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Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry
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Study on Age-Related Facial Fat Changes Using 3D MRI and a Novel Algorithm.

Mingxia Sun, Qi Zhou, Yingtong Wu

    Aesthetic Surgery Journal. Open Forum
    |April 3, 2026
    PubMed
    Summary

    Facial and neck fat distribution changes with age, with neck fat increasing and facial fat showing varied regional changes. These age-related fat shifts impact appearance and may differ across fat compartments.

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    Area of Science:

    • Aesthetics
    • Anatomy
    • Gerontology

    Background:

    • Age-related changes in facial and cervical fat distribution significantly influence aesthetic appearance.
    • Quantitative evidence on age-related fat distribution patterns in the face and neck is limited.
    • Understanding these changes is crucial for aesthetic interventions.

    Purpose of the Study:

    • To quantitatively characterize regional fat distribution in the neck and face across different age groups.
    • To examine the relationship between age, body mass index (BMI), and fat distribution.
    • To provide a detailed understanding of age-related facial and cervical fat remodeling.

    Main Methods:

    • Cross-sectional study of 47 healthy female participants aged 18-65 years.
    • Utilized high-resolution 3D magnetic resonance imaging (MRI) for precise fat measurements.
    • Measured fat thickness and volume in predefined anatomical compartments of the face and neck.

    Main Results:

    • Neck fat thickness and volume positively correlated with age and BMI, peaking in midlife.
    • Facial fat showed region-specific changes: buccal and nasolabial fat decreased, while upper facial fat remained stable.
    • Infraorbital fat volume and thickness increased with age, particularly between young and middle-aged individuals.

    Conclusions:

    • Quantitative imaging reveals heterogeneous age-related changes in facial and cervical fat distribution.
    • Different fat compartments exhibit distinct aging rates.
    • Findings have implications for understanding facial aging and developing targeted interventions.