Literature DB >> 23508704

Disease quantification in dermatology: in vivo near-infrared spectroscopy measures correlate strongly with the clinical assessment of psoriasis severity.

Tanja Maria Greve1, Søren Kamp, Gregor B E Jemec.   

Abstract

Accurate documentation of disease severity is a prerequisite for clinical research and the practice of evidence-based medicine. The quantification of skin diseases such as psoriasis currently relies heavily on clinical scores. Although these clinical scoring methods are well established and very useful in quantifying disease severity, they require an extensive clinical experience and carry a risk of subjectivity. We explore the opportunity to use in vivo near-infrared (NIR) spectra as an objective and noninvasive method for local disease severity assessment in 31 psoriasis patients in whom selected plaques were scored clinically. A partial least squares (PLS) regression model was used to analyze and predict the severity scores on the NIR spectra of psoriatic and uninvolved skin. The correlation between predicted and clinically assigned scores was R=0.94 (RMSE=0.96), suggesting that in vivo NIR provides accurate clinical quantification of psoriatic plaques. Hence, NIR may be a practical solution to clinical severity assessment of psoriasis, providing a continuous, linear, numerical value of severity.

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Year:  2013        PMID: 23508704     DOI: 10.1117/1.JBO.18.3.037006

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  2 in total

1.  Noninvasive in vivo glucose sensing on human subjects using mid-infrared light.

Authors:  Sabbir Liakat; Kevin A Bors; Laura Xu; Callie M Woods; Jessica Doyle; Claire F Gmachl
Journal:  Biomed Opt Express       Date:  2014-06-23       Impact factor: 3.732

Review 2.  Emerging imaging technologies in dermatology: Part II: Applications and limitations.

Authors:  Samantha L Schneider; Indermeet Kohli; Iltefat H Hamzavi; M Laurin Council; Anthony M Rossi; David M Ozog
Journal:  J Am Acad Dermatol       Date:  2018-12-04       Impact factor: 11.527

  2 in total

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