Quantification of human body fat tissue percentage by MRI

Müller, Hans‐Peter; Raudies, Florian; Unrath, Alexander; Neumann, Heiko; Ludolph, Albert C.; Kassubek, Jan

doi:10.1002/nbm.1549

Cited by 60 publications

(52 citation statements)

References 39 publications

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“…The volume and distribution of atherosclerotic plaques was measured semiautomatically as a function of the threshold value of hyperdense areas with the in-house developed software, IBAS (Intensity-Based Analysis Software) [13]. Calcified plaques (fig.…”

Section: Methodsmentioning

confidence: 99%

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Body Fat Distribution as a Risk Factor for Cerebrovascular Disease: An MRI-Based Body Fat Quantification Study

et al. 2013

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Background: While adiposity is a well-established risk factor for cardiovascular disease, the association between adiposity and cerebrovascular disease is not entirely understood. For example, common methods to quantify body fat volume such as body mass index, waist circumference and waist-to-hip ratio are not suitable to identify the complex distribution patterns of body fat and its relation to cerebrovascular pathology. In view of a better understanding of the association between fat distribution and cerebrovascular disorders, the aim of the study was to perform measurements of body fat distribution patterns and body fat volumes in correlation to arteriosclerosis of the brain-feeding arteries and white matter lesion load (WMLL). Methods: In this study we performed a magnetic resonance imaging (MRI)-based volumetric differential analysis of subcutaneous and visceral body fat distribution in 25 patients with MRI-proven hyperacute ischemic stroke. For the measurement of adipose tissue volume and tissue distribution automatic labeling analysis software was used. A correlation analysis of MRI volumetric measurements of subcutaneous and visceral body fat, atherosclerotic plaque load of the brain-feeding arteries measured by computed tomography angiography, and WMLL measured by MRI volumetry of the whole brain was performed. Results: The normalized total abdominal adipose tissue and the normalized subcutaneous abdominal adipose tissue showed no significant correlation with either WMLL or total plaque volume. In contrast, the normalized visceral adipose tissue showed a significant correlation with WMLL volume. Visceral adipose tissue as a percentage of total adipose tissue showed a significant correlation with WMLL. In particular, the percentage of visceral adipose tissue rather than total body fat volume strongly correlated with atherosclerosis and ischemic cerebral lesions. Furthermore, the volume of both soft and calcified plaques correlated significantly with WMLL. Conclusions: Our results contribute to existing studies about the association of different patterns of fat distribution with atherosclerosis of the brain-feeding arteries, in particular highlighting the importance of visceral adiposity as a risk factor for cerebrovascular disease. The percentage of visceral adipose tissue in total adipose tissue has the potential of a sensitive parameter and might become a relevant new epidemiological marker, showing highly significant correlations with well-established markers of cerebrovascular disease. In conclusion, the percentage of visceral adipose tissue by itself has to be regarded as a risk factor for both small vessel cerebrovascular disease and cerebral atherosclerosis of the large-to-medium-sized arteries.

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Section: Methodsmentioning

confidence: 99%

“…For the measurement of adipose tissue volume and distribution, the in-house developed software package, ATLAS (Automatic Tissue Labeling Analysis Software) was used, as described previously [13]. An example of the measurement method is depicted in figure 1c.…”

Section: Methodsmentioning

confidence: 99%

Body Fat Distribution as a Risk Factor for Cerebrovascular Disease: An MRI-Based Body Fat Quantification Study

et al. 2013

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“…The quantification of subcutaneous and visceral fat was done using the automatic tissue and labeling analysis software ATLAS and in-house developed software from the University of Ulm (22). Afterwards, manual correction by certified students was applied.…”

Section: Measurementsmentioning

confidence: 99%

Translating Pharmacological Findings from Hypothyroid Rodents to Euthyroid Humans: Is There a Functional Role of Endogenous 3,5-T2?

Pietzner

Lehmphul

Friedrich

et al. 2015

Thyroid

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Background: During the last two decades, it has become obvious that 3,5-diiodothyronine (3,5-T2), a wellknown endogenous metabolite of the thyroid hormones thyroxine (T4) or triiodothyronine (T3), not only represents a simple degradation intermediate of the former but also exhibits specific metabolic activities. Administration of 3,5-T2 to hypothyroid rodents rapidly stimulated their basal metabolic rate, prevented highfat diet-induced obesity as well as steatosis, and increased oxidation of long-chain fatty acids. Objective: The aim of the present study was to analyze associations between circulating 3,5-T2 in human serum and different epidemiological parameters, including age, sex, or smoking, as well as measures of anthropometry, glucose, and lipid metabolism. Methods: 3,5-T2 concentrations were measured by a recently developed immunoassay in sera of 761 euthyroid participants of the population-based Study of Health in Pomerania. Subsequently, analysis of variance and multivariate linear regression analysis were performed. Results: Serum 3,5-T2 concentrations exhibited a right-skewed distribution, resulting in a median serum concentration of 0.24 nM (1st quartile: 0.20 nM; 3rd quartile: 0.37 nM). Significant associations between 3,5-T2 and serum fasting glucose, thyrotropin (TSH), as well as leptin concentrations were detected ( p < 0.05). Interestingly, the association to leptin concentrations seemed to be mediated by TSH. Age, sex, smoking, and blood lipid profile parameters did not show significant associations with circulating 3,5-T2. Conclusion: Our findings from a healthy euthyroid population may point toward a physiological link between circulating 3,5-T2 and glucose metabolism.

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“…It is also possible to use bioelectric impedance (BIA), dual energy X-ray absorptiometry (DEXA), computed tomography (CT) or nuclear magnet resonance (NMR) [13]. The best option is to measure the areas of lipid stores after NMR imaging using custom software [14]. This is unfortunately far from manageable in everyday practice; therefore we need cheaper and easier methods to monitor centralization of lipid stores.…”

Section: Introductionmentioning

confidence: 99%

Subcutaneous adipose tissue measurements and better metabolic prediction

et al. 2013

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AbstractThe aim of the study was to establish the importance of an additional measurement of subcutaneous adipose tissue thickness (SAT) on a predetermined position on the waistline, and its relation to waist measurements as an improvement of metabolic prediction in equally obese subjects. One hundred and forty two consecutive patients were enrolled in the study: stratified by weight as normal (body mass index — BMI 20–25 kg/m2), overweight (BMI 25–30 kg/m2) and obese (BMI >30 kg/m2); and by fasting glucose level as normoglycemic, impaired fasting glucose (IFG), or with type 2 diabetes mellitus (T2DM). SAT was measured in relaxed expiration, 3 cm left of the umbilicus, with ultrasound. Fasting blood samples for glucose, insulin and HbAlc were taken. Waist circumference was slightly higher in the IFG (112.8 cm) and normoglycemic groups (115.62 cm), compared to T2DM (108.15 cm). The T2DM group had a lower average SAT (2.7 cm) than both the IFG group (3.4 cm, p<0.01) and the normoglycemic group (4.2cm, p=0.001). The homeostatic model of assessment for insulin resistance (HOMA IR) was the lowest in normoglycemic and the highest in IFG group. Waistline radius to SAT ratio provides better insight into the deterioration of glucose metabolism than standard anthropometric markers of abdominal obesity in equally obese patients.

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Quantification of human body fat tissue percentage by MRI

Cited by 60 publications

References 39 publications

Body Fat Distribution as a Risk Factor for Cerebrovascular Disease: An MRI-Based Body Fat Quantification Study

Body Fat Distribution as a Risk Factor for Cerebrovascular Disease: An MRI-Based Body Fat Quantification Study

Translating Pharmacological Findings from Hypothyroid Rodents to Euthyroid Humans: Is There a Functional Role of Endogenous 3,5-T2?

Subcutaneous adipose tissue measurements and better metabolic prediction

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