AIMC Topic: Sarcopenia
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Sarcopenia identified by computed tomography imaging using a deep learning-based segmentation approach impacts survival in patients with newly diagnosed multiple myeloma.
Cancer
Nov 22, 2022
BACKGROUND: Sarcopenia increases with age and is associated with poor survival outcomes in patients with cancer. By using a deep learning-based segmentation approach, clinical computed tomography (CT) images of the abdomen of patients with newly diag...
Robotic Esophagectomy Compared With Open Esophagectomy Reduces Sarcopenia within the First Postoperative Year: A Propensity Score-Matched Analysis.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Nov 4, 2022
INTRODUCTION: Sarcopenia is a known risk factor for adverse outcomes after esophageal cancer (EC) surgery. Robot-assisted minimally invasive esophagectomy (RAMIE) offers numerous advantages, including reduced morbidity and mortality. However, no evid...
An externally validated deep learning model for the accurate segmentation of the lumbar paravertebral muscles.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Jul 19, 2022
PURPOSE: Imaging studies about the relevance of muscles in spinal disorders, and sarcopenia in general, require the segmentation of the muscles in the images which is very labour-intensive if performed manually and poses a practical limit to the numb...
Deep learning for automatic segmentation of paraspinal muscle on computed tomography.
Acta radiologica (Stockholm, Sweden : 1987)
Mar 30, 2022
BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.
Validation of a deep learning segmentation algorithm to quantify the skeletal muscle index and sarcopenia in metastatic renal carcinoma.
European radiology
Mar 18, 2022
OBJECTIVES: To validate a deep learning (DL) algorithm for measurement of skeletal muscular index (SMI) and prediction of overall survival in oncology populations.
Editorial Comment: Pediatric Sarcopenia-Quest for Diagnosis.
AJR. American journal of roentgenology
Mar 9, 2022
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...
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