AIMC Topic: Sarcopenia
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Fully automated deep-learning section-based muscle segmentation from CT images for sarcopenia assessment.
Clinical radiology
Mar 5, 2022
AIM: To develop a fully automated deep-learning-based approach to measure muscle area for assessing sarcopenia on standard-of-care computed tomography (CT) of the abdomen without any case exclusion criteria, for opportunistic screening for frailty.
Deep learning based sarcopenia prediction from shear-wave ultrasonographic elastography and gray scale ultrasonography of rectus femoris muscle.
Scientific reports
Mar 4, 2022
We aim to evaluate the performance of a deep convolutional neural network (DCNN) in predicting the presence or absence of sarcopenia using shear-wave elastography (SWE) and gray-scale ultrasonography (GSU) of rectus femoris muscle as an imaging bioma...
Defining Normal Ranges of Skeletal Muscle Area and Skeletal Muscle Index in Children on CT Using an Automated Deep Learning Pipeline: Implications for Sarcopenia Diagnosis.
AJR. American journal of roentgenology
Mar 2, 2022
Skeletal muscle area (SMA), representing skeletal muscle cross-sectional area at the L3 vertebral level, and skeletal muscle index (SMI), representing height-normalized SMA, can serve as markers of sarcopenia. Normal SMA and SMI values have been rep...
Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma.
British journal of cancer
Nov 30, 2021
BACKGROUND: Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of tempora...
A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.
Nutrients
Nov 10, 2021
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...
Artificial-intelligence-driven discovery of prognostic biomarker for sarcopenia.
Journal of cachexia, sarcopenia and muscle
Oct 26, 2021
BACKGROUND: Sarcopenia is defined as muscle wasting, characterized by a progressive loss of muscle mass and function due to ageing. Diagnosis of sarcopenia typically involves both muscle imaging and the physical performance of people exhibiting signs...
Detection of sarcopenic obesity and prediction of long-term survival in patients with gastric cancer using preoperative computed tomography and machine learning.
Journal of surgical oncology
Sep 7, 2021
BACKGROUND: Previous studies evaluating the prognostic value of computed tomography (CT)-derived body composition data have included few patients. Thus, we assessed the prevalence and prognostic value of sarcopenic obesity in a large population of ga...
Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes.
AJR. American journal of roentgenology
Aug 18, 2021
Sarcopenia is associated with adverse clinical outcomes. CT-based skeletal muscle measurements for sarcopenia assessment are most commonly performed at the L3 vertebral level. The purpose of this article is to compare the utility of fully automated...
Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia.
Journal of healthcare engineering
Jul 29, 2021
The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the ...
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...
Positron Emission Tomography Computed Tomography
Body Composition
Radiopharmaceuticals
Fluorodeoxyglucose F18
Nutrition Assessment
Abdomen
Sarcopenia
Humans
Muscle, Skeletal
Intra-Abdominal Fat
Neural Networks, Computer
Subcutaneous Fat
Retrospective Studies
Female
Whole Body Imaging
Republic of Korea
Aged
Male
Middle Aged
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