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Alternating unbalanced SSFP for 3D R 2 ′ mapping of the human brain
Author(s) -
Lee Hyunyeol,
Wehrli Felix W.
Publication year - 2021
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28637
Subject(s) - steady state free precession imaging , nuclear magnetic resonance , relaxation (psychology) , pulse sequence , pulse (music) , signal (programming language) , transverse plane , contrast (vision) , physics , magnetic resonance imaging , computational physics , computer science , optics , neuroscience , medicine , radiology , biology , programming language , detector
Purpose Measuring the transverse‐relaxation rate R 2 ′ provides valuable information in quantitative evaluation of tissue microstructure, for example, in terms of oxygenation levels. Here, we propose an alternating unbalanced SSFP pulse sequence for rapid whole‐brain 3D R 2 ′ mapping. Methods Unlike currently practiced, spin echo–based R 2 ′ measurement techniques, the proposed method alternates between SSFP‐FID and SSFP‐ECHO modes for rapid 3D encoding of transverse relaxation rates expressed as R 2 + R 2 ′ and R 2 ‐R 2 ′ . Z‐shimming gradients embedded into multi‐echo trains of each SSFP module are designed to achieve relative immunity to large‐scale magnetic‐field variations (ΔB 0 ). Appropriate models for the temporal evolution of the two groups of SSFP signals were constructed with ΔB 0 ‐induced modulations accounted for, leading to ΔB 0 ‐corrected estimation of R 2 , R 2 ′ , and R 2 ∗ (= R 2 + R 2 ′ ). Additionally, relative magnetic susceptibility (Δχ) maps were obtained by quantitative susceptibility mapping of the phase data. Numerical simulations were performed to optimize scan parameters, followed by in vivo studies at 3 T in 7 healthy subjects. Measured parameters were evaluated in six brain regions, and subjected to interparameter correlation analysis. Results The resultant maps of R 2 ′ and additionally derived R 2 , R 2 ∗ , and Δχ all demonstrated the expected contrast across brain territories (eg, deep brain structures versus cortex), with the measured values in good agreement with previous reports. Furthermore, regression analyses yielded strong linear relationships for the transverse relaxation parameters ( R 2 ′ , R 2 , and R 2 ∗ ) against Δχ. Conclusion Results suggest feasibility of the proposed method as a practical and reliable means for measuring R 2 ′ , R 2 , R 2 ∗ , and Δχ across the entire brain.