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AJNR Am J Neuroradiol. 2011 Dec;32(11):2080-6. doi: 10.3174/ajnr.A2837. Epub 2011 Nov 11.
2
Age correction in dementia--matching to a healthy brain.痴呆症的年龄校正——与健康大脑相匹配。
PLoS One. 2011;6(7):e22193. doi: 10.1371/journal.pone.0022193. Epub 2011 Jul 29.
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Microstructural brain abnormalities in patients with obsessive-compulsive disorder: diffusion-tensor MR imaging study at 3.0 T.强迫症患者的脑微观结构异常:3.0T 磁共振弥散张量成像研究。
Radiology. 2011 Jul;260(1):216-23. doi: 10.1148/radiol.11101971. Epub 2011 Apr 7.
4
Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ).基于体素的定量分析(VBQ)显示 MRI 对比参数在正常老化过程中的区域特异性变化。
Neuroimage. 2011 Apr 15;55(4):1423-34. doi: 10.1016/j.neuroimage.2011.01.052. Epub 2011 Jan 28.
5
Apolipoprotein E genotype is associated with temporal and hippocampal atrophy rates in healthy elderly adults: a tensor-based morphometry study.载脂蛋白 E 基因型与健康老年人的时间和海马萎缩率相关:一项基于张量的形态计量学研究。
J Alzheimers Dis. 2011;23(3):433-42. doi: 10.3233/JAD-2010-101398.
6
Twenty-five pitfalls in the analysis of diffusion MRI data.二十五种弥散磁共振成像数据分析中的陷阱。
NMR Biomed. 2010 Aug;23(7):803-20. doi: 10.1002/nbm.1543.
7
Voxel-based analysis of the diffusion tensor.体素基分析弥散张量。
Neuroradiology. 2010 Aug;52(8):699-710. doi: 10.1007/s00234-010-0716-3. Epub 2010 May 14.
8
Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins.基于张量的100对双胞胎弥散张量成像脑完整性遗传影响分析。
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9
Smoothing that does not blur: effects of the anisotropic approach for evaluating diffusion tensor imaging data in the clinic.平滑但不模糊:评估扩散张量成像数据的各向异性方法在临床中的应用效果。
J Magn Reson Imaging. 2010 Mar;31(3):690-7. doi: 10.1002/jmri.22040.
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Alzheimer's disease as homeostatic responses to age-related myelin breakdown.阿尔茨海默病是对与年龄相关的髓鞘破坏的体内平衡反应。
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基于体素的弥散张量图像分析方法的改进:在研究载脂蛋白 E 对脑白质完整性的影响中的应用。

Methodological improvements in voxel-based analysis of diffusion tensor images: applications to study the impact of apolipoprotein E on white matter integrity.

机构信息

Department of Physics, San Diego State University, San Diego, California, USA.

出版信息

J Magn Reson Imaging. 2014 Feb;39(2):387-97. doi: 10.1002/jmri.24157. Epub 2013 Apr 15.

DOI:10.1002/jmri.24157
PMID:23589355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3775904/
Abstract

PURPOSE

To identify regional differences in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) using customized preprocessing before voxel-based analysis (VBA) in 14 normal subjects with the specific genes that decrease (apolipoprotein [APO] E ε2) and that increase (APOE ε4) the risk of Alzheimer's disease.

MATERIALS AND METHODS

Diffusion tensor images (DTI) acquired at 1.5 Tesla were denoised with a total variation tensor regularization algorithm before affine and nonlinear registration to generate a common reference frame for the image volumes of all subjects. Anisotropic and isotropic smoothing with varying kernel sizes was applied to the aligned data before VBA to determine regional differences between cohorts segregated by allele status.

RESULTS

VBA on the denoised tensor data identified regions of reduced FA in APOE ε4 compared with the APOE ε2 healthy older carriers. The most consistent results were obtained using the denoised tensor and anisotropic smoothing before statistical testing. In contrast, isotropic smoothing identified regional differences for small filter sizes alone, emphasizing that this method introduces bias in FA values for higher kernel sizes.

CONCLUSION

Voxel-based DTI analysis can be performed on low signal to noise ratio images to detect subtle regional differences in cohorts using the proposed preprocessing techniques.

摘要

目的

在基于体素的分析(VBA)之前,使用定制的预处理方法,对 14 名具有降低(载脂蛋白 [APO] E ε2)和增加(APOE ε4)阿尔茨海默病风险的特定基因的正常受试者,识别表观扩散系数(ADC)和各向异性分数(FA)的区域差异。

材料与方法

在进行仿射和非线性配准之前,使用全变差张量正则化算法对 1.5T 获得的弥散张量图像(DTI)进行去噪,以生成所有受试者图像体积的公共参考框架。在进行 VBA 之前,对配准数据应用各向异性和各向同性平滑处理,并用不同的核大小,以确定根据等位基因状态分层的队列之间的区域差异。

结果

对去噪张量数据进行 VBA 分析,发现与 APOE ε2 健康老年携带者相比,APOE ε4 患者的 FA 值降低。在进行统计检验之前,使用去噪张量和各向异性平滑处理可获得最一致的结果。相比之下,各向同性平滑处理仅单独使用小滤波器尺寸就能识别出区域差异,这强调了这种方法在较大核尺寸时会引入 FA 值的偏差。

结论

可以对低信噪比图像进行基于体素的 DTI 分析,使用提出的预处理技术来检测队列中的细微区域差异。