Although facial aging is a well-known phenomenon, it has not been comprehensively characterized in 3 dimensions. This study introduces a novel technique for capturing periorbital structures across age groups using 3-dimensional (3D) imaging and point cloud data collection.
Forty-six white women were divided into 3 age groups: 20–39 years, 40–59 years, and 60+ years. Patients were scanned with the Canfield 3D photogrammetry system, and data files were exported to the point cloud processing software CloudCompare. Manually selected points specifying eyelid margins, creases, and 5 key periorbital features provided the basis for a fitted model and principal component analysis (PCA). Potential statistical significance across age groups was assessed for PCA values corresponding to each subject's eyelid geometry.
Three tendencies emerged with respect to increasing age and eyelid anatomy: the width and height of the palpebral fissure decreases, with the width decreasing more rapidly; the depth of the lateral canthus relative to the medial canthus decreases; and the superior crease becomes more variable. Analyses of variance of PCA values across age groups show statistically significant differences between the youngest and oldest groups.