4.5 Article

Optimization of selective inversion recovery magnetization transfer imaging for macromolecular content mapping in the human brain

Journal

MAGNETIC RESONANCE IN MEDICINE
Volume 80, Issue 5, Pages 1824-1835

Publisher

WILEY
DOI: 10.1002/mrm.27174

Keywords

quantitative magnetization transfer; optimization; selective inversion recovery; myelin; cross-relaxation

Funding

  1. National MS Society
  2. [K25 EB013659]
  3. [R01 NS97821]
  4. [R01 EB017767]
  5. [R01 CA184693]
  6. [R01 EY023240]

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Purpose: To optimize a selective inversion recovery (SIR) sequence for macromolecular content mapping in the human brain at 3.0T. Theory and Methods: SIR is a quantitative method for measuring magnetization transfer (qMT) that uses a low-power, on-resonance inversion pulse. This results in a biexponential recovery of free water signal that can be sampled at various inversion/predelay times (t(I)/t(D)) to estimate a subset of qMT parameters, including the macromolecular-to-free pool-size-ratio (PSR), the R-1 of free water (R-1f), and the rate of MT exchange (k(mf)). The adoption of SIR has been limited by long acquisition times (approximate to 4 min/slice). Here, we use Cramer-Rao lower bound theory and data reduction strategies to select optimal t(I)/t(D) combinations to reduce imaging times. The schemes were experimentally validated in phantoms, and tested in healthy volunteers (N = 4) and a multiple sclerosis patient. Results: Two optimal sampling schemes were determined: (i) a 5-point scheme (k(mf) estimated) and (ii) a 4-point scheme (k(mf) assumed). In phantoms, the 5/4-point schemes yielded parameter estimates with similar SNRs as our previous 16-point scheme, but with 4.1/6.1-fold shorter scan times. Pair-wise comparisons between schemes did not detect significant differences for any scheme/parameter. In humans, parameter values were consistent with published values, and similar levels of precision were obtained from all schemes. Furthermore, fixing k(mf) reduced the sensitivity of PSR to partial-volume averaging, yielding more consistent estimates throughout the brain. Conclusions: qMT parameters can be robustly estimated in <= 1 min/slice (without independent measures of Delta B-0, B-1(+), and T-1) when optimized t(I)-t(D) combinations are selected.

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