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Abstract #3042

Investigating Off-Resonance Fat Modulations in the TurboSPI Signal to Improve R2* Mapping for Quantitative Cell Tracking

Zoe O'Brien-Moran1,2, Chris V Bowen1,2, James A Rioux*1,2, and Kimberly D Brewer*1,2

1Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada, 2Physics, Dalhousie University, Halifax, NS, Canada

TurboSPI has the potential to offer quantitative cell tracking with high fidelity R2* mapping. However, early in vivo studies demonstrated that accuracy of the R2* fitting deteriorates in the presence of off-resonance fat signal. In this work, we investigate these findings further with an in vitro study. We used in silico and in vitro data to develop and test a more comprehensive decay model that accounts for fat oscillations in the TurboSPI signal. The proposed model results in improved R2* estimates in the presence of fat.

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