20 research outputs found

    Sub‐phenotyping Metabolic Disorders Using Body Composition: An Individualized, Nonparametric Approach Utilizing Large Data Sets

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    Objective This study performed individual-centric, data-driven calculations of propensity for coronary heart disease (CHD) and type 2 diabetes (T2D), utilizing magnetic resonance imaging-acquired body composition measurements, for sub-phenotyping of obesity and nonalcoholic fatty liver disease (NAFLD). Methods A total of 10,019 participants from the UK Biobank imaging substudy were included and analyzed for visceral and abdominal subcutaneous adipose tissue, muscle fat infiltration, and liver fat. An adaption of the k-nearest neighbors algorithm was applied to the imaging variable space to calculate individualized CHD and T2D propensity and explore metabolic sub-phenotyping within obesity and NAFLD. Results The ranges of CHD and T2D propensity for the whole cohort were 1.3% to 58.0% and 0.6% to 42.0%, respectively. The diagnostic performance, area under the receiver operating characteristic curve (95% CI), using disease propensities for CHD and T2D detection was 0.75 (0.73-0.77) and 0.79 (0.77-0.81). Exploring individualized disease propensity, CHD phenotypes, T2D phenotypes, comorbid phenotypes, and metabolically healthy phenotypes were found within obesity and NAFLD. Conclusions The adaptive k-nearest neighbors algorithm allowed an individual-centric assessment of each individual’s metabolic phenotype moving beyond discrete categorizations of body composition. Within obesity and NAFLD, this may help in identifying which comorbidities a patient may develop and consequently enable optimization of treatment

    Individual and Collective Identities in Russian Orthodoxy

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    This chapter addresses trends within Russian Orthodoxy from the point of view of the formation of collective and individual identities and their interaction within and around the church. It deals with both discursive and practical domains, and in addition to an analysis of theological debates it draws also upon fieldwork, particularly with regard to worship of the newly canonized Russian royal family

    Quantitative abdominal fat estimation using MRI

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    This paper introduces a new method for automatic quantification of subcutaneous, visceral and nonvisceral internal fat from MR-images acquired using the two point Dixon technique in the abdominal region. The method includes (1) a three dimensional phase unwrapping to provide water and fat images, (2) an image intensity inhomogeneity correction, and (3) a morphon based registration and segmentation of the tissue. This is followed by an integration of the corrected fat images within the different fat compartments that avoids the partial volume effects associated with traditional fat segmentation methods. The method was tested on 18 subjects before and after a period of fastfood hyper-alimentation showing high stability and performance in all analysis steps. 1

    Fat infiltration in the thigh muscles is associated with symptomatic spinal stenosis and reduced physical functioning in adults with achondroplasia

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    BackgroundSymptomatic spinal stenosis is a prevalent complication in adults with achondroplasia. Increased muscle fat infiltration (MFI) and reduced thigh muscle volumes have also been reported, but the pathophysiology is poorly understood. We explored whether the increased MFI and reduced thigh muscle volumes were associated with the presence of symptomatic spinal stenosis and physical functioning.MethodsMFI and thigh muscle volumes were assessed by MRI in 40 adults with achondroplasia, and compared to 80 average-statured controls, matched for BMI, gender, and age. In achondroplasia participants, the six-minute walk-test (6MWT), the 30-s sit-to-stand test (30sSTS), and a questionnaire (the IPAQ) assessed physical functioning.ResultsSymptomatic spinal stenosis was present in 25 of the participants (the stenosis group), while 15 did not have stenosis (the non-stenosis group). In the stenosis group, 84% (21/25) had undergone at least one spinal decompression surgery. The stenosis group had significantly higher MFI than the non-stenosis group, with an age-, gender and BMI-adjusted difference in total MFI of 3.3 percentage points (pp) (95% confidence interval [CI] 0.04 to 6.3 pp; p = 0.03). Compared to matched controls, the mean age-adjusted difference was 3.3 pp (95% CI 1.7 to 4.9 pp; p &amp;lt; 0.01). The non-stenosis group had MFI similar to controls (age-adjusted difference - 0.9 pp, 95% CI - 3.4 to 1.8 pp; p = 0.51). MFI was strongly correlated with the 6MWT (r = - 0.81, - 0.83, and - 0.86; all p-values &amp;lt; 0.01), and moderately correlated with the 30sSTS (r = - 0.56, - 0.57, and - 0.59; all p-values &amp;lt; 0.01). There were no significant differences in muscle volumes or physical activity level between the stenosis group and the non-stenosis group.ConclusionIncreased MFI in the thigh muscles was associated with the presence of symptomatic spinal stenosis, reduced functional walking capacity, and reduced lower limb muscle strength. The causality between spinal stenosis, accumulation of thigh MFI, and surgical outcomes need further study. We have demonstrated that MRI might serve as an objective muscle biomarker in future achondroplasia studies, in addition to functional outcome measures. The method could potentially aid in optimizing the timing of spinal decompression surgery and in planning of post-surgery rehabilitation.Funding Agencies|Dam Foundation [2019/FO249324]; The Norwegian National Advisory Unit on Rare Disorders (NKSD) [226038, 226053]</p

    Quantitative muscle analysis in facioscapulohumeral muscular dystrophy using whole-body fat-referenced MRI: Protocol development, multicenter feasibility, and repeatability

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    INTRODUCTION/AIMS: Functional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole-body fat-referenced magnetic resonance imaging (MRI) for use in multisite clinical trials. METHODS: Subjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0-5), were enrolled at six sites and imaged twice 4-12 weeks apart with T1-weighted two-point Dixon MRI covering the torso and upper and lower extremities. Thirty-six muscles were volumetrically segmented using semi-automatic multi-atlas-based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat-referenced quantification. RESULTS: Seventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within-patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%. DISCUSSION: We developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders
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