Analysis of scoliosis trunk deformities using ICA

This paper describes a method for analyzing scoliosis trunk deformities using Independent Component Analysis (ICA). Our hypothesis is that ICA can capture the scoliosis deformities visible on the trunk. Unlike Principal Component Analysis (PCA), ICA gives local shape variation and assumes that the data distribution is not normal. 3D torso images of 56 subjects including 28 patients with adolescent idiopathic scoliosis and 28 healthy subjects are analyzed using ICA. First, we remark that the independent components capture the local scoliosis deformities as the shoulder variation, the scapula asymmetry and the waist deformation. Second, we note that the different scoliosis curve types are characterized by different combinations of specific independent components.CIHR (Canadian Institutes of Health Research

Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging

SummaryObjectiveThe purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.MethodAn approach to MRI classification of cartilage degradation is proposed using pattern recognition and multivariable regression in which image features from MRIs of histologically scored human articular cartilage plugs were computed using weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHRM). The WND-CHRM method was first applied to several clinically available MRI scan types to perform binary classification of normal and osteoarthritic osteochondral plugs based on the Osteoarthritis Research Society International (OARSI) histological system. In addition, the image features computed from WND-CHRM were used to develop a multiple linear least-squares regression model for classification and prediction of an OARSI score for each cartilage plug.ResultsThe binary classification of normal and osteoarthritic plugs yielded results of limited quality with accuracies between 36% and 70%. However, multiple linear least-squares regression successfully predicted OARSI scores and classified plugs with accuracies as high as 86%. The present results improve upon the previously-reported accuracy of classification using average MRI signal intensities and parameter values.ConclusionMRI features detected by WND-CHRM reflect cartilage degradation status as assessed by OARSI histologic grading. WND-CHRM is therefore of potential use in the clinical detection and grading of osteoarthritis

Analysis of Subchondral Bone and Microvessels Using a Novel Vascular Perfusion Contrast Agent and Optimized Dual-Energy Computed Tomography

Osteoarthritis (OA), is a chronic debilitating disease that affects millions of individuals and is characterized by the degeneration of joint subchondral bone and cartilage. These tissue degenerations manifest as joint pain, limited range of joint motion, and overall diminished quality of life. Currently, the exact mechanism(s) and cause(s) by which OA initiates and progresses remain unknown. The multi-factorial complex nature of OA (i.e. age, diabetes, obesity, and prior injuries have all been shown to play a role in OA) contributes to the current lack of a cure or effective long-term treatment for OA. One re-emerging and interesting hypothesis revolves around the delicate homeostatic microvascular environment around the cartilage – an avascular tissue. The absence of blood vessels within cartilage stresses the importance of nutrient and oxygen delivery from the neighbouring synovium and subchondral bone. Currently, the effects of changes in the subchondral bone microvessel density on cartilage health remain unknown due to the difficulties in simultaneously studying dense bone and the associated small microvessels. Computed tomography (CT) is widely used in the diagnosis of OA, as the use of x-rays provide detailed images of the bone degeneration associated with OA. However, the study of microvessels using CT has been exceptionally difficult due to their small (\u3c 10 µm) size, lack of contrast from neighbouring soft tissues, and proximity to dense bone. The purpose of this thesis was to develop a novel dual-energy micro-computed tomography (DECT) compatible vascular perfusion contrast agent and the associated instrumentation to optimize DECT on pre-clinical, cone-beam micro-CT scanners. The combination of these two techniques would facilitate the simultaneous visualization and quantification of subchondral bone and microvessels within the bone underlining the cartilage (i.e. distal femoral epiphysis and proximal tibial epiphysis) of rats that have undergone an OA-induced surgery. Results gained from this study will further provide information into the role that microvessels may play in OA

Functionalised nanoparticles for molecular imaging

This thesis describes the synthesis of iron oxide nanoparticles for use as contrast agents in biomedical imaging, specifically for MRI. The limitations of single imaging modalities can be overcome by the synergistic combination of two or more imaging techniques, e.g. the low sensitivity but high resolution of MRI complements the high sensitivity but low resolution of PET. The large surface area of superparamagnetic iron oxide nanoparticles (SPION) allows relatively simple functionalisation. The large size of a single combined nanoparticle MRI/PET probe would slow down in vivo movement, diminishing radioactivity before reaching its target. Pre-targeting using a magnetic nanoparticle followed by the injection of the radio-labelled molecule at the correct time will ensure radioactivity remains sufficiently high. Thus, the investigation of dual-modality probe development is also a focus of the thesis. Chapter 2 discusses the preparation of iron oxide nanoparticles with a core diameter of 6 nm via the high temperature thermal decomposition of iron salts. Direct modification to the surface of the nanoparticles was carried out using various small molecules with differing anchoring groups, the most successful being sodium alendronate, a bisphosphonate ligand. Chapter 3 describes the further functionalisation of the nanoparticles. One way this was achieved was by the incorporation of PEG chains of different lengths to increase water solubility and biocompatibility. Functionalisation with a strained alkyne for eventual in vitro/in vivo copper-free cycloaddition with an azide group was also achieved. The PET moiety was designed to be a 68Ga-azido-DOTA complex. Prior to radiolabelling with gallium-68, the copper-free cyclised resultant nanoparticles were characterised by the use of lanthanide analogues (Eu, Tb and Gd). Eu and Tb allowed for fluorescence spectroscopy, while the Gd allowed for relaxivity measurements to be carried out. Unexpected fluorescence results were observed for the Eu and Tb analogues. The Gd-NP conjugates are further investigated in Chapter 4. Combination of both a T1 and T2 moiety results in changes to the relaxivity of the resultant nanoparticle which can act as a dual-weighted MRI probe. The relaxivities are found to vary with modifications to the nanoparticle construct. Finally, preliminary in vitro experiments with macrophages were carried out to investigate whether there was significant preferential uptake between M1 and M2 macrophages. A single-chain variable fragment (scFv) specific to Fractalkine, a chemokine important in the progression of atherosclerosis was prepared, for use as a targeting moiety towards the imaging of vulnerable plaque.Open Acces

40th Rocky Mountain Conference on Analytical Chemistry

Final program, abstracts, and information about the 40th annual meeting of the Rocky Mountain Conference on Analytical Chemistry, co-sponsored by the Colorado Section of the American Chemical Society and the Rocky Mountain Section of the Society for Applied Spectroscopy. Held in Denver, Colorado, July 25 - August 1, 1998

FPGA-based High Performance Diagnostics For Fusion

High performance diagnostics are an important aspect of fusion research. Increasing shot-lengths paired with the requirement for higher accuracy and speed make it mandatory to employ new technology to cope with the increasing demands on digitization and data handling. Field programmable gate arrays (FPGAs) are well known in high performance applications. Their ability to handle multiple fast data streams whilst remaining programmable make them an ideal tool for diagnostic development. Both the improvement of old and the design of new diagnostics can benefit from FPGA-technology and increase the amount of accessible physics significantly. In this work the developments on two FPGA-based diagnostics are presented. In the first part a new open-hardware low-cost FPGA-based digitizer is presented for the MAST-Upgrade (MAST-U) integral electron density interferometer. The system is shown to have an optically limited phase accuracy and a detection bandwidth of over 3.5 MHz. Data is acquired continuously at 20 MS/s and streamed to an acquisition PC via optical fiber. By employing a dual-FPGA approach real-time processing of the density signal can be achieved despite severly limited resources, thus providing a control signal for the MAST-U plasma control system system with less than 8 μs latency. Due to MAST-U being still inoperable, in-situ testing has been conducted on the ASDEX Upgrade, where fast wave physics up to 3.5 MHz could first be observed. The second part presents developments to the Synthetic Aperture Microwave Imaging (SAMI) diagnostic. In addition to improving the utilization of long shot-lengths and enabling dual-polarized acquisition the system has been enhanced to continuously acquire active probing profiles for 2D Doppler back-scattering (DBS), a technique recently developed using SAMI. The aim is to measure pitch angle profiles to derive the edge current density. SAMI has been transferred to the NSTX-Upgrade and integrated into the experiment’s infrastructure, where it has been acquiring data since May 2016. As part of this move an investigation into near-field effects on SAMI’s image reconstruction algorithms was conducted

Topics in image reconstruction for high resolution positron emission tomography

Les problèmes mal posés représentent un sujet d'intérêt interdisciplinaire qui surgires dans la télédétection et des applications d'imagerie. Cependant, il subsiste des questions cruciales pour l'application réussie de la théorie à une modalité d'imagerie. La tomographie d'émission par positron (TEP) est une technique d'imagerie non-invasive qui permet d'évaluer des processus biochimiques se déroulant à l'intérieur d'organismes in vivo. La TEP est un outil avantageux pour la recherche sur la physiologie normale chez l'humain ou l'animal, pour le diagnostic et le suivi thérapeutique du cancer, et l'étude des pathologies dans le coeur et dans le cerveau. La TEP partage plusieurs similarités avec d'autres modalités d'imagerie tomographiques, mais pour exploiter pleinement sa capacité à extraire le maximum d'information à partir des projections, la TEP doit utiliser des algorithmes de reconstruction d'images à la fois sophistiquée et pratiques. Plusieurs aspects de la reconstruction d'images TEP ont été explorés dans le présent travail. Les contributions suivantes sont d'objet de ce travail: Un modèle viable de la matrice de transition du système a été élaboré, utilisant la fonction de réponse analytique des détecteurs basée sur l'atténuation linéaire des rayons y dans un banc de détecteur. Nous avons aussi démontré que l'utilisation d'un modèle simplifié pour le calcul de la matrice du système conduit à des artefacts dans l'image. (IEEE Trans. Nucl. Sei., 2000) );> La modélisation analytique de la dépendance décrite à l'égard de la statistique des images a simplifié l'utilisation de la règle d'arrêt par contre-vérification (CV) et a permis d'accélérer la reconstruction statistique itérative. Cette règle peut être utilisée au lieu du procédé CV original pour des projections aux taux de comptage élevés, lorsque la règle CV produit des images raisonnablement précises. (IEEE Trans. Nucl. Sei., 2001) Nous avons proposé une méthodologie de régularisation utilisant la décomposition en valeur propre (DVP) de la matrice du système basée sur l'analyse de la résolution spatiale. L'analyse des caractéristiques du spectre de valeurs propres nous a permis d'identifier la relation qui existe entre le niveau optimal de troncation du spectre pour la reconstruction DVP et la résolution optimale dans l'image reconstruite. (IEEE Trans. Nucl. Sei., 2001) Nous avons proposé une nouvelle technique linéaire de reconstruction d'image événement-par-événement basée sur la matrice pseudo-inverse régularisée du système. L'algorithme représente une façon rapide de mettre à jour une image, potentiellement en temps réel, et permet, en principe, la visualisation instantanée de distribution de la radioactivité durant l'acquisition des données tomographiques. L'image ainsi calculée est la solution minimisant les moindres carrés du problème inverse régularisé.Abstract: Ill-posed problems are a topic of an interdisciplinary interest arising in remote sensing and non-invasive imaging. However, there are issues crucial for successful application of the theory to a given imaging modality. Positron emission tomography (PET) is a non-invasive imaging technique that allows assessing biochemical processes taking place in an organism in vivo. PET is a valuable tool in investigation of normal human or animal physiology, diagnosing and staging cancer, heart and brain disorders. PET is similar to other tomographie imaging techniques in many ways, but to reach its full potential and to extract maximum information from projection data, PET has to use accurate, yet practical, image reconstruction algorithms. Several topics related to PET image reconstruction have been explored in the present dissertation. The following contributions have been made: (1) A system matrix model has been developed using an analytic detector response function based on linear attenuation of [gamma]-rays in a detector array. It has been demonstrated that the use of an oversimplified system model for the computation of a system matrix results in image artefacts. (IEEE Trans. Nucl. Sci., 2000); (2) The dependence on total counts modelled analytically was used to simplify utilisation of the cross-validation (CV) stopping rule and accelerate statistical iterative reconstruction. It can be utilised instead of the original CV procedure for high-count projection data, when the CV yields reasonably accurate images. (IEEE Trans. Nucl. Sci., 2001); (3) A regularisation methodology employing singular value decomposition (SVD) of the system matrix was proposed based on the spatial resolution analysis. A characteristic property of the singular value spectrum shape was found that revealed a relationship between the optimal truncation level to be used with the truncated SVD reconstruction and the optimal reconstructed image resolution. (IEEE Trans. Nucl. Sci., 2001); (4) A novel event-by-event linear image reconstruction technique based on a regularised pseudo-inverse of the system matrix was proposed. The algorithm provides a fast way to update an image potentially in real time and allows, in principle, for the instant visualisation of the radioactivity distribution while the object is still being scanned. The computed image estimate is the minimum-norm least-squares solution of the regularised inverse problem