Related Experiment Video
Updated: Jan 23, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult
Peter M Graffy1, Jiamin Liu2, Perry J Pickhardt1
11 University of Wisconsin School of Medicine and Public Health 600 Highland Avenue, Madison, WI 53705.
Objective:
To investigate a fully automated abdominal CT-based muscle tool in a large adult screening population.
Methods:
A fully automated validated muscle segmentation algorithm was applied to 9310 non-contrast CT scans, including a primary screening cohort of 8037 consecutive asymptomatic adults (mean age, 57.1±7.8 years; 3555M/4482F). Sequential follow-up scans were available in a subset of 1171 individuals (mean interval, 5.1 years). Muscle tissue cross-sectional area and attenuation (Hounsfield unit, HU) at the L3 level were assessed, including change over time.
Results:
Mean values were significantly higher in males for both muscle area (190.6±33.6 vs 133.3±24.1 cm2, p<0.001) and density (34.3±11.1 HU vs 27.3±11.7 HU, p<0.001). Age-related losses were observed, with mean muscle area reduction of -1.5 cm2/year and attenuation reduction of -1.5 HU/year. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes up to the age of 70 years. Between ages 50 and 70, relative muscle attenuation decreased significantly more in females (-30.6% vs -18.0%, p<0.001), whereas relative rates of muscle area loss were similar (-8%). Between ages 70 and 90, males lost more density (-22.4% vs -7.5%) and area (-13.4% vs -6.9%, p<0.001). Of the 1171 patients with longitudinal follow-up, 1013 (86.5%) showed a decrease in muscle attenuation, 739 (63.1%) showed a decrease in area, and 1119 (95.6%) showed a decrease in at least one of these measures.
Conclusion:
This fully automated CT muscle tool allows for both individualized and population-based assessment. Such data could be automatically derived at abdominal CT regardless of study indication, allowing for opportunistic sarcopenia detection.
Advances In Knowledge:
This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic sarcopenia assessment, regardless of the original clinical indication. Mean values were significantly higher in males for both muscle area and muscle density. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes, and therefore may be a more valuable predictor of adverse outcomes.
More Related Videos
Related Concept Videos
Longitudinal Research
Longitudinal Studies
Abdominal Aorta
The celiac trunk, a singular artery, divides into the left gastric artery, which...
Assessment of Airway, Skin Color, and Use of Accessory Muscles
Introduction
The initial evaluation of a patient's respiratory system...
Avoidance Learning and Learned Helplessness
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
Radiological Investigation I: X-ray and CT

