Automated temporalis muscle quantification and growth charts for children through adulthood.
Nat Commun
; 14(1): 6863, 2023 11 09.
Article
in En
| MEDLINE
| ID: mdl-37945573
ABSTRACT
Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Temporal Muscle
/
Growth Charts
Limits:
Child
/
Female
/
Humans
/
Male
Language:
En
Journal:
Nat Commun
Journal subject:
BIOLOGIA
/
CIENCIA
Year:
2023
Type:
Article
Affiliation country:
United States