Spatial frequency domain imaging for the assessment of scleroderma skin involvement.


Journal

Biomedical optics express
ISSN: 2156-7085
Titre abrégé: Biomed Opt Express
Pays: United States
ID NLM: 101540630

Informations de publication

Date de publication:
01 Jun 2023
Historique:
received: 10 03 2023
revised: 11 05 2023
accepted: 11 05 2023
medline: 21 6 2023
pubmed: 21 6 2023
entrez: 21 6 2023
Statut: epublish

Résumé

Systemic sclerosis (SSc) is an autoimmune disease characterized by the widespread deposition of excess collagen in the skin and internal organs, as well as vascular dysfunction. The current standard of care technique used to quantify the extent of skin fibrosis in SSc patients is the modified Rodnan skin score (mRSS), which is an assessment of skin thickness based on clinical palpation. Despite being considered the gold standard, mRSS testing requires a trained physician and suffers from high inter-observer variability. In this study, we evaluated the use of spatial frequency domain imaging (SFDI) as a more quantitative and reliable method for assessing skin fibrosis in SSc patients. SFDI is a wide-field and non-contact imaging technique that utilizes spatially modulated light to generate a map of optical properties in biological tissue. The SFDI data were collected at six measurement sites (left and right forearms, hands, and fingers) of eight control subjects and ten SSc patients. mRSS were assessed by a physician, and skin biopsies were collected from subject's forearms and used to assess for markers of skin fibrosis. Our results indicate that SFDI is sensitive to skin changes even at an early stage, as we found a significant difference in the measured optical scattering (

Identifiants

pubmed: 37342706
doi: 10.1364/BOE.489609
pii: 489609
pmc: PMC10278615
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2955-2968

Informations de copyright

© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

Déclaration de conflit d'intérêts

A.P., A.M., K.K., A.B. and D.R. have submitted a patent disclosure related to the technology in this publication.

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Auteurs

Anahita Pilvar (A)

Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.

Aarohi M Mehendale (AM)

Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.

Kavon Karrobi (K)

Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.

Fatima El-Adili (F)

Division of Rheumatology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.
Arthritis and Autoimmune Diseases Center, Boston University, Boston, MA 02118, USA.

Andreea Bujor (A)

Division of Rheumatology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.
Arthritis and Autoimmune Diseases Center, Boston University, Boston, MA 02118, USA.

Darren Roblyer (D)

Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.

Classifications MeSH