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Superpixel Raman spectroscopy for rapid skin cancer margin assessment
Author(s) -
Feng Xu,
Fox Matthew C.,
Reichenberg Jason S.,
Lopes Fabiana C.P.S.,
Sebastian Katherine R.,
Dunn Andrew K.,
Markey Mia K.,
Tunnell James W.
Publication year - 2020
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201960109
Subject(s) - raman spectroscopy , basal cell carcinoma , margin (machine learning) , pathology , materials science , biomedical engineering , computer science , medicine , basal cell , optics , physics , machine learning
Spontaneous Raman micro‐spectroscopy has been demonstrated great potential in delineating tumor margins; however, it is limited by slow acquisition speed. We describe a superpixel acquisition approach that can expedite acquisition between ~×100 and ×10 000, as compared to point‐by‐point scanning by trading off spatial resolution. We present the first demonstration of superpixel acquisition on rapid discrimination of basal cell carcinoma tumor from eight patients undergoing Mohs micrographic surgery. Results have been demonstrated high discriminant power for tumor vs normal skin based on the biochemical differences between nucleus, collagen, keratin and ceramide. We further perform raster‐scanned superpixel Raman imaging on positive and negative margin samples. Our results indicate superpixel acquisition can facilitate the use of Raman microspectroscopy as a rapid and specific tool for tumor margin assessment.