Purpose: To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of
b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics.
Methods: We obtained 2 image datasets with 30 gradient directions, 6
b-values up to 2500 s/mm
2, and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (
MK,
K∥, and
K⊥) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets.
Results: The
MK and
K⊥ maps generated from the datasets including only the
b-value of 2500 s/mm
2 showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of
MK,
K∥, and
K⊥ maps obtained with 3
b-values (0, 1000, and 2500 s/mm
2) and 4 signal averages than maps obtained with any other combination of numbers of
b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics.
Conclusion:
MK and
K⊥ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (
b-value = 0, 1000, and 2500 s/mm
2; 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).
抄録全体を表示