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

Johannes Tran-Gia¹, Dietbert Hahn¹, Herbert Kstler¹

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.