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Fast and sensitive delineation of brain tumor with clinically compatible moxifloxacin labeling and confocal microscopy
Author(s) -
Lee Seunghun,
Park Won Yeong,
Chang Hoonchul,
Kim Bumju,
Jang Won Hyuk,
Kim Seonghan,
Shin Younghoon,
Kim Myoung Joon,
Lee Kyung Hwa,
Kim Eui Hyun,
Chung Euiheon,
Kim Ki Hean
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.201900197
Subject(s) - cytoarchitecture , brain tumor , confocal microscopy , confocal , autofluorescence , pathology , moxifloxacin , medicine , fluorescence lifetime imaging microscopy , image registration , biology , fluorescence , antibiotics , computer science , physics , geometry , mathematics , quantum mechanics , artificial intelligence , microbiology and biotechnology , image (mathematics)
Delineation of brain tumor margins during surgery is critical to maximize tumor removal while preserving normal brain tissue to obtain optimal clinical outcomes. Although various imaging methods have been developed, they have limitations to be used in clinical practice. We developed a high‐speed cellular imaging method by using clinically compatible moxifloxacin and confocal microscopy for sensitive brain tumor detection and delineation. Moxifloxacin is a Food and Drug Administration (FDA) approved antibiotic and was used as a cell labeling agent through topical administration. Its strong fluorescence at short visible excitation wavelengths allowed video‐rate cellular imaging. Moxifloxacin‐based confocal microscopy (MBCM) was characterized in normal mouse brain specimens and visualized their cytoarchitecture clearly. Then, MBCM was applied to both brain tumor murine models and two malignant human brain tumors of glioblastoma and metastatic cancer. MBCM detected tumors in all the specimens by visualizing dense and irregular cell distributions, and tumor margins were easily delineated based on the cytoarchitecture. An image analysis method was developed for automated detection and delineation. MBCM demonstrated sensitive delineation of brain tumors through cytoarchitecture visualization and would have potentials for human applications, such as a surgery‐guiding method for tumor removal.