AIMC Topic: Intra-Abdominal Fat

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Effect of visceral fat on onset of metabolic syndrome.

Scientific reports May 30, 2025
This study analysed the effects of visceral fat on metabolic syndrome (MetS) and developed an algorithm to predict its onset using health examination data from the Iwaki Health Promotion Project in Japan. The dataset included 213 cases of MetS onset ...
Humans Male Middle Aged Metabolic Syndrome Japan Intra-Abdominal Fat Machine Learning Algorithms Female Aged Adult
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Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.

Scientific reports Apr 7, 2025
Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessi...
Intra-Abdominal Fat Subcutaneous Fat Sarcopenia Muscle, Skeletal Body Composition Psoas Muscles Humans Tomography, X-Ray Computed Female Aged Aged, 80 and over Male Middle Aged Deep Learning Image Processing, Computer-Assisted
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Measurement of adipose body composition using an artificial intelligence-based CT Protocol and its association with severe acute pancreatitis in hospitalized patients.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Mar 21, 2025
BACKGROUND/OBJECTIVES: The clinical utility of body composition in predicting the severity of acute pancreatitis (AP) remains unclear. We aimed to measure body composition using artificial intelligence (AI) to predict severe AP in hospitalized patien...
Humans Artificial Intelligence Retrospective Studies Adult Male Middle Aged Severity of Illness Index Adipose Tissue Tomography, X-Ray Computed Female Hospitalization Aged Acute Disease Body Composition Intra-Abdominal Fat Pancreatitis
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Preoperative blood and CT-image nutritional indicators in short-term outcomes and machine learning survival framework of intrahepatic cholangiocarcinoma.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Jan 30, 2025
BACKGROUND&AIMS: Intrahepatic cholangiocarcinoma (iCCA) is aggressive with limited treatment and poor prognosis. Preoperative nutritional status assessment is crucial for predicting outcomes in patients. This study aimed to compare the predictive cap...
Intra-Abdominal Fat Serum Albumin Cholangiocarcinoma Subcutaneous Fat Hepatectomy Bile Duct Neoplasms Nutritional Status Preoperative Period Female Aged Survival Rate Male Middle Aged Nutrition Assessment Postoperative Complications Neoplasm Recurrence, Local Bilirubin Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed
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Artificial intelligence-based body composition analysis using computed tomography images predicts both prevalence and incidence of diabetes mellitus.

Journal of diabetes investigation Nov 22, 2024
AIM/INTRODUCTION: We assess the efficacy of artificial intelligence (AI)-based, fully automated, volumetric body composition metrics in predicting the risk of diabetes.
Diabetes Mellitus Longitudinal Studies Follow-Up Studies Body Composition Intra-Abdominal Fat Male Middle Aged Prevalence Incidence Humans Female Artificial Intelligence Risk Factors Prognosis Aged Retrospective Studies Adult Tomography, X-Ray Computed Cross-Sectional Studies
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The development of an attention mechanism enhanced deep learning model and its application for body composition assessment with L3 CT images.

Scientific reports Nov 22, 2024
Body composition assessment is very useful for evaluating a patient's status in the clinic, but recognizing, labeling, and calculating the body compositions would be burdensome. This study aims to develop a web-based service that could automate calcu...
Humans Tomography, X-Ray Computed Female Deep Learning Aged Image Processing, Computer-Assisted Adult Body Composition Male Intra-Abdominal Fat Middle Aged Subcutaneous Fat
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Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

Scientific reports Jul 27, 2024
The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of c...
Middle Aged Support Vector Machine Obesity Decision Trees Absorptiometry, Photon Intra-Abdominal Fat Humans Machine Learning Female Aged Adult
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Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients.

Journal of medical radiation sciences May 22, 2024
INTRODUCTION: This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) regio...
Female Aged Aged, 80 and over Intra-Abdominal Fat Male Humans Adult Middle Aged Artificial Intelligence Colorectal Neoplasms Image Processing, Computer-Assisted Retrospective Studies Body Composition Tomography, X-Ray Computed
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Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment.

Scientific reports May 14, 2024
This study investigates the application of cavitation in non-invasive abdominal fat reduction and body contouring, a topic of considerable interest in the medical and aesthetic fields. We explore the potential of cavitation to alter abdominal fat com...
Male Abdominal Fat Humans Intra-Abdominal Fat Body Contouring Machine Learning Female Adult
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Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

Magma (New York, N.Y.) Feb 1, 2024
OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with o...
Imaging, Three-Dimensional Overweight Reproducibility of Results Longitudinal Studies Magnetic Resonance Imaging Humans Aged Contrast Media Obesity Neural Networks, Computer Adult Image Interpretation, Computer-Assisted Algorithms Male Abdominal Fat Female Middle Aged Intra-Abdominal Fat
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