Automated segmentation reveals sex-divergent age-related decline in temporalis muscle volume among Asian adults

Temporalis muscle measurements are recognized biomarkers of sarcopenia. However, manual assessments on computed tomography (CT) are time-consuming and prone to interobserver variability, and population-specific normative data for Asian populations are limited. A Multi-Scale Residual Dense Attention U-Net was developed for automated temporalis muscle segmentation from head CT images and validated using fivefold cross-validation. Age- and sex-specific normative values were derived from 320 Taiwanese adults (160 males and 160 females) spanning eight age groups from 20 to 99 years. The model achieved a Dice coefficient of 0.914 and an F1 score of 0.958. In males, peak temporalis muscle volume (TMV) was 36.9 mL at 20-29 years, followed by a 38% decline to the oldest age group. In females, peak TMV was 27.9 mL at 30-39 years, with a 60% decline across the lifespan. Females exhibited a markedly faster rate of decline than males during midlife, with rates converging after 65 years of age. Temporalis muscle area showed a strong correlation with TMV (r = 0.882, p < 0.001). This study establishes the first comprehensive age- and sex-specific normative database for TMV in Taiwanese adults. The proposed approach enables standardized muscle mass assessment from routine head CT scans.

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Journal
Scientific Reports
Published
2026-06-29
DOI
https://doi.org/10.1038/s41598-026-59470-2
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
0.00

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article

Automated segmentation reveals sex-divergent age-related decline in temporalis muscle volume among Asian adults

Cheng‐Tang Pan, Yow‐Ling Shiue, M Lee, Yao-Chung Yang
Scientific Reports
Nutrition and Health in Aging
article

Automated segmentation reveals sex-divergent age-related decline in temporalis muscle volume among Asian adults

Cheng‐Tang Pan, Yow‐Ling Shiue, M Lee, Yao-Chung Yang
article en

Abstract

Temporalis muscle measurements are recognized biomarkers of sarcopenia. However, manual assessments on computed tomography (CT) are time-consuming and prone to interobserver variability, and population-specific normative data for Asian populations are limited. A Multi-Scale Residual Dense Attention U-Net was developed for automated temporalis muscle segmentation from head CT images and validated using fivefold cross-validation. Age- and sex-specific normative values were derived from 320 Taiwanese adults (160 males and 160 females) spanning eight age groups from 20 to 99 years. The model achieved a Dice coefficient of 0.914 and an F1 score of 0.958. In males, peak temporalis muscle volume (TMV) was 36.9 mL at 20-29 years, followed by a 38% decline to the oldest age group. In females, peak TMV was 27.9 mL at 30-39 years, with a 60% decline across the lifespan. Females exhibited a markedly faster rate of decline than males during midlife, with rates converging after 65 years of age. Temporalis muscle area showed a strong correlation with TMV (r = 0.882, p < 0.001). This study establishes the first comprehensive age- and sex-specific normative database for TMV in Taiwanese adults. The proposed approach enables standardized muscle mass assessment from routine head CT scans.

Scientific Reports
National Sun Yat-sen University (TW), Advanced Semiconductor Engineering (Taiwan) (TW), Kaohsiung Veterans General Hospital (TW), National Institutes of Applied Research (TW), National Kaohsiung University of Science and Technology (TW)
Kaohsiung Veterans General Hospital
Openalex Percentile: Top 8%
Nutrition and Health in Aging
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