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Title
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CryptoCEST : a promising tool for spatially resolved identification of fungal brain lesions and their differentiation from brain tumors with MRI
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Author
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Abstract
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| Infectious brain lesions caused by the pathogenic fungi Cryptococcus neoformans and C. gattii, also referred to as cryptococcomas, could be diagnosed incorrectly as cystic brain tumors if only based on conventional magnetic resonance (MR) images. Previous MR spectroscopy (MRS) studies showed high local concentrations of the fungal disaccharide trehalose in cryptococcomas. The aim of this study was to detect and localize fungal brain lesions caused by Cryptococcus species based on Chemical Exchange Saturation Transfer (CEST) MR imaging of endogenous trehalose, and hereby to distinguish cryptococcomas from gliomas. In phantoms, trehalose and cryptococcal cells generated a concentration-dependent CEST contrast in the 0.2 - 2 ppm chemical shift range, similar to glucose, but approximately twice as strong. In vivo single voxel MRS of a murine cryptococcoma model confirmed the presence of trehalose in cryptococcomas, but mainly for lesions that were large enough compared to the size of the MRS voxel. With CEST MRI, combining the more specific CEST signal at 0.7 ppm with the higher signal-to-noise ratio signal at 4 ppm in the CryptoCEST contrast enabled localization and distinction of cryptococcomas from the normal brain and from gliomas, even for lesions smaller than 1 mm(3). Thanks to the high endogenous concentration of the fungal biomarker trehalose in cryptococcal cells, the CryptoCEST contrast allowed identification of cryptococcomas with high spatial resolution and differentiation from gliomas in mice. Furthermore, the CryptoCEST contrast was tested to follow up antifungal treatment of cryptococcomas. Translation of this non-invasive method to the clinic holds potential for improving the differential diagnosis and follow-up of cryptococcal infections in the brain. |
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Language
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English
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Source (journal)
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NeuroImage: Clinical
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Publication
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2021
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ISSN
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2213-1582
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DOI
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10.1016/J.NICL.2021.102737
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Volume/pages
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31
(2021)
, 11 p.
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Article Reference
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102737
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ISI
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000689554800003
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Pubmed ID
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34225021
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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