Understanding scanner upgrade effects on brain integrity & connectivity measures

L. Zhan, N. Jahanshad, Yan Jin, T. Nir, Cassandra D. Leonardo, M. Bernstein, B. Borowski, C. Jack, P. Thompson
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引用次数: 6

Abstract

Large multi-site studies, such as the Alzheimer's disease Neuroimaging Initiative (ADNI) are designed to harmonize imaging protocols as far as possible across scanning sites. ADNI-2 collects diffusion-weighted images (DWI) at 14 sites, with a consistent scanner manufacturer (General Electric), magnetic field strength (3T) and consistent acquisition parameters - including voxel size and the number of gradient directions. Here we studied how the SNR, voxel-wise and ROI-based diffusion measures, and derived connectivity matrices and network properties depended on the scanner platform (with "HD" denoting version 16.x software and lower and DV being 20.x and higher). We found scanner platform effects on voxel-based FA, in several ROIs, but not on SNR or network properties. These results indicate the importance of accounting for any differences in scanner platform in multi-site DTI studies, even when the protocols are harmonized in all other respects.
了解扫描仪升级对大脑完整性和连通性的影响
大型多位点研究,如阿尔茨海默病神经成像倡议(ADNI),旨在尽可能协调跨扫描位点的成像协议。ADNI-2在14个地点收集弥散加权图像(DWI),具有一致的扫描仪制造商(通用电气),磁场强度(3T)和一致的采集参数-包括体素大小和梯度方向的数量。在这里,我们研究了信噪比、体素和基于roi的扩散度量,以及推导的连通性矩阵和网络属性如何依赖于扫描仪平台(其中“HD”表示版本16)。x软件和更低,DV为20。X或更高)。在几个roi中,我们发现扫描仪平台对基于体素的FA有影响,但对信噪比或网络属性没有影响。这些结果表明,在多站点DTI研究中,考虑扫描仪平台的任何差异的重要性,即使协议在所有其他方面都是协调一致的。
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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