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A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging.
Liu, Hongyan; van der Heide, Oscar; Versteeg, Edwin; Froeling, Martijn; Fuderer, Miha; Xu, Fei; van den Berg, Cornelis A T; Sbrizzi, Alessandro.
Affiliation
  • Liu H; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van der Heide O; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Versteeg E; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Froeling M; Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Fuderer M; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Xu F; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van den Berg CAT; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Sbrizzi A; Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
NMR Biomed ; 37(2): e5050, 2024 Feb.
Article in En | MEDLINE | ID: mdl-37857335
ABSTRACT
Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Imaging, Three-Dimensional / Multiparametric Magnetic Resonance Imaging Language: En Journal: NMR Biomed Journal subject: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Year: 2024 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Imaging, Three-Dimensional / Multiparametric Magnetic Resonance Imaging Language: En Journal: NMR Biomed Journal subject: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Year: 2024 Document type: Article Affiliation country: