@inproceedings{oai:repo.qst.go.jp:00054485,
 author = {Kershaw, Jeffrey and Leuze, Christoph and Obata, Takayuki and Kanno, Iwao and Aoki, Ichio and Ｋｅｒｓｈａｗ Ｊｅｆｆｒｅｙ and ロイツェ クリストフ and 小畠 隆行 and 菅野 巖 and 青木 伊知男},
 book = {Proc. Intl. Soc. Mag. Reson. Med.},
 month = {May},
 note = {It has long been hypothesised that the restricted (or hindered) motion of water molecules is responsible for the anisotropic image contrast in diffusion-tensor MRI. It has also been recognised that by varying the length or separation of the motionprobing gradients (MPGs) in a pulsed-gradient spin-echo (PGSE) sequence, it should be possible to alter the contrast of in vivo images and thus common measures of diffusion anisotropy to probe tissue microstructure. Unfortunately, previous efforts to demonstrate this were unable to find in vivo evidence for the restricted-diffusion hypothesis (eg [1]). Recent work, using a technique that employs sinusoidally oscillating MPGs added to a standard spin-echo sequence, has demonstrated some of the hallmarks of restricted diffusion for in vitro samples, and normal and diseased rat brain [2-4]. In the only previous application of the technique to diffusion tensor imaging (DTI), it was found that the fractional anisotropy (FA) of white matter in an ex vivo monkey brain was clearly dependent on MPG frequency [5]. The experimental results were in agreement with computer simulations from a restricted diffusion model and therefore the technique is expected to be a useful method for probing microstructure. However, the technique has never been applied to examine how the diffusion tensor is altered for in vivo DTI. In this study, an oscillating MPG sequence was applied to investigate changes to the apparent diffusion tensor, FA and mean diffusivity (MD) measured for in vivo rat brain as the MPG frequency is increased (or equivalently, the diffusion-time is decreased).},
 title = {Changes to the Fractional Anisotropy and Mean Diffusivity of in Vivo Rat Brain Measured at Short Effective Diffusion-Times},
 volume = {19},
 year = {2011}
}