AIMC Topic: Intra-Abdominal Fat

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Automated and accurate quantification of subcutaneous and visceral adipose tissue from magnetic resonance imaging based on machine learning.

Magnetic resonance imaging
Accurate measuring of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) is vital for the research of many diseases. The localization and quantification of SAT and VAT by computed tomography (CT) expose patients to harmful ionizing r...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

PloS one
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...

The effect of vitamin D supplementation on insulin resistance, visceral fat and adiponectin in vitamin D deficient women with polycystic ovary syndrome: a randomized placebo-controlled trial.

Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology
INTRODUCTION: Low plasma 25-hydroxy-vitamin D (25OHD) is associated with polycystic ovary syndrome (PCOS). Vitamin D deficiency may contribute to the development of insulin resistance, visceral fat and low level of adiponectin which are common featur...

Relationship Between Serum Macrophage Migration Inhibitory Factor Level and Insulin Resistance, High-Sensitivity C-Reactive Protein and Visceral Fat Mass in Prediabetes.

The American journal of the medical sciences
BACKGROUND: Growing evidence suggest that macrophage migration inhibitory factor (MIF) plays a vital role in glucose metabolism. We aimed to ascertain whether MIF levels are altered in subjects with prediabetes and also to determine the relationship ...

A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.

Computer methods and programs in biomedicine
Accurately assessment of adipose tissue volume inside a human body plays an important role in predicting disease or cancer risk, diagnosis and prognosis. In order to overcome limitation of using only one subjectively selected CT image slice to estima...

Automated three-dimensional body composition analysis identifies visceral adipose tissue radiodensity as a predictor of mortality and recurrence in colorectal cancer.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND: Artificial intelligence enables automated three-dimensional (3D) volumetric body composition (BC) analysis from computed tomography (CT), opposed to single third lumbar vertebra (L3) slices alone. This study aimed to identify relationship...

Visceral Fat Quantified by a Fully Automated Deep-Learning Algorithm and Risk of Incident and Recurrent Diverticulitis.

Diseases of the colon and rectum
BACKGROUND: Obesity is a risk factor for diverticulitis. However, it remains unclear whether visceral fat area, a more precise measurement of abdominal fat, is associated with the risk of diverticulitis.

External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images.

The British journal of radiology
OBJECTIVES: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess la...