Journal of cosmetic dermatology · 2015
The use of facial modeling and analysis to objectively quantify facial redness.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Foolad Negar, Prakash Neha, Shi Vivian Y, Kamangar Faranak, Wang Qinlu, Li Chin-Shang, Sivamani Raja K
Аннотация
BACKGROUND: The reproducible evaluation of facial redness is critical to the assessment of erythematotelangiectatic rosacea. Assessments have typically focused on the use of photography with the use of semi-quantitative grading scales based on evaluator rating. However, few studies have utilized computer-based algorithms to evaluate facial redness.
AIM: The purpose of this clinical study was to assess whether there is correlation between clinical grading of facial redness to the assessment of a quantitative computer-based facial modeling and measurement.
MATERIAL AND METHODS: In this prospective study, a set of high-resolution facial photographs and cross-polarized subsurface photographs for erythema detection were obtained for 31 study participants. A computer algorithm was then utilized to detect and quantify facial redness in the photographs and compare this to semi-quantitative evaluator-based grading for facial redness.
RESULTS: There was a strong correlation between computer-based cross-polarized subsurface erythema quantification and clinical grading for redness intensity (Clinical Erythema Assessment), redness distribution, and overall redness severity (Modified Clinical Erythema Assessment).
CONCLUSION: Overall, facial redness measurements by facial imaging and computer analysis correlated well to clinical grading scales for both redness intensity and distribution. Future studies should incorporate facial modeling and analysis tools for assessments in clinical studies to introduce greater objectivity and quantitative analysis in facial erythema-based analyses.
AIM: The purpose of this clinical study was to assess whether there is correlation between clinical grading of facial redness to the assessment of a quantitative computer-based facial modeling and measurement.
MATERIAL AND METHODS: In this prospective study, a set of high-resolution facial photographs and cross-polarized subsurface photographs for erythema detection were obtained for 31 study participants. A computer algorithm was then utilized to detect and quantify facial redness in the photographs and compare this to semi-quantitative evaluator-based grading for facial redness.
RESULTS: There was a strong correlation between computer-based cross-polarized subsurface erythema quantification and clinical grading for redness intensity (Clinical Erythema Assessment), redness distribution, and overall redness severity (Modified Clinical Erythema Assessment).
CONCLUSION: Overall, facial redness measurements by facial imaging and computer analysis correlated well to clinical grading scales for both redness intensity and distribution. Future studies should incorporate facial modeling and analysis tools for assessments in clinical studies to introduce greater objectivity and quantitative analysis in facial erythema-based analyses.