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Assessment of age‐ and sex‐related changes in baggy lower eyelids using a novel objective image analysis method: Orbital gray scale analysis
Author(s) -
Jo SeongJin,
Kim Hyung Su,
Park Jung Tae,
Kim Bo Ri,
Youn Sang Woong
Publication year - 2018
Publication title -
journal of cosmetic dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.626
H-Index - 44
eISSN - 1473-2165
pISSN - 1473-2130
DOI - 10.1111/jocd.12423
Subject(s) - medicine , gray (unit) , correlation , linear regression , audiology , statistics , mathematics , nuclear medicine , geometry
Summary Background Baggy lower eyelids ( BLE s) are a common aesthetic problem of aging. Valid and reliable assessment tools for BLE s are required to evaluate the current status and treatment outcome. Aims Age‐ and sex‐related changes in BLE s were assessed with the orbital gray scale ( OGS ), a novel objective image analysis method. Methods We gathered frontal‐view photographs of the faces of the patients who sought for correction of BLE s. Based on the clinical pattern, we classified the BLE s of the subjects into medial (M), medial and central ( MC ), and medial to lateral ( MCL ) types. Severity was evaluated using the OGS , a modified method of the linear gray scale analysis. Results The BLE s of 1034 subjects were classified. The most common types were MCL type in the men and MC type in the women, respectively. The M and MC types were common in the young subjects, whereas the MCL type was more common in the old subjects ( P < .001). The measurements of OGS in 104 subjects showed positive correlation with age, a higher mean value in the men, and a trend toward higher values in the order of M, MC , and MCL types ( P < .001 for central and lateral OGS scores). In a multiple linear regression analysis, central and lateral OGS values were significantly related with age, sex, and M‐C‐L classification type ( P < .001). Conclusion The M‐C‐L classification and OGS were significantly associated with both age and sex, proving that they could be potent objective assessment tools for BLE s.