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Title: QuantitativeT2: interactive quantitative T2 MRI witnessed in mouse glioblastoma
Other Titles: Advanced multi-exponential analysis of mouse glioblastoma by interactive quantitative T2 MRI
Authors: Ali, Tonima
Bjarnason, Thorarin
Senger, Donna
Dunn, Jeff F.
Joseph, Jeffery
Mitchell, Joseph
Keywords: magnetic resonance imaging;QuantitativeT2;qT2;software;glioblastoma
Issue Date: 21-Jul-2015
Publisher: Scientific Research Publishing
Citation: Ali, T., T. Bjarnason, D. Senger, J. F. Dunn, J. Joseph and R. Mitchell. (2015). QuantitativeT2: interactive quantitative T2 MRI witnessed in mouse glioblastoma. J Medical Imaging. 2(3): 036002.
Series/Report no.: Journal of Medical Imaging;
Abstract: The aim of this study was to establish an advanced analytical platform for complex in vivo pathologies. We have developed a software program, QuantitativeT2, for voxel-based real-time quantitative T2 magnetic resonance imaging. We analyzed murine brain tumors to confirm feasibility of our method for neurological conditions. Anesthetized mice (with invasive gliomas, and controls) were imaged on a 9.4 Tesla scanner using a Carr–Purcell–Meiboom–Gill sequence. The multiecho T2 decays from axial brain slices were analyzed using QuantitativeT2. T2 distribution histograms demonstrated substantial characteristic differences between normal and pathological brain tissues. Voxel-based quantitative maps of tissue water fraction (WF) and geometric mean T2 (gmT2) revealed the heterogeneous alterations to water compartmentalization caused by pathology. The numeric distribution of WF and gmT2 indicated the extent of tumor infiltration. Relative evaluations between in vivo scans and ex vivo histology indicated that the T2s between 30 and 150 ms were related to cellular density and the integrity of the extracellular matrix. Overall, QuantitativeT2 has demonstrated significant advancements in qT2 analysis with real-time operation. It is interactive with an intuitive workflow; can analyze data from many MR manufacturers; and is released as open-source code to encourage examination, improvement, and expansion of this method.
ISSN: 2164-2788
Appears in Collections:Dunn, Jeffrey F.

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