Abstract #2231

R2* Estimation by Multispectral Fat-Water Models for GRE and UTE Acquisitions Using Virtual Liver Iron Overload Model and Monte Carlo Simulations

Prasiddhi Neupane¹, Utsav Shrestha¹, and Aaryani Tipirneni-Sajja^1,2

¹Biomedical Engineering, The University of Memphis, Memphis, TN, United States, ²St. Jude Children's Research Hospital, Memphis, TN, United States

Synopsis

Keywords: Data Analysis, Data AnalysisMultispectral fat-water-R2* models are used for the confounder-free assessment of hepatic iron overload. In this study, Monte Carlo-based virtual liver iron overload models were created, MRI signals were synthesized for GRE and UTE acquisitions, and the R2* values estimated using the monoexponential and the multispectral fat-water models were analyzed. Our results demonstrate that both multispectral models exhibit high accuracy and precision for UTE acquisition at both 1.5T and 3T.

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