Automated Voxel-Wise Brain DTI Analysis of Fitness and Aging

Zhexing Liu, Mahshid Farzinfar, L. Katz, Hongtu Zhu, C. Goodlett, G. Gerig, M. Styner, B. Marks
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引用次数: 9

Abstract

Diffusion Tensor Imaging (DTI) has become a widely used MR modality to investigate white matter integrity in the brain. This paper presents the application of an automated method for voxel-wise group comparisons of DTI images in a study of fitness and aging. The automated processing method consists of 3 steps: 1) preprocessing including image format converting, image quality control, eddy-current and motion artifact correction, skull stripping and tensor image estimation, 2) study-specific unbiased DTI atlas computation via diffeomorphic fluid-based and demons deformable registration and 3) voxel-wise statistical analysis via heterogeneous linear regression and a wild bootstrap technique for correcting for multiple comparisons. Our results show that this fully automated method is suitable for voxel-wise group DTI analysis. Furthermore, in older adults, the results suggest a strong link between reduced fractional anisotropy (FA) values, fitness and aging.
自动体素脑DTI分析健康和衰老
弥散张量成像(DTI)已成为一种广泛应用于脑白质完整性研究的MR方式。本文介绍了在健康和衰老研究中,DTI图像体素组比较的自动化方法的应用。自动化处理方法包括3个步骤:1)预处理,包括图像格式转换、图像质量控制、涡流和运动伪影校正、头骨去除和张量图像估计;2)通过基于微分同构流体和可变形配准的研究特定的无偏DTI图谱计算;3)通过异构线性回归和野自举技术进行体素统计分析,用于校正多个比较。我们的结果表明,这种全自动方法适用于体素级群DTI分析。此外,在老年人中,结果表明分数各向异性(FA)值降低与健康和衰老之间存在密切联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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