AIMC Topic: Intra-Abdominal Fat

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CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

Magma (New York, N.Y.) Aug 2, 2021
BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and stroke to also impact upon the muscle to give rise to sarcopenic obesity. Phenotypic knowledge of ob...
Humans Female Reproducibility of Results Magnetic Resonance Imaging Obesity Aged Abdominal Fat Middle Aged Deep Learning Intra-Abdominal Fat Cohort Studies Subcutaneous Fat Diabetes Mellitus, Type 2
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Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.

Clinical nutrition (Edinburgh, Scotland) Jul 15, 2021
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...
Subcutaneous Fat Retrospective Studies Whole Body Imaging Republic of Korea Female Aged Male Humans Middle Aged Neural Networks, Computer Positron Emission Tomography Computed Tomography Nutrition Assessment Body Composition Abdomen Radiopharmaceuticals Sarcopenia Fluorodeoxyglucose F18 Muscle, Skeletal Intra-Abdominal Fat
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Prognostic implications of body composition change during primary treatment in patients with ovarian cancer: A retrospective study using an artificial intelligence-based volumetric technique.

Gynecologic oncology May 14, 2021
OBJECTIVE: To investigate the impact of changes in body composition during primary treatment on survival outcomes in patients with epithelial ovarian cancer (EOC).
Tomography, X-Ray Computed Female Middle Aged Deep Learning Cohort Studies Humans Prognosis Retrospective Studies Carcinoma, Ovarian Epithelial Muscle, Skeletal Intra-Abdominal Fat Ovarian Neoplasms Subcutaneous Fat Neoplasm Staging Body Composition
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Deep Learning-based Quantification of Abdominal Subcutaneous and Visceral Fat Volume on CT Images.

Academic radiology Aug 6, 2020
RATIONALE AND OBJECTIVES: Develop a deep learning-based algorithm using the U-Net architecture to measure abdominal fat on computed tomography (CT) images.
Humans Tomography, X-Ray Computed Deep Learning Abdominal Fat Intra-Abdominal Fat Subcutaneous Fat
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Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.

European journal of radiology Jul 12, 2020
PURPOSE: Aim of this study was to develop and evaluate a software toolkit, which allows for a fully automated body composition analysis in contrast enhanced abdominal computed tomography leveraging the strengths of both, quantitative information from...
Subcutaneous Fat Body Composition Linear Models Radiology Information Systems Intra-Abdominal Fat Algorithms Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Male Middle Aged Deep Learning Image Processing, Computer-Assisted Muscle, Skeletal Humans
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Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.

Clinical nutrition (Edinburgh, Scotland) Feb 14, 2020
BACKGROUND: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner avail...
Humans Neural Networks, Computer Female Reproducibility of Results Aged Male Middle Aged Magnetic Resonance Imaging Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Anthropometry Adiposity United Kingdom Linear Models Intra-Abdominal Fat
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Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.

European radiology Feb 13, 2020
INTRODUCTION: The aim of the study was to extract anthropometric measures from CT by deep learning and to evaluate their prognostic value in patients with non-small-cell lung cancer (NSCLC).
Body Surface Area Adult Intra-Abdominal Fat Survival Rate Subcutaneous Fat Humans Neoplasm Staging Whole Body Imaging Male Prognosis Deep Learning Body Composition Female Middle Aged Lung Neoplasms Progression-Free Survival Disease Progression Reproducibility of Results Carcinoma, Non-Small-Cell Lung Proportional Hazards Models Aged Muscle, Skeletal Positron Emission Tomography Computed Tomography
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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 Apr 18, 2019
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...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Cluster Analysis Intra-Abdominal Fat Subcutaneous Fat Aged, 80 and over Adult Humans Male Machine Learning Middle Aged Female Reproducibility of Results Aged
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Deep learning-based quantification of abdominal fat on magnetic resonance images.

PloS one Sep 20, 2018
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...
Mice, Knockout Body Weight Automation Organ Specificity Abdominal Fat Deep Learning Intra-Abdominal Fat Phenotype Magnetic Resonance Imaging Apolipoproteins E Female Mice, Inbred C57BL Subcutaneous Fat Animals Adipose Tissue Diet, Western Male Mice, Inbred C3H
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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 Dec 22, 2017
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...
Vitamin D Deficiency Blood Glucose Humans Intra-Abdominal Fat Insulin Dietary Supplements Female Insulin Resistance Polycystic Ovary Syndrome Young Adult Hormone Replacement Therapy Adiponectin Adult Treatment Outcome Cholecalciferol
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