Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain
Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain
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DOI:
10.1016/s0730-725x(97)00037-4
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发表时间:
1997-01-01
影响因子:
2.5
通讯作者:
Hall, LD
中科院分区:
文献类型:
--
作者:
Xing, D;Papadakis, NG;Hall, LD
This work studies the effect of diffusion-weighting on the precision of measurements of the apparent diffusion coefficient (ADC, or D) by diffusion-weighted magnetic resonance imaging, The precision in the value of the ADC was described in terms of a diffusion-to-noise ratio (I)NR) which was calculated as the signal-to-noise ratio in the resultant ADC, A theoretical analysis decomposed the DNR into the signal-to-noise ratio in the diffusion-weighted image and the sensitivity of diffusion-weighting, ''K-D'', The latter reflects the effect of the sampling strategy in the diffusion-weighting domain on the DNR, The theoretical analysis demonstrated that optimal two-point diffusion-weighting could be achieved in the vicinity of xi = D(b(2)-b(1)) 1.1, where xi is a nondimensional parameter of diffusion-weighting, and b(1) and b(2) are the diffusion-weighting factors for the two-point diffusion-weighting, This approach also derived an optimised signal averaging scheme, The limitations and restrictions of the two-point scheme for in vivo ADC measurement were also considered; these included a detailed discussion on partial volume effects, The theory was verified by experiments on phantoms and on the brain of a healthy volunteer using a diffusion-weighted echo-planar imaging protocol, This led to an optimal two-point diffusion-weighting for ADC measurement in human brain using b(1) = 300, and b(2) 1550 +/- 100 s/mm(2), Such a two-point scheme successfully measured values of the ADC in gray matter, white matter and cerebrospinal fluid in human brain, It thus offers an alternative to the commonly used multiple-point schemes and has the advantage of requiring significantly shorter imaging times, (C) 1997 Elsevier Science Inc.