4.7 Article

An approach to high resolution diffusion tensor imaging in fixed primate brain

期刊

NEUROIMAGE
卷 35, 期 2, 页码 553-565

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2006.12.028

关键词

-

资金

  1. NCRR NIH HHS [S10RR016811, P41RR14075] Funding Source: Medline
  2. NIBIB NIH HHS [EB00790] Funding Source: Medline
  3. NINDS NIH HHS [R01 NS041285-04, NS41285] Funding Source: Medline

向作者/读者索取更多资源

High resolution ay vivo diffusion tensor imaging (DTI) studies of neural tissues can improve our understanding of brain structure. In these studies we can modiN the tissue relaxation properties of the fixed tissues to better suite the scanner hardware. We investigated the use of Gd-DTPA contrast agent to provide the optimum signal-to-noise (SNR) ratio in 3D DTI scans of formalin fixed nonhuman primate brains at 4.7 T. Relaxivity measurements in gray and white matter allowed us to optimize the Gd concentration for soaking the brains, resulting in a 2 fold improvement in SNR for the 3D scans. FA changed little with Gd concentrations up to 10 mM although ADC was reduced at 5 and 10 miNt. Comparison of in vivo, fresh ex vivo and fixed brains showed no significant FA changes but reductions in ADC of about 50% in fresh ex vivo, and 64% and 80% in fixed gray and white matter respectively. Studies of the temperature dependence of diffusion in these tissues suggested that a 30 degrees increase in sample temperature may yield an improvement of up to 55% in SNR-efficiency for a given diffusion weighting. Our Gd soaking regimen appeared to have no detrimental effect on standard histology of the fixed brain sections. Our methods yield both high SNR and spatial resolution DTI data in fixed primate brains, allowing us to perform high resolution tractography which will facilitate the process of 'validation' of DTI fiber tracts against traditional measures of brain fiber architecture. (c) 2006 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据