High SNR full brain relaxometry at 7T by accelerated MR-STAT

Edwin Versteeg, Hongyan Liu, Oscar van der Heide, Miha Fuderer, Cornelis A T van den Berg, Alessandro Sbrizzi

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Abstract

Purpose: To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T. Methods: To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measured (Formula presented.) -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity to (Formula presented.) inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency. Results: The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including the (Formula presented.) -mapping. After (Formula presented.) -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%–2.1% (WM-GM) for T1 and 4.3%–5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency. Conclusion: We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T.

Original languageEnglish
Pages (from-to)226-235
Number of pages10
JournalMagnetic Resonance in Medicine
Volume92
Issue number1
Early online date7 Feb 2024
DOIs
Publication statusPublished - Jul 2024

Keywords

  • magnetic resonance imaging
  • quantitative imaging

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