Towards label‐free non‐invasive autofluorescence multispectral imaging for melanoma diagnosis

Author:

Knab Aline12ORCID,Anwer Ayad G.12,Pedersen Bernadette34,Handley Shannon12,Marupally Abhilash Goud12,Habibalahi Abbas12,Goldys Ewa M.12

Affiliation:

1. Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales Sydney Australia

2. ARC Centre of Excellence for Nanoscale Biophotonics, University of New South Wales Sydney Australia

3. Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University Sydney New South Wales Australia

4. Melanoma Institute Australia, The University of Sydney Sydney New South Wales Australia

Abstract

AbstractThis study focuses on the use of cellular autofluorescence which visualizes the cell metabolism by monitoring endogenous fluorophores including NAD(P)H and flavins. It explores the potential of multispectral imaging of native fluorophores in melanoma diagnostics using excitation wavelengths ranging from 340 nm to 510 nm and emission wavelengths above 391 nm. Cultured immortalized cells are utilized to compare the autofluorescent signatures of two melanoma cell lines to one fibroblast cell line. Feature analysis identifies the most significant and least correlated features for differentiating the cells. The investigation successfully applies this analysis to pre‐processed, noise‐removed images and original background‐corrupted data. Furthermore, the applicability of distinguishing melanomas and healthy fibroblasts based on their autofluorescent characteristics is validated using the same evaluation technique on patient cells. Additionally, the study tentatively maps the detected features to underlying biological processes. This research demonstrates the potential of cellular autofluorescence as a promising tool for melanoma diagnostics.

Funder

University of New South Wales

Publisher

Wiley

Reference55 articles.

1. B.Sreedhar B. E.Manjunath Swamy M. S.Kumar 2020 Fourth International Conference on I‐SMAC (IoT in Social Mobile Analytics and Cloud) (I‐SMAC) 7–9 October2020 654–658.

2. E. Y.Sari I. N. B.Kiscahyadi M.Gracia A. A. S.Gunawan 2022 2nd International Conference on Information Technology and Education (ICIT&E) 22–22 January 2022 212–216.

3. Epidemiology of Melanoma

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