Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity

Shen, Jun; Baum, Thomas; Cordes, Christian; B, Ott; Skurk, Thomas; Kooijman, Hendrik; Rummeny, Ernst J.; Hauner, Hans; Menze, Bjoern; Karampinos, Dimitrios C.

doi:10.1016/j.ejrad.2016.06.006

Cited by 33 publications

(33 citation statements)

References 29 publications

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“…A custom-built post-processing algorithm was used for automatic classification of the different abdominal tissue compartments based on the water-separated and fat-separated images from the two-echo Dixon scan, which has been described extensively in earlier studies. 45 , 46 SAT, VAT and non-adipose tissue (water) volumes were determined by summing the segmented regions from the liver dome down to the center of the femoral head. Non-VAT depots (for example, intermuscular, around spine) were excluded manually slice by slice.…”

Section: Methodsmentioning

confidence: 99%

Association of proton density fat fraction in adipose tissue with imaging-based and anthropometric obesity markers in adults

et al. 2017

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Background/Objectives:The purpose of this study was to examine the relationship of the proton density fat fraction (PDFF), measured by magnetic resonance imaging (MRI), of supraclavicular and gluteal adipose tissue with subcutaneous and visceral adipose tissue (SAT and VAT) volumes, liver fat fraction and anthropometric obesity markers. The supraclavicular fossa was selected as a typical location where brown adipocytes may be present in humans and the gluteal region was selected as a typical location enclosing primarily white adipocytes.Subjects/Methods:In this cross-sectional study, 61 adults (44 women, median age 29.3 years, range 21–68 years) underwent an MRI examination of the neck and the abdomen/pelvis (3T, Ingenia, Philips Healthcare). PDFF maps of the supraclavicular and gluteal adipose tissue and the liver were generated. Volumes of SAT and VAT were calculated and supraclavicular and subcutaneous fat were segmented using custom-built post-processing algorithms. Body mass index (BMI), waist circumference and waist-to-height ratio were recorded. Statistical analysis was conducted using the Student's t-test and Pearson correlation analysis.Results:Mean supraclavicular PDFF was 75.3±4.7% (range 65.4–83.8%) and mean gluteal PDFF was 89.7±2.9% (range 82.2-94%), resulting in a significant difference (P<0.0001). Supraclavicular PDFF was positively correlated with VAT (r=0.76, P<0.0001), SAT (r=0.73, P<0.0001), liver PDFF (r=0.42, P=0.0008) and all measured anthropometric obesity markers. Gluteal subcutaneous PDFF also correlated with VAT (r=0.59, P<0.0001), SAT (r=0.63, P<0.0001), liver PDFF (r=0.3, P=0.02) and anthropometric obesity markers.Conclusions:The positive correlations between adipose tissue PDFF and imaging, as well as anthropometric obesity markers suggest that adipose tissue PDFF may be useful as a biomarker for improving the characterization of the obese phenotype, for risk stratification and for selection of appropriate treatment strategies.

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Section: Methodsmentioning

confidence: 99%

Association of proton density fat fraction in adipose tissue with imaging-based and anthropometric obesity markers in adults

et al. 2017

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“…The first has been more commonly linked to comorbidities such as hypertension, dyslipidemia, and T2D [15] , [16] , [17] , while the second confers a neutral or even protective effect against metabolic diseases [17] , [18] . To account for these differences, parameters like waist-to-hip ratio, magnetic resonance imaging or dual-energy X-ray absorptiometry [19] , [20] have been used as bona fide predictors of metabolic diseases and as useful parameters for researchers to understand how fat accumulation determines the risk of these diseases [12] , [21] , [22] .…”

Section: Metabolic Diseasesmentioning

confidence: 99%

Shortcuts to a functional adipose tissue: The role of small non-coding RNAs

2017

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Metabolic diseases such as type 2 diabetes are a major public health issue worldwide. These diseases are often linked to a dysfunctional adipose tissue. Fat is a large, heterogenic, pleiotropic and rather complex tissue. It is found in virtually all cavities of the human body, shows unique plasticity among tissues, and harbors many cell types in addition to its main functional unit – the adipocyte. Adipose tissue function varies depending on the localization of the fat depot, the cell composition of the tissue and the energy status of the organism. While the white adipose tissue (WAT) serves as the main site for triglyceride storage and acts as an important endocrine organ, the brown adipose tissue (BAT) is responsible for thermogenesis. Beige adipocytes can also appear in WAT depots to sustain heat production upon certain conditions, and it is becoming clear that adipose tissue depots can switch phenotypes depending on cell autonomous and non-autonomous stimuli. To maintain such degree of plasticity and respond adequately to changes in the energy balance, three basic processes need to be properly functioning in the adipose tissue: i) adipogenesis and adipocyte turnover, ii) metabolism, and iii) signaling. Here we review the fundamental role of small non-coding RNAs (sncRNAs) in these processes, with focus on microRNAs, and demonstrate their importance in adipose tissue function and whole body metabolic control in mammals.

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“…One is the difference between abdominal and trunk regions assessed by the respective measurements; another, the limited precision of segmental, multifrequency BIA . In addition, body water, the only parameter measured and not estimated by BIA, is affected by the electrolyte balance, which depends on nutrition intake or exercise and differs between individuals and during the day . Therefore, BIA as well as multifrequency BIA results might be influenced by confounding factors, and these results should not be generalized to other BIA devices .…”

Section: Discussionmentioning

confidence: 99%

“…First, a fuzzy C‐means clustering algorithm that separated voxels in the air from those inside the body was applied to the whole stack to determine the body surface and a total abdominal (TA) volume of interest (VOI). Then an operator previously trained by an expert radiologist manually segmented the visceral (VS) VOI section by section because, in our case, automatic methods were not available. The abdominal and paraspinal muscles guided this segmentation.…”

Section: Methodsmentioning

confidence: 99%

Magnetic Resonance Imaging and Bioelectrical Impedance Analysis to Assess Visceral and Abdominal Adipose Tissue

Chaudry

Grimm

Friedberger

et al. 2020

Obesity

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What is already known?► Visceral adipose tissue, which is relevant for several pathologies, is commonly assessed by magnetic resonance imaging (MRI) using different scanning protocols. Biolelectrical impedence analysis (BIA) is often used as a cost-effective and widely available alternative to MRI when quantifying total adipose tissue. What does this study add?► This study compares BIA with Dixon fat fraction map results and volumetric fat measurements with direct fat fraction results.Objective: This study aimed to compare a state-of-the-art bioelectrical impedance analysis (BIA) device with two-point Dixon magnetic resonance imaging (MRI) for the quantification of visceral adipose tissue (VAT) as a health-related risk factor. Methods: A total of 63 male participants were measured using a 3-T MRI scanner and a segmental, multifrequency BIA device. MRI generated fat fraction (FF) maps, in which VAT volume, total abdominal adipose tissue volume, and FF of visceral and total abdominal compartments were quantified. BIA estimated body fat mass and VAT area.Results: Coefficients of determination between abdominal (r 2 = 0.75) and visceral compartments (r 2 = 0.78) were similar for both groups, but slopes differed by a factor of two. The ratio of visceral to total abdominal FF was increased in older men compared with younger men. This difference was not detected with BIA. MRI and BIA measurements of the total abdominal volume correlated moderately (r 2 = 0.31-0.56), and visceral measurements correlated poorly (r 2 = 0.13-0.44).Conclusions: Visceral BIA measurements agreed better with MRI measurements of the total abdomen than of the visceral compartment, indicating that BIA visceral fat area assessment cannot differentiate adipose tissue between visceral and abdominal compartments in young and older participants.Obesity (2020) 28, 277-283.

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Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity

Cited by 33 publications

References 29 publications

Association of proton density fat fraction in adipose tissue with imaging-based and anthropometric obesity markers in adults

Association of proton density fat fraction in adipose tissue with imaging-based and anthropometric obesity markers in adults

Shortcuts to a functional adipose tissue: The role of small non-coding RNAs

Magnetic Resonance Imaging and Bioelectrical Impedance Analysis to Assess Visceral and Abdominal Adipose Tissue

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