Olivier Jaubert1, Cristobal Arrieta2, Gastão Cruz1, Aurélien Bustin1, Torben Schneider3, Georgios Georgiopoulos1, Pier-Giorgio Masci1, Carlos Sing-Long2,4, Rene M Botnar1,5, Claudia Prieto1,5. 1. School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom. 2. Biomedical Imaging Center and Millennium Nucleus for Cardiovascular Magnetic Resonance, Pontificia Universidad Católica de Chile, Santiago, Chile. 3. Philips Healthcare, Guilford, United Kingdom. 4. Instituto de Ingeniería Matemática y Computacional and Millennium Nucleus for the Discovery of Structures in Complex Data, Pontificia Universidad Católica de Chile, Santiago, Chile. 5. Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile.
Abstract
PURPOSE: Quantitative T1 , T2 , T2 *, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1 , T2 , T2 *, and FF mapping from a single ~14 s breath-hold scan. METHODS: A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5-15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1 , T2 , T2 *, and FF simultaneously. The nine-echo time-series are reconstructed using a low-rank tensor constrained reconstruction and used to fit T2 *, B0 and to separate the water and fat signals. Water- and fat-specific T1 , T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1 /T2 phantom, a water-fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. RESULTS: The proposed water T1 , water T2 , T2 *, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1 , T2 , T2 *, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, -7.1 ms, -1.4 ms, and 0.63% when compared to conventional methods. CONCLUSION: A nine-echo liver MRF sequence allows for quantitative multi-parametric liver tissue characterization in a single breath-hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.
PURPOSE: Quantitative T1 , T2 , T2 *, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1 , T2 , T2 *, and FF mapping from a single ~14 s breath-hold scan. METHODS: A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5-15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1 , T2 , T2 *, and FF simultaneously. The nine-echo time-series are reconstructed using a low-rank tensor constrained reconstruction and used to fit T2 *, B0 and to separate the water and fat signals. Water- and fat-specific T1 , T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1 /T2 phantom, a water-fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. RESULTS: The proposed water T1 , water T2 , T2 *, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1 , T2 , T2 *, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, -7.1 ms, -1.4 ms, and 0.63% when compared to conventional methods. CONCLUSION: A nine-echo liver MRF sequence allows for quantitative multi-parametric liver tissue characterization in a single breath-hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.
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