Model-Based Acceleration of Look-Locker T1 Mapping
Author(s) -
Johannes TranGia,
Tobias Wech,
Thorsten Alexander Bley,
Herbert Köstler
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0122611
Subject(s) - imaging phantom , reproducibility , computer science , acceleration , gold standard (test) , nuclear medicine , artificial intelligence , biomedical engineering , algorithm , computer vision , physics , nuclear magnetic resonance , mathematics , optics , medicine , statistics , classical mechanics
Mapping the longitudinal relaxation time T 1 has widespread applications in clinical MRI as it promises a quantitative comparison of tissue properties across subjects and scanners. Due to the long scan times of conventional methods, however, the use of quantitative MRI in clinical routine is still very limited. In this work, an acceleration of Inversion-Recovery Look-Locker (IR-LL) T 1 mapping is presented. A model-based algorithm is used to iteratively enforce an exponential relaxation model to a highly undersampled radially acquired IR-LL dataset obtained after the application of a single global inversion pulse. Using the proposed technique, a T 1 map of a single slice with 1.6mm in-plane resolution and 4mm slice thickness can be reconstructed from data acquired in only 6s. A time-consuming segmented IR experiment was used as gold standard for T 1 mapping in this work. In the subsequent validation study, the model-based reconstruction of a single-inversion IR-LL dataset exhibited a T 1 difference of less than 2.6% compared to the segmented IR-LL reference in a phantom consisting of vials with T 1 values between 200ms and 3000ms. In vivo, the T 1 difference was smaller than 5.5% in WM and GM of seven healthy volunteers. Additionally, the T 1 values are comparable to standard literature values. Despite the high acceleration, all model-based reconstructions were of a visual quality comparable to fully sampled references. Finally, the reproducibility of the T 1 mapping method was demonstrated in repeated acquisitions. In conclusion, the presented approach represents a promising way for fast and accurate T 1 mapping using radial IR-LL acquisitions without the need of any segmentation.
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