP analysis, which is sensitive to new physics. The data set consists of 227 million BB̅ pairs recorded by the BABAR detector at the Stanford Linear Accelerator Center. Sophisticated analysis techniques have been applied primarily to suppress background from e+e- → quark/anti-quark reactions. The analysis of such rare decay channels with BABAR relies on the availability of a large set of computer simulated data. For that purpose a computer cluster has been built at the University of Tennessee as part of the distributed computing support work for BABAR. The design and performance of the cluster is a main subject of this thesis work

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Algorithms for enhanced artifact reduction and material recognition in computed tomography

Computed tomography (CT) imaging provides a non-destructive means to examine the interior of an object which is a valuable tool in medical and security applications. The variety of materials seen in the security applications is higher than in the medical applications. Factors such as clutter, presence of dense objects, and closely placed items in a bag or a parcel add to the difficulty of the material recognition in security applications. Metal and dense objects create image artifacts which degrade the image quality and deteriorate the recognition accuracy. Conventional CT machines scan the object using single source or dual source spectra and reconstruct the effective linear attenuation coefficient of voxels in the image which may not provide the sufficient information to identify the occupying materials. In this dissertation, we provide algorithmic solutions to enhance CT material recognition. We provide a set of algorithms to accommodate different classes of CT machines. First, we provide a metal artifact reduction algorithm for conventional CT machines which perform the measurements using single X-ray source spectrum. Compared to previous methods, our algorithm is robust to severe metal artifacts and accurately reconstructs the regions that are in proximity to metal. Second, we propose a novel joint segmentation and classification algorithm for dual-energy CT machines which extends prior work to capture spatial correlation in material X-ray attenuation properties. We show that the classification performance of our method surpasses the prior work's result. Third, we propose a new framework for reconstruction and classification using a new class of CT machines known as spectral CT which has been recently developed. Spectral CT uses multiple energy windows to scan the object, thus it captures data across higher energy dimensions per detector. Our reconstruction algorithm extracts essential features from the measured data by using spectral decomposition. We explore the effect of using different transforms in performing the measurement decomposition and we develop a new basis transform which encapsulates the sufficient information of the data and provides high classification accuracy. Furthermore, we extend our framework to perform the task of explosive detection. We show that our framework achieves high detection accuracy and it is robust to noise and variations. Lastly, we propose a combined algorithm for spectral CT, which jointly reconstructs images and labels each region in the image. We offer a tractable optimization method to solve the proposed discrete tomography problem. We show that our method outperforms the prior work in terms of both reconstruction quality and classification accuracy

The application of autofluorescence lifetime metrology to the study of heart failure models and heart disease

Autofluorescence spectroscopy offers a promising label-free approach to characterise biological samples and has already shown diagnostic potential in a number of medical applications, although study of myocardium has been relatively limited. A number of myocardial molecules display autofluorescence, including those involved in energetics, e.g. NADH and flavoproteins, as well as structural molecules, e.g. collagen. This thesis discusses the application of a custom-built single point fibre-optic probe-based instrumentation for time-resolved spectrofluorometry utilising spectrally resolved time-correlated single photon counting detection (TCSPC) and white light reflectometry to the investigation of models of heart failure, both ex vivo and in vivo. Heart failure (HF) is a pathophysiological state in which an abnormality of cardiac function causes failure of the heart to pump blood at a rate commensurate with the requirements of the metabolising tissues. It affects 1-2% of the population rising to greater than 10% aged over 70 years. Despite recent therapeutic advances, annualized mortality can still approach 10%. HF results from a myocardial injury (e.g. myocardial infarction, chemotherapy) causing loss of myocytes, and maladaptive changes in surviving myocytes and extracellular matrix by ‘pathological remodelling’. That HF is characterized by structural and energetic changes was the principal motivation for the creation of an instrument to investigate changes in myocardial autofluorescence signature in disease states in vivo. If the signatures associated with known pathological diagnoses could be ascertained, such a technique could perform ‘virtual biopsy’ to aid diagnosis. This thesis describes the application of autofluorescence technique to an ex vivo Langendorff-heart to characterise the changes in autofluorescence signature with controlled insults of glucose deprivation and hypoxia. Additionally, it reports for the first-time the characterization of the autofluorescence lifetime signature in vivo at different time points in an established rat post-myocardial infarction heart failure. The thesis describes development of in vivo intravenous doxorubicin chemotherapy-cardiomyopathy heart failure model (DOX-HF) and subsequent characterization of in vivo autofluorescence signature. This investigation prompted development of a clinically viable instrument and the progress to date is described.Open Acces