Print Email Facebook Twitter Fast multi-component analysis using a joint sparsity constraint for MR fingerprinting Title Fast multi-component analysis using a joint sparsity constraint for MR fingerprinting Author Nagtegaal, M.A. (TU Delft ImPhys/Quantitative Imaging; Technical University of Berlin) Koken, Peter (Philips Research) Amthor, Thomas (Philips Research) Doneva, Mariya (Philips Research) Date 2020 Abstract PurposeTo develop an efficient algorithm for multi‐component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties.MethodsDifferent tissues or components within a voxel are potentially separable in MRF because of their distinct signal evolutions. The observed signal evolution in each voxel can be described as a linear combination of the signals for each component with a non‐negative weight. An assumption that only a small number of components are present in the measured field of view is usually imposed in the interpretation of multi‐component data. In this work, a joint sparsity constraint is introduced to utilize this additional prior knowledge in the multi‐component analysis of MRF data. A new algorithm combining joint sparsity and non‐negativity constraints is proposed and compared to state‐of‐the‐art multi‐component MRF approaches in simulations and brain MRF scans of 11 healthy volunteers.ResultsSimulations and in vivo measurements show reduced noise in the estimated tissue fraction maps compared to previously proposed methods. Applying the proposed algorithm to the brain data resulted in 4 or 5 components, which could be attributed to different brain structures, consistent with previous multi‐component MRF publications.ConclusionsThe proposed algorithm is faster than previously proposed methods for multi‐component MRF and the simulations suggest improved accuracy and precision of the estimated weights. The results are easier to interpret compared to voxel‐wise methods, which combined with the improved speed is an important step toward clinical evaluation of multi‐component MRF. Subject joint sparsity constraintMR fingerprintingmulti-component analysisNNLSpartial volume effectSparsity Promoting Iterative Joint NNLS (SPIJN) To reference this document use: http://resolver.tudelft.nl/uuid:694a17a9-a7d8-4c9b-a54c-9c86a2ee7319 DOI https://doi.org/10.1002/mrm.27947 ISSN 0740-3194 Source Magnetic Resonance in Medicine, 83 (2), 521-534 Part of collection Institutional Repository Document type journal article Rights © 2020 M.A. Nagtegaal, Peter Koken, Thomas Amthor, Mariya Doneva Files PDF Nagtegaal_et_al_2020_Magn ... dicine.pdf 2.09 MB Close viewer /islandora/object/uuid:694a17a9-a7d8-4c9b-a54c-9c86a2ee7319/datastream/OBJ/view