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Optimization of quasi‐diffusion magnetic resonance imaging for quantitative accuracy and time‐efficient acquisition
Author(s) -
Spilling Catherine A.,
Howe Franklyn A.,
Barrick Thomas R.
Publication year - 2022
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.29420
Subject(s) - diffusion mri , fractional anisotropy , white matter , diffusion , physics , nuclear magnetic resonance , value (mathematics) , effective diffusion coefficient , magnetic resonance imaging , mathematics , statistics , medicine , thermodynamics , radiology
Purpose Quasi‐diffusion MRI (QDI) is a novel quantitative technique based on the continuous time random walk model of diffusion dynamics. QDI provides estimates of the diffusion coefficient,D 1 , 2$$ {D}_{1,2} $$ in mm 2 s −1 and a fractional exponent,α $$ \upalpha $$ , defining the non‐Gaussianity of the diffusion signal decay. Here, the b ‐value selection for rapid clinical acquisition of QDI tensor imaging (QDTI) data is optimized. Methods Clinically appropriate QDTI acquisitions were optimized in healthy volunteers with respect to a multi‐ b ‐value reference (MbR) dataset comprising 29 diffusion‐sensitized images arrayed betweenb = 0 $$ b=0 $$ and 5000 s mm −2 . The effects of varying maximum b ‐value (b max $$ {b}_{\mathrm{max}} $$ ), number of b ‐value shells, and the effects of Rician noise were investigated. Results QDTI measures showedb max $$ {b}_{\mathrm{max}} $$ dependence, most significantly forα $$ \upalpha $$ in white matter, which monotonically decreased with higherb max $$ {b}_{\mathrm{max}} $$ leading to improved tissue contrast. Optimized 2 b ‐value shell acquisitions showed small systematic differences in QDTI measures relative to MbR values, with overestimation ofD 1 , 2$$ \kern0.50em {D}_{1,2} $$ and underestimation ofα $$ \upalpha $$ in white matter, and overestimation ofD 1 , 2$$ {D}_{1,2} $$ andα $$ \upalpha $$ anisotropies in gray and white matter. Additional shells improved the accuracy, precision, and reliability of QDTI estimates with 3 and 4 shells atb max = 5000 $$ {b}_{\mathrm{max}}=5000 $$ s mm −2 , and 4 b ‐value shells atb max = 3960 $$ {b}_{\mathrm{max}}=3960 $$ s mm −2 , providing minimal bias inD 1 , 2$$ {D}_{1,2} $$ andα $$ \upalpha $$ compared to the MbR. Conclusion A highly detailed optimization of non‐Gaussian dMRI for in vivo brain imaging was performed. QDI provided robust parameterization of non‐Gaussian diffusion signal decay in clinically feasible imaging times with high reliability, accuracy, and precision of QDTI measures.