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Abstract #2454

A Model-Based Reconstruction Technique for Inversion Recovery Prepared Radially Acquired Data

Johannes Tran-Gia1, Dietbert Hahn1, Herbert Kstler1

1Institute of Radiology, University of Wrzburg, Wrzburg, Germany

In this work, the previously presented Model-based Acceleration of Parameter mapping (MAP) algorithm for saturation prepared radially acquired datasets is extended for Inversion Recovery (IR) prepared datasets. By incorporating an exponential signal model into the image reconstruction, the proposed IR-MAP algorithm allows quantifying the longitudinal relaxation parameter T1 from a dataset acquired after one single magnetization preparation, leading to extremely short acquisition times of about 7 seconds for one slice of the human brain. The functionality of the algorithm is demonstrated in phantom experiments as well as in-vivo.

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Keywords

acceleration acceptably according acquisition actual additionally allows amount apparent applied approximately array basic body bottom brain calibrating capable carried caused channel coil compartments concentrations consequence consistency consistent consisting contrast contrasts dataset datasets depicted derive described determine deviations drastically employing ensure especially every evolution excellence excitation experiment exponential extended fashion fast feasible fixed flash fully function functionality good graduate grant grog head human implementation in vivo inaccuracies included indicate indicated initialized inversion iteration iterations knowledge least length life limits lists long longitudinal magnetization mapping maps materials matrix measured might model modeled mono passed phantom pixel position preparation preparations prepared prior projection projections proposed quantification quantifying radial radially radiology readout reconstructed reconstruction reconstructs recovery reduced reduction repetition resolution resolve resolving samples saturation scanner school sciences sector segmented short shot side slice snapshot space spatial steady still subsequent subsequently suitable systematic table terminated tissue tracking train trajectory transforming trio underestimation utilizing validation varying whole yellow yielding