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Hyperspectral imaging microscopy for identification and quantitative analysis of fluorescently‐labeled cells in highly autofluorescent tissue
Author(s) -
Leavesley Silas J.,
Annamdevula Naga,
Boni John,
Stocker Samantha,
Grant Kristin,
Troyanovsky Boris,
Rich Thomas C.,
Alvarez Diego F.
Publication year - 2012
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.201100066
Subject(s) - autofluorescence , hyperspectral imaging , microscopy , fluorophore , fluorescence , false positive paradox , photobleaching , fluorescence microscope , fluorescence lifetime imaging microscopy , thresholding , chemistry , pathology , optics , artificial intelligence , computer science , medicine , physics , image (mathematics)
Abstract Standard fluorescence microscopy approaches rely on measurements at single excitation and emission bands to identify specific fluorophores and the setting of thresholds to quantify fluorophore intensity. This is often insufficient to reliably resolve and quantify fluorescent labels in tissues due to high autofluorescence. Here we describe the use of hyperspectral analysis techniques to resolve and quantify fluorescently labeled cells in highly autofluorescent lung tissue. This approach allowed accurate detection of green fluorescent protein (GFP) emission spectra, even when GFP intensity was as little as 15% of the autofluorescence intensity. GFP‐expressing cells were readily quantified with zero false positives detected. In contrast, when the same images were analyzed using standard (single‐band) thresholding approaches, either few GFP cells (high thresholds) or substantial false positives (intermediate and low thresholds) were detected. These results demonstrate that hyperspectral analysis approaches uniquely offer accurate and precise detection and quantification of fluorescence signals in highly autofluorescent tissues. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)