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Design of an algorithm for automated, computer-guided PASI measurements by digital image analysis

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The Psoriasis Area and Severity Index (PASI) is the most accepted method for psoriasis severity scoring. However, a prominent level of subjectivity and a low intra- and inter-rater reproducibility was reported. Therefore, an accurate and reproducible measure of psoriasis severity is needed, especial...

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Bibliographic Details
Main Authors: Müller-Christmann, Christine (Author) , Fuchs, Tobias (Author) , Enk, Alexander (Author) , Hänßle, Holger (Author)
Format: Article (Journal)
Language:English
Published: 03 November 2018
In: Journal of medical systems
Year: 2018, Volume: 42, Issue: 12
ISSN:1573-689X
DOI:10.1007/s10916-018-1110-7
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s10916-018-1110-7
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Author Notes:Christine Fink, Tobias Fuchs, Alexander Enk & Holger A. Haenssle

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520 |a The Psoriasis Area and Severity Index (PASI) is the most accepted method for psoriasis severity scoring. However, a prominent level of subjectivity and a low intra- and inter-rater reproducibility was reported. Therefore, an accurate and reproducible measure of psoriasis severity is needed, especially in the setting of registration studies for systemic anti-psoriatic drugs. Herein we describe a robust, user-friendly, computer-guided technology that allows for automated PASI measurements after total body imaging and digital image analysis. For this purpose, a novel image processing software for PASI calculations was developed, which was combined with a commercially available, automated image capturing system. Our data shows, that the software was able to accurately calculate the proportion of psoriatic skin surface as well as the severity of erythema, induration, and desquamation by anatomic region. In a pilot clinical validation the time-efficient technology showed a high reproducibility and high levels of agreement to results attained by PASI-trained physicians. Therefore, automated computer-guided PASI measurements hold the promise of significantly reducing the physicians’ workload while ensuring a high level of reproducibility and standardization. 
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