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为脑磁图源重建共享个体化模板磁共振成像数据:在保持受试者隐私的同时实现开放数据的解决方案。

Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality.

机构信息

NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Nobels väg 9, D2, Stockholm 171 77, Sweden; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.

NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Nobels väg 9, D2, Stockholm 171 77, Sweden; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherland.

出版信息

Neuroimage. 2022 Jul 1;254:119165. doi: 10.1016/j.neuroimage.2022.119165. Epub 2022 Apr 1.

Abstract

The increasing requirements for adoption of FAIR data management and sharing original research data from neuroimaging studies can be at odds with protecting the anonymity of the research participants due to the person-identifiable anatomical features in the data. We propose a solution to this dilemma for anatomical MRIs used in MEG source analysis. In MEG analysis, the channel-level data is reconstructed to the source-level using models derived from anatomical MRIs. Sharing data, therefore, requires sharing the anatomical MRI to replicate the analysis. The suggested solution is to replace the individual anatomical MRIs with individualised warped templates that can be used to carry out the MEG source analysis and that provide sufficient geometrical similarity to the original participants' MRIs. First, we demonstrate how the individualised template warping can be implemented with one of the leading open-source neuroimaging analysis toolboxes. Second, we compare results from four different MEG source reconstruction methods performed with an individualised warped template to those using the participant's original MRI. While the source reconstruction results are not numerically identical, there is a high similarity between the results for single dipole fits, dynamic imaging of coherent sources beamforming, and atlas-based virtual channel beamforming. There is a moderate similarity between minimum-norm estimates, as anticipated due to this method being anatomically constrained and dependent on the exact morphological features of the cortical sheet. We also compared the morphological features of the warped template to those of the original MRI. These showed a high similarity in grey matter volume and surface area, but a low similarity in the average cortical thickness and the mean folding index within cortical parcels. Taken together, this demonstrates that the results obtained by MEG source reconstruction can be preserved with the warped templates, whereas the anatomical and morphological fingerprint is sufficiently altered to protect the anonymity of research participants. In cases where participants consent to sharing anatomical MRI data, it remains preferable to share the original defaced data with an appropriate data use agreement. In cases where participants did not consent to share their MRIs, the individualised warped MRI template offers a good compromise in sharing data for reuse while retaining anonymity for research participants.

摘要

由于数据中的可识别个体的解剖特征,神经影像学研究原始数据的 FAIR 数据管理和共享的要求不断增加,这与保护研究参与者的匿名性相冲突。我们为用于 MEG 源分析的解剖 MRI 提出了一个解决方案。在 MEG 分析中,使用源自解剖 MRI 的模型对通道级数据进行重建到源级。因此,共享数据需要共享解剖 MRI 以复制分析。建议的解决方案是用个体变形模板替换个体解剖 MRI,这些模板可以用于进行 MEG 源分析,并与原始参与者的 MRI 具有足够的几何相似性。首先,我们展示了如何使用领先的开源神经影像学分析工具箱之一来实现个体模板变形。其次,我们比较了使用个体变形模板进行的四种不同 MEG 源重建方法的结果与使用参与者原始 MRI 的结果。虽然源重建结果在数值上并不完全相同,但单偶极子拟合、相干源动态成像波束形成和基于图谱的虚拟通道波束形成的结果之间存在高度相似性。由于该方法具有解剖学约束并且依赖于皮质层的精确形态特征,因此最小范数估计的相似性适中。我们还比较了变形模板与原始 MRI 的形态特征。这些显示了灰质体积和表面积的高度相似性,但皮质包裹的平均皮质厚度和平均折叠指数的相似性较低。总的来说,这表明可以使用变形模板保留 MEG 源重建的结果,而解剖和形态学指纹足以保护研究参与者的匿名性。在参与者同意共享解剖 MRI 数据的情况下,最好共享带有适当数据使用协议的原始蒙版图数据。在参与者不同意共享其 MRI 的情况下,个性化变形 MRI 模板提供了一个很好的折衷方案,在共享数据以供重用的同时保留研究参与者的匿名性。

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