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Use of Reflectance Spectrophotometry to Predict the Response of Port Wine Stains to Pulsed Dye Laser

Overview
Journal Lasers Med Sci
Publisher Springer
Date 2013 Apr 24
PMID 23609559
Citations 2
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Abstract

Reflectance spectroscopy can be used to quantitate subtle differences in color. We applied a portable reflectance spectrometer to determine its utility in the evaluation of pulsed dye laser treatment of port wine stains (PWS) and in prediction of clinical outcome, in a prospective study. Forty-eight patients with PWS underwent one to nine pulsed dye laser treatments. Patient age and skin color as well as PWS surface area, anatomic location, and color were recorded. Pretreatment spectrophotometric measurements were performed. The subjective clinical results of treatment and the quantitative spectrophotometry results were evaluated by two independent teams, and the findings were correlated. The impact of the clinical characteristics on the response to treatment was assessed as well. Patients with excellent to good clinical results of laser treatments had pretreatment spectrophotometric measurements which differed by more than 10%, whereas patients with fair to poor results had spectrophotometric measurements with a difference of of less than 10%. The correlation between the spectrophotometric results and the clinical outcome was 73% (p < 0.01). The impact of the other clinical variables on outcome agreed with the findings in the literature. Spectrophotometry has a higher correlation with clinical outcome and a better predictive value than other nonmeasurable, nonquantitative, dependent variables.

Citing Articles

Clinical outcome measures and scoring systems used in prospective studies of port wine stains: A systematic review.

van Raath M, Chohan S, Wolkerstorfer A, van der Horst C, Limpens J, Huang X PLoS One. 2020; 15(7):e0235657.

PMID: 32614899 PMC: 7332045. DOI: 10.1371/journal.pone.0235657.


Laser treatment of port-wine stains.

Brightman L, Geronemus R, Reddy K Clin Cosmet Investig Dermatol. 2015; 8:27-33.

PMID: 25624768 PMC: 4296879. DOI: 10.2147/CCID.S53118.

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