De-identification procedures for magnetic resonance images and the impact on structural brain measures at different ages.
Elizabeth E L BuimerHugo G SchnackYaron CaspiNeeltje E M van HarenMikhail MilchenkoPascal Pasnull nullHilleke E Hulshoff PolRachel M BrouwerPublished in: Human brain mapping (2021)
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.
Keyphrases
- young adults
- white matter
- resting state
- contrast enhanced
- computed tomography
- magnetic resonance
- functional connectivity
- cerebral ischemia
- bioinformatics analysis
- magnetic resonance imaging
- physical activity
- optical coherence tomography
- multiple sclerosis
- healthcare
- air pollution
- machine learning
- clinical trial
- deep learning
- study protocol
- subarachnoid hemorrhage
- diffusion weighted imaging
- brain injury
- electronic health record