Meeting Banner
Abstract #3623

Analysing McDESPOT Data with an Arbitrary Number of T2 Components

Jing Zhang1, Alex L. MacKay1, 2

1Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada; 2Department of Physics and Astonomy, University of British Columbia, Vancouver, British Columbia, Canada

mcDESPOT derives two-component relaxation information from spoiled and fully balanced steady-state (SPGR and bSSFP) imaging data acquired over multiple flip angles. However, the two water-pool model may be inadequate to address the complex nature of water pools in brain. We analyzed mcDESPOT data using a T2 relaxation model with an arbitrary number of components. The results show that a two pool model may be unable to describe the complex water environments found in brain. MWF values obtained from the T2 distribution of mcDESPOT were smaller and closer to values obtained from the literature.

Abstract PDF Presentation Video

Keywords

acquisition address addressing analyzed applied arbitrary arising array assumed audience axially balanced believed best body brain channel closer coil combined complex component components consider constrained containing content contents corpus correction created curve derived derives describe despot detection determining distribution distributions driven eight environments equilibrium evidence example exchange exhibit extracellular field fits fitting fraction free fully gradient head human in vivo inadequate incorporation inhomogeneities internal intra introduced journal known least lesions limit literature magnetization mapping maps measuring medical medicine minor model multicomponent nature negative nonnegative observation oriented peters physics play pool pools possibility precession pulse quadrature radiology rapid recalled reception representative resolution role scanner slice smaller speed spoiled squares steady steps suggesting systems taken target tissue transmission transverse unable unlike water whole