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Understanding scanner upgrade effects on brain integrity amp; connectivity measures

机译:了解扫描仪升级对大脑完整性和连接性措施的影响

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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.
机译:大型的多站点研究(例如阿尔茨海默氏病神经成像计划(ADNI))旨在尽可能在整个扫描站点之间协调成像协议。 ADNI-2使用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14个位置收集扩散加权图像(DWI)。在这里,我们研究了SNR,基于体素和基于ROI的扩散措施以及导出的连接矩阵和网络属性如何取决于扫描仪平台(“ HD”表示版本16.x和更低版本,DV为20.x和更高版本)。 )。我们发现扫描仪平台对基于体素的FA有几个ROI,但对SNR或网络属性没有影响。这些结果表明,即使协议在所有其他方面都得到了协调,在多站点DTI研究中考虑扫描仪平台中任何差异的重要性也很重要。

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