Free‐breathing Magnetic Resonance Imaging Assessment of Body Composition in Healthy and Overweight Children

Ly, Karrie V.; Armstrong, Tess; Yeh, Joanna; Ghahremani, Shahnaz; Kim, Grace H.; Wu, Holden H.; Calkins, Kara L.

doi:10.1097/mpg.0000000000002309

Cited by 12 publications

(7 citation statements)

References 38 publications

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“…Оба позволяют измерить площадь ВЖТ, определить общий объем жировой ткани и объемы ее различных депо путем многоуровневого сканирования [17,12,24]. Применение КТ в детской практике ограничено ввиду ионизирующего излучения [17], в связи с чем предпочтительной является процедура МРТ, которая к тому же осуществляется при свободном дыхании [12,25]. Однако МРТ является дорогостоящим методом, чем обусловлена его низкая доступность [26].…”

Section: измерение висцеральной жировой тканиunclassified

Visceral Obesity: Terminology, Measurement, and Its Correlation with Inflammation

Tarabrina

Огородова

Федорова

2022

Vopr. sovr. pediatr.

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The prevalence of childhood obesity in the world is significant and it is topical issue due to the high risk of chronic non-communicable diseases development. This article presents the analysis of pathogenetic role of visceral obesity, describes modern methods for measuring visceral adipose tissue, discusses major terminology on obesity. The current data on inflammation induced by excess of visceral adipose tissue and inflammasome’s role in this process are summed up. All the findings are crucial for the development of tools for prevention any obesity associated adverse effects in children.

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Section: измерение висцеральной жировой тканиunclassified

Visceral Obesity: Terminology, Measurement, and Its Correlation with Inflammation

Tarabrina

Огородова

Федорова

2022

Vopr. sovr. pediatr.

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“…Despite the advantages of qMRI in terms of accuracy and lack of irradiation compared to DXA and CT, its use in the pediatric population is relatively limited (1)(2)(3)(4)13,15,20,23,25,32,33,45,(49)(50)(51). Unlike DXA, MRI provides volumetric three-dimensional imaging, and can be used in healthy volunteers and infants without irradiation.…”

Section: Quantitative Mri (Qmri)mentioning

confidence: 99%

“…Magnetic resonance imaging (MRI) is the emerging technique to assess body composition in children and adolescents (23). It has been proven that MRI has an accuracy comparable to that of CT to quantify SAT and VAT in obese adults (24) and adolescents (20).…”

Section: Introductionmentioning

confidence: 99%

“…MRI does not require radiation, which is the main limitation for the use of CT in children and adolescents. MRI is particularly suitable to quantify abdominal fat in children because it requires only a few minutes without compromise in imaging quality (23). MRI also allows an estimation of the fat fraction of brown adipose tissue (BAT), expressed as a percentage, which is inversely associated with VAT (25).…”

Section: Introductionmentioning

confidence: 99%

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Imaging of body composition in children

Simoni¹,

Guglielmi²,

Gómez³

2020

Quant Imaging Med Surg

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Overweight and obesity in children and adolescents have become a worldwide public health concern with an ever-increasing prevalence. An excessive accumulation of intraabdominal fat tissue increases the risk of developing insulin resistance, diabetes, and cardiovascular diseases in adulthood. Body composition has a role in metabolism regulation in children and adolescents with differences between genders and age groups. Until recently, Air Displacement Plethysmography and Dual-energy X-ray Absorptiometry (DXA) have been the most common techniques used to assess body composition in children.Ultrasound (US) is an accurate, readily available, and radiation-free technique to quantify intra-abdominal fat in adults, but its use in children has not yet been validated. Computed tomography (CT) is a reliable tool to assess body composition, but its use in children should be avoided due to the significant radiation burden.Quantitative Magnetic Resonance Imaging (qMRI) provides an accurate measurement of body composition, through the quantification of the visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and brown adipose tissue (BAT), as well as lean mass. Furthermore, qMRI provides other significant estimates such as the Proton Density Fat-Fraction of the fat tissue. This review article aims to briefly describe the state of art of the advanced imaging techniques to provide a quantitative assessment of body composition in children and adolescents.

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“…In particular, VAT plays a key role in metabolic activity via secretion of inflammatory markers [4]. Currently, the reference standard to quantify SAT and VAT is manual annotations [3], [5], which require expert knowledge, may have inter-observer variability, is time-consuming (especially for VAT), and challenging for large-scale and longitudinal studies. Machine learning approaches have been proposed to segment SAT and VAT [6] [7] [8].…”

Section: Introductionmentioning

confidence: 99%

3D Neural Networks for Visceral and Subcutaneous Adipose Tissue Segmentation using Volumetric Multi-Contrast MRI

Kafalı

Shih

et al. 2021

2021 43rd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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Individuals with obesity have larger amounts of visceral (VAT) and subcutaneous adipose tissue (SAT) in their body, increasing the risk for cardiometabolic diseases. The reference standard to quantify SAT and VAT uses manual annotations of magnetic resonance images (MRI), which requires expert knowledge and is time-consuming. Although there have been studies investigating deep learning-based methods for automated SAT and VAT segmentation, the performance for VAT remains suboptimal (Dice scores of 0.43 to 0.89). Previous work had key limitations of not fully considering the multicontrast information from MRI and the 3D anatomical context, which are critical for addressing the complex spatially varying structure of VAT. An additional challenge is the imbalance between the number and distribution of pixels representing SAT/VAT. This work proposes a network based on 3D U-Net that utilizes the full field-of-view volumetric T1-weighted, water, and fat images from dual-echo Dixon MRI as the multi-channel input to automatically segment SAT and VAT in adults with overweight/obesity. In addition, this work extends the 3D U-Net to a new Attention-based Competitive Dense 3D U-Net (ACD 3D U-Net) trained with a class frequencybalancing Dice loss (FBDL). In an initial testing dataset, the proposed 3D U-Net and ACD 3D U-Net with FBDL achieved 3D Dice scores of (mean ± standard deviation) 0.99±0.01 and 0.99±0.01 for SAT, and 0.95±0.04 and 0.96±0.04 for VAT, respectively, compared to manual annotations. The proposed 3D networks had rapid inference time (<60 ms/slice) and can enable automated segmentation of SAT and VAT.Clinical relevance-This work developed 3D neural networks to automatically, accurately, and rapidly segment visceral and subcutaneous adipose tissue on MRI, which can help to characterize the risk for cardiometabolic diseases such as diabetes, elevated glucose levels, and hypertension.

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Free‐breathing Magnetic Resonance Imaging Assessment of Body Composition in Healthy and Overweight Children

Cited by 12 publications

References 38 publications

Visceral Obesity: Terminology, Measurement, and Its Correlation with Inflammation

Visceral Obesity: Terminology, Measurement, and Its Correlation with Inflammation

Imaging of body composition in children

3D Neural Networks for Visceral and Subcutaneous Adipose Tissue Segmentation using Volumetric Multi-Contrast MRI

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