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磁共振图像去识别处理程序及其对不同年龄段结构脑测量的影响。

De-identification procedures for magnetic resonance images and the impact on structural brain measures at different ages.

机构信息

UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, Rotterdam, Netherlands.

出版信息

Hum Brain Mapp. 2021 Aug 1;42(11):3643-3655. doi: 10.1002/hbm.25459. Epub 2021 May 11.

Abstract

Surface rendering of MRI brain scans may lead to identification of the participant through facial characteristics. In this study, we evaluate three methods that overwrite voxels containing privacy-sensitive information: Face Masking, FreeSurfer defacing, and FSL defacing. We included structural T1-weighted MRI scans of children, young adults and older adults. For the young adults, test-retest data were included with a 1-week interval. The effects of the de-identification methods were quantified using different statistics to capture random variation and systematic noise in measures obtained through the FreeSurfer processing pipeline. Face Masking and FSL defacing impacted brain voxels in some scans especially in younger participants. FreeSurfer defacing left brain tissue intact in all cases. FSL defacing and FreeSurfer defacing preserved identifiable characteristics around the eyes or mouth in some scans. For all de-identification methods regional brain measures of subcortical volume, cortical volume, cortical surface area, and cortical thickness were on average highly replicable when derived from original versus de-identified scans with average regional correlations >.90 for children, young adults, and older adults. Small systematic biases were found that incidentally resulted in significantly different brain measures after de-identification, depending on the studied subsample, de-identification method, and brain metric. In young adults, test-retest intraclass correlation coefficients (ICCs) were comparable for original scans and de-identified scans with average regional ICCs >.90 for (sub)cortical volume and cortical surface area and ICCs >.80 for cortical thickness. We conclude that apparent visual differences between de-identification methods minimally impact reliability of brain measures, although small systematic biases can occur.

摘要

MRI 脑扫描的表面渲染可能会通过面部特征识别参与者。在这项研究中,我们评估了三种覆盖包含隐私敏感信息体素的方法:面罩、FreeSurfer 模糊和 FSL 模糊。我们纳入了儿童、年轻成年人和老年人的结构 T1 加权 MRI 扫描。对于年轻成年人,还包括了间隔 1 周的测试-重测数据。使用不同的统计方法来量化去识别方法的效果,以捕捉通过 FreeSurfer 处理管道获得的测量值中的随机变化和系统噪声。面罩和 FSL 模糊在某些扫描中影响了一些脑区的体素,尤其是在年轻参与者中。FreeSurfer 模糊在所有情况下都保留了脑组织的完整。FSL 模糊和 FreeSurfer 模糊在某些扫描中保留了眼睛或嘴周围可识别的特征。对于所有去识别方法,亚皮质体积、皮质体积、皮质表面积和皮质厚度的区域脑测量值在从原始扫描和去识别扫描中获得时平均具有高度的可重复性,平均区域相关性>0.90,适用于儿童、年轻成年人和老年人。我们发现了一些小的系统偏差,这些偏差在去识别后会导致大脑测量值的显著差异,这取决于所研究的子样本、去识别方法和大脑指标。在年轻成年人中,原始扫描和去识别扫描的测试-重测内类系数(ICC)相当,平均区域 ICC>0.90 适用于(亚)皮质体积和皮质表面积,ICC>0.80 适用于皮质厚度。我们得出结论,尽管可能会出现小的系统偏差,但去识别方法之间的明显视觉差异对大脑测量值的可靠性影响最小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f58b/8249889/ef67703ebdd9/HBM-42-3643-g001.jpg

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