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Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin
Patients with psoriasis represent a heterogeneous population with individualized disease expression. Psoriasis can be monitored through gold standard histopathology of biopsy specimens that are painful and permanently scar. A common associated measure is the use of non-invasive assessment of the Pso...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280219/ https://www.ncbi.nlm.nih.gov/pubmed/32513976 http://dx.doi.org/10.1038/s41598-020-65689-4 |
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author | Žurauskas, Mantas Barkalifa, Ronit Alex, Aneesh Marjanovic, Marina Spillman, Darold R. Mukherjee, Prabuddha Neitzel, Craig D. Lee, Warren Medler, Jeremy Arp, Zane Cleveland, Matthew Hood, Steve Boppart, Stephen A. |
author_facet | Žurauskas, Mantas Barkalifa, Ronit Alex, Aneesh Marjanovic, Marina Spillman, Darold R. Mukherjee, Prabuddha Neitzel, Craig D. Lee, Warren Medler, Jeremy Arp, Zane Cleveland, Matthew Hood, Steve Boppart, Stephen A. |
author_sort | Žurauskas, Mantas |
collection | PubMed |
description | Patients with psoriasis represent a heterogeneous population with individualized disease expression. Psoriasis can be monitored through gold standard histopathology of biopsy specimens that are painful and permanently scar. A common associated measure is the use of non-invasive assessment of the Psoriasis Area and Severity Index (PASI) or similarly derived clinical assessment based scores. However, heterogeneous manifestations of the disease lead to specific PASI scores being poorly reproducible and not easily associated with clinical severity, complicating the efforts to monitor the disease. To address this issue, we developed a methodology for non-invasive automated assessment of the severity of psoriasis using optical imaging. Our analysis shows that two-photon fluorescence lifetime imaging permits the identification of biomarkers present in both lesional and non-lesional skin that correlate with psoriasis severity. This ability to measure changes in lesional and healthy-appearing skin provides a new pathway for independent monitoring of both the localized and systemic effects of the disease. Non-invasive optical imaging was conducted on lesions and non-lesional (pseudo-control) skin of 33 subjects diagnosed with psoriasis, lesional skin of 7 subjects diagnosed with eczema, and healthy skin of 18 control subjects. Statistical feature extraction was combined with principal component analysis to analyze pairs of two-photon fluorescence lifetime images of stratum basale and stratum granulosum layers of skin. We found that psoriasis is associated with biochemical and structural changes in non-lesional skin that can be assessed using clinically available two-photon fluorescence lifetime microscopy systems. |
format | Online Article Text |
id | pubmed-7280219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72802192020-06-15 Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin Žurauskas, Mantas Barkalifa, Ronit Alex, Aneesh Marjanovic, Marina Spillman, Darold R. Mukherjee, Prabuddha Neitzel, Craig D. Lee, Warren Medler, Jeremy Arp, Zane Cleveland, Matthew Hood, Steve Boppart, Stephen A. Sci Rep Article Patients with psoriasis represent a heterogeneous population with individualized disease expression. Psoriasis can be monitored through gold standard histopathology of biopsy specimens that are painful and permanently scar. A common associated measure is the use of non-invasive assessment of the Psoriasis Area and Severity Index (PASI) or similarly derived clinical assessment based scores. However, heterogeneous manifestations of the disease lead to specific PASI scores being poorly reproducible and not easily associated with clinical severity, complicating the efforts to monitor the disease. To address this issue, we developed a methodology for non-invasive automated assessment of the severity of psoriasis using optical imaging. Our analysis shows that two-photon fluorescence lifetime imaging permits the identification of biomarkers present in both lesional and non-lesional skin that correlate with psoriasis severity. This ability to measure changes in lesional and healthy-appearing skin provides a new pathway for independent monitoring of both the localized and systemic effects of the disease. Non-invasive optical imaging was conducted on lesions and non-lesional (pseudo-control) skin of 33 subjects diagnosed with psoriasis, lesional skin of 7 subjects diagnosed with eczema, and healthy skin of 18 control subjects. Statistical feature extraction was combined with principal component analysis to analyze pairs of two-photon fluorescence lifetime images of stratum basale and stratum granulosum layers of skin. We found that psoriasis is associated with biochemical and structural changes in non-lesional skin that can be assessed using clinically available two-photon fluorescence lifetime microscopy systems. Nature Publishing Group UK 2020-06-08 /pmc/articles/PMC7280219/ /pubmed/32513976 http://dx.doi.org/10.1038/s41598-020-65689-4 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Žurauskas, Mantas Barkalifa, Ronit Alex, Aneesh Marjanovic, Marina Spillman, Darold R. Mukherjee, Prabuddha Neitzel, Craig D. Lee, Warren Medler, Jeremy Arp, Zane Cleveland, Matthew Hood, Steve Boppart, Stephen A. Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title | Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title_full | Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title_fullStr | Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title_full_unstemmed | Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title_short | Assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
title_sort | assessing the severity of psoriasis through multivariate analysis of optical images from non-lesional skin |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280219/ https://www.ncbi.nlm.nih.gov/pubmed/32513976 http://dx.doi.org/10.1038/s41598-020-65689-4 |
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