313 research outputs found

    Automatic generation of statistical pose and shape models for articulated joints

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    Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint like the wrist. We present a novel framework for simultaneous registration and segmentation of multiple 3-D (CT or MR) volumes of different subjects at various articulated positions. The framework starts with a pose model generated from 3-D volumes captured at different articulated positions of a single subject (template). This initial pose model is used to register the template volume to image volumes from new subjects. During this process, the Grow-Cut algorithm is used in an iterative refinement of the segmentation of the bone along with the pose parameters. As each new subject is registered and segmented, the pose model is updated, improving the accuracy of successive registrations. We applied the algorithm to CT images of the wrist from 25 subjects, each at five different wrist positions and demonstrated that it performed robustly and accurately. More importantly, the resulting segmentations allowed a statistical pose model of the carpal bones to be generated automatically without interaction. The evaluation results show that our proposed framework achieved accurate registration with an average mean target registration error of mm. The automatic segmentation results also show high consistency with the ground truth obtained semi-automatically. Furthermore, we demonstrated the capability of the resulting statistical pose and shape models by using them to generate a measurement tool for scaphoid-lunate dissociation diagnosis, which achieved 90% sensitivity and specificity

    Stroke penumbra defined by an MRI-based oxygen challenge technique: 2. Validation based on the consequences of reperfusion

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    Magnetic resonance imaging (MRI) with oxygen challenge (T2* OC) uses oxygen as a metabolic biotracer to define penumbral tissue based on CMRO2 and oxygen extraction fraction. Penumbra displays a greater T2* signal change during OC than surrounding tissue. Since timely restoration of cerebral blood flow (CBF) should salvage penumbra, T2* OC was tested by examining the consequences of reperfusion on T2* OC-defined penumbra. Transient ischemia (109±20 minutes) was induced in male Sprague-Dawley rats (n=8). Penumbra was identified on T2*-weighted MRI during OC. Ischemia and ischemic injury were identified on CBF and apparent diffusion coefficient maps, respectively. Reperfusion was induced and scans repeated. T2 for final infarct and T2* OC were run on day 7. T2* signal increase to OC was 3.4% in contralateral cortex and caudate nucleus and was unaffected by reperfusion. In OC-defined penumbra, T2* signal increased by 8.4%±4.1% during ischemia and returned to 3.25%±0.8% following reperfusion. Ischemic core T2* signal increase was 0.39%±0.47% during ischemia and 0.84%±1.8% on reperfusion. Penumbral CBF increased from 41.94±13 to 116.5±25 mL per 100 g per minute on reperfusion. On day 7, OC-defined penumbra gave a normal OC response and was located outside the infarct. T2* OC-defined penumbra recovered when CBF was restored, providing further validation of the utility of T2* OC for acute stroke management

    Stroke penumbra defined by an MRI-based oxygen challenge technique: 1. validation using [14C]2-deoxyglucose autoradiography

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    Accurate identification of ischemic penumbra will improve stroke patient selection for reperfusion therapies and clinical trials. Current magnetic resonance imaging (MRI) techniques have limitations and lack validation. Oxygen challenge T2* MRI (T2* OC) uses oxygen as a biotracer to detect tissue metabolism, with penumbra displaying the greatest T2* signal change during OC. [14C]2-deoxyglucose (2-DG) autoradiography was combined with T2* OC to determine metabolic status of T2*-defined penumbra. Permanent middle cerebral artery occlusion was induced in anesthetized male Sprague-Dawley rats (n=6). Ischemic injury and perfusion deficit were determined by diffusion- and perfusion-weighted imaging, respectively. At 147±32 minutes after stroke, T2* signal change was measured during a 5-minute 100% OC, immediately followed by 125 μCi/kg 2-DG, intravenously. Magnetic resonance images were coregistered with the corresponding autoradiograms. Regions of interest were located within ischemic core, T2*-defined penumbra, equivalent contralateral structures, and a region of hyperglycolysis. A T2* signal increase of 9.22%±3.9% (mean±s.d.) was recorded in presumed penumbra, which displayed local cerebral glucose utilization values equivalent to contralateral cortex. T2* signal change was negligible in ischemic core, 3.2%±0.78% in contralateral regions, and 1.41%±0.62% in hyperglycolytic tissue, located outside OC-defined penumbra and within the diffusion abnormality. The results support the utility of OC-MRI to detect viable penumbral tissue follow

    Potential use of oxygen as a metabolic biosensor in combination with T2*-weighted MRI to define the ischemic penumbra

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    We describe a novel magnetic resonance imaging technique for detecting metabolism indirectly through changes in oxyhemoglobin:deoxyhemoglobin ratios and T2* signal change during ‘oxygen challenge’ (OC, 5 mins 100% O2). During OC, T2* increase reflects O2 binding to deoxyhemoglobin, which is formed when metabolizing tissues take up oxygen. Here OC has been applied to identify tissue metabolism within the ischemic brain. Permanent middle cerebral artery occlusion was induced in rats. In series 1 scanning (n=5), diffusion-weighted imaging (DWI) was performed, followed by echo-planar T2* acquired during OC and perfusion-weighted imaging (PWI, arterial spin labeling). Oxygen challenge induced a T2* signal increase of 1.8%, 3.7%, and 0.24% in the contralateral cortex, ipsilateral cortex within the PWI/DWI mismatch zone, and ischemic core, respectively. T2* and apparent diffusion coefficient (ADC) map coregistration revealed that the T2* signal increase extended into the ADC lesion (3.4%). In series 2 (n=5), FLASH T2* and ADC maps coregistered with histology revealed a T2* signal increase of 4.9% in the histologically defined border zone (55% normal neuronal morphology, located within the ADC lesion boundary) compared with a 0.7% increase in the cortical ischemic core (92% neuronal ischemic cell change, core ADC lesion). Oxygen challenge has potential clinical utility and, by distinguishing metabolically active and inactive tissues within hypoperfused regions, could provide a more precise assessment of penumbra

    The organisation and delivery of health improvement in general practice and primary care: a scoping study

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    Background This project examines the organisation and delivery of health improvement activities by and within general practice and the primary health-care team. The project was designed to examine who delivers these interventions, where they are located, what approaches are developed in practices, how individual practices and the primary health-care team organise such public health activities, and how these contribute to health improvement. Our focus was on health promotion and ill-health prevention activities. Aims The aim of this scoping exercise was to identify the current extent of knowledge about the health improvement activities in general practice and the wider primary health-care team. The key objectives were to provide an overview of the range and type of health improvement activities, identify gaps in knowledge and areas for further empirical research. Our specific research objectives were to map the range and type of health improvement activity undertaken by general practice staff and the primary health-care team based within general practice; to scope the literature on health improvement in general practice or undertaken by health-care staff based in general practice and identify gaps in the evidence base; to synthesise the literature and identify effective approaches to the delivery and organisation of health improvement interventions in a general practice setting; and to identify the priority areas for research as defined by those working in general practice. Methods We undertook a comprehensive search of the literature. We followed a staged selection process involving reviews of titles and abstracts. This resulted in the identification of 1140 papers for data extraction, with 658 of these papers selected for inclusion in the review, of which 347 were included in the evidence synthesis. We also undertook 45 individual and two group interviews with primary health-care staff. Findings Many of the research studies reviewed had some details about the type, process or location, or who provided the intervention. Generally, however, little attention is paid in the literature to examining the impact of the organisational context on the way services are delivered or how this affects the effectiveness of health improvement interventions in general practice. We found that the focus of attention is mainly on individual prevention approaches, with practices engaging in both primary and secondary prevention. The range of activities suggests that general practitioners do not take a population approach but focus on individual patients. However, it is clear that many general practitioners see health promotion as an integral part of practice, whether as individual approaches to primary or secondary health improvement or as a practice-based approach to improving the health of their patients. Our key conclusion is that there is currently insufficient good evidence to support many of the health improvement interventions undertaken in general practice and primary care more widely. Future Research Future research on health improvement in general practice and by the primary health-care team needs to move beyond clinical research to include delivery systems and be conducted in a primary care setting. More research needs to examine areas where there are chronic disease burdens – cancer, dementia and other disabilities of old age. Reviews should be commissioned that examine the whole prevention pathway for health problems that are managed within primary care drawing together research from general practice, pharmacy, community engagement, etc

    Reliability of digital ulcer definitions as proposed by the UK Scleroderma Study Group:A challenge for clinical trial design

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    INTRODUCTION: The reliability of clinician grading of systemic sclerosis–related digital ulcers has been reported to be poor to moderate at best, which has important implications for clinical trial design. The aim of this study was to examine the reliability of new proposed UK Scleroderma Study Group digital ulcer definitions among UK clinicians with an interest in systemic sclerosis. METHODS: Raters graded (through a custom-built interface) 90 images (80 unique and 10 repeat) of a range of digital lesions collected from patients with systemic sclerosis. Lesions were graded on an ordinal scale of severity: ‘no ulcer’, ‘healed ulcer’ or ‘digital ulcer’. RESULTS: A total of 23 clinicians – 18 rheumatologists, 3 dermatologists, 1 hand surgeon and 1 specialist rheumatology nurse – completed the study. A total of 2070 (1840 unique + 230 repeat) image gradings were obtained. For intra-rater reliability, across all images, the overall weighted kappa coefficient was high (0.71) and was moderate (0.55) when averaged across individual raters. Overall inter-rater reliability was poor (0.15). CONCLUSION: Although our proposed digital ulcer definitions had high intra-rater reliability, the overall inter-rater reliability was poor. Our study highlights the challenges of digital ulcer assessment by clinicians with an interest in systemic sclerosis and provides a number of useful insights for future clinical trial design. Further research is warranted to improve the reliability of digital ulcer definition/rating as an outcome measure in clinical trials, including examining the role for objective measurement techniques, and the development of digital ulcer patient–reported outcome measures
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