AIMC Topic: Adipose Tissue
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Muscle Fat and Volume Differences in People With Hip-Related Pain Compared With Controls: A Machine Learning Approach.
Journal of cachexia, sarcopenia and muscle
Sep 29, 2024
BACKGROUND: Hip-related pain (HRP) affects young to middle-aged active adults and impacts physical activity, finances and quality of life. HRP includes conditions like femoroacetabular impingement syndrome and labral tears. Lateral hip muscle dysfunc...
Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.
Journal of imaging informatics in medicine
Sep 19, 2024
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three ...
Accelerated chemical shift encoded cardiovascular magnetic resonance imaging with use of a resolution enhancement network.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Sep 5, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (fast chemical shift encoding [FastCSE]) to accelerate CSE.
Middle Aged
Reproducibility of Results
Case-Control Studies
Aged
Humans
Myocardium
Deep Learning
Young Adult
Prospective Studies
Adipose Tissue
Heart Diseases
Adult
Retrospective Studies
Predictive Value of Tests
Image Interpretation, Computer-Assisted
Male
Adiposity
Female
Magnetic Resonance Imaging, Cine
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.
Cardiovascular diabetology
Sep 3, 2024
BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Deep Learning
Diabetes Mellitus, Type 2
Vascular Calcification
Adipose Tissue
Predictive Value of Tests
Computed Tomography Angiography
Coronary Angiography
Pericardium
Radiographic Image Interpretation, Computer-Assisted
Epicardial Adipose Tissue
Humans
Coronary Artery Disease
Adiposity
Prognosis
Risk Factors
Automation
Female
Aged
Diabetic Angiopathies
Reproducibility of Results
Male
Middle Aged
Risk Assessment
Improving cardiovascular risk prediction with machine learning: a focus on perivascular adipose tissue characteristics.
Biomedical engineering online
Aug 5, 2024
BACKGROUND: Timely prevention of major adverse cardiovascular events (MACEs) is imperative for reducing cardiovascular diseases-related mortality. Perivascular adipose tissue (PVAT), the adipose tissue surrounding coronary arteries, has attracted inc...
Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.
Journal of cachexia, sarcopenia and muscle
Jul 15, 2024
BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of i...
Low muscle quality on a procedural computed tomography scan assessed with deep learning as a practical useful predictor of mortality in patients with severe aortic valve stenosis.
Clinical nutrition ESPEN
Jun 17, 2024
BACKGROUND & AIMS: Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in tr...
Impact of functional electrical stimulation on nerve-damaged muscles by quantifying fat infiltration using deep learning.
Scientific reports
May 28, 2024
Quantitative imaging in life sciences has evolved into a powerful approach combining advanced microscopy acquisition and automated analysis of image data. The focus of the present study is on the imaging-based evaluation of the posterior cricoaryteno...
Predicting the presence of adherent perinephric fat using MRI radiomics combined with machine learning.
International journal of medical informatics
Apr 26, 2024
OBJECTIVES: Adherent perinephric fat (APF) poses significant challenges to surgical procedures. This study aimed to evaluate the usefulness of machine learning algorithms combined with MRI-based radiomics features for predicting the presence of APF.
DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.
Atherosclerosis
Apr 18, 2024
BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging.
Magnetic Resonance Imaging, Cine
Reproducibility of Results
Epicardial Adipose Tissue
Risk Factors
Humans
Aged
Stroke Volume
Adipose Tissue
Male
Prognosis
Middle Aged
Predictive Value of Tests
Ventricular Function, Left
Risk Assessment
Retrospective Studies
Coronary Artery Disease
Deep Learning
Female
Myocardial Infarction
Magnetic Resonance Imaging
Pericardium
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