Spatial distribution bias in subject-specific abnormalities analyses
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The neuroimaging community has seen a renewed interest in algorithms that provide a location-independent summary of subject-specific abnormalities (SSA) to assess individual lesion load. More recently, these methods have been extended to assess whether multiple individuals within the same cohort exhibit extrema in the same spatial location (e.g., voxel or region of interest). However, the statistical validity of this approach has not been rigorously established. The current study evaluated the potential for a spatial bias in the distribution of SSA using several common z-transformation algorithms (leave-one-out [LOO]; independent sample [IDS]; Enhanced Z-Score Microstructural Assessment of Pathology [EZ-MAP]; distribution-corrected z-scores [DisCo-Z]) using both simulated data and DTI data from 50 healthy controls. Results indicated that methods which z-transformed data based on statistical moments from a reference group (LOO, DisCo-Z) led to bias in the spatial location of extrema for the comparison group. In contrast, methods that z-transformed data using an independent third group (EZ-MAP, IDS) resulted in no spatial bias. Importantly, none of the methods exhibited bias when results were summed across all individual elements. The spatial bias is primarily driven by sampling error, in which differences in the mean and standard deviation of the untransformed data have a higher probability of producing extrema in the same spatial location for the comparison but not reference group. In conclusion, evaluating SSA overlap within cohorts should be either be avoided in deference to established group-wise comparisons or performed only when data is available from an independent third group.
KeywordsSimulations Single-subject Fractional anisotropy Neuroimaging Overlap
We would also like to thank Diana South and Catherine Smith for their assistance with data collection.
This work was supported by the National Institutes of Health (grant numbers 1R01MH101512-01A1 and 1R01NS098494-01A1) to A.R.M.. The funding agencies had no involvement in the study design, data collection, analyses, writing of the manuscript, or decisions related to submission for publication.
Compliance with ethical standards
Conflict of interest
Mr. Dodd reports no conflicts of interest. Mr. Ling reports no conflicts of interest. Dr. Bedrick reports no conflicts of interest. Dr. Meier reports no conflicts of interest. Dr. Mayer reports no conflicts of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Bouix, S., Pasternak, O., Rathi, Y., Pelavin, P. E., Zafonte, R., & Shenton, M. E. (2013). Increased gray matter diffusion anisotropy in patients with persistent post-concussive symptoms following mild traumatic brain injury. PLoS One, 8(6), e66205.Google Scholar
- Kim, N., Branch, C. A., Kim, M., & Lipton, M. L. (2013). Whole brain approaches for identification of microstructural abnormalities in individual patients: Comparison of techniques applied to mild traumatic brain injury. PLoS ONE, 8(3), e59382.Google Scholar
- Mayer, A. R., Dodd, A. B., Ling, J. M., Wertz, C. J., Shaff, N. A., Bedrick, E. J., et al. (2017). An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data. Brain Imaging and Behavior.Google Scholar
- Miller, D. R., Hayes, J. P., Lafleche, G., Salat, D. H., & Verfaellie, M. (2016). White matter abnormalities are associated with overall cognitive status in blast-related mTBI. Brain Imaging and Behavior.Google Scholar
- Pasternak, O., Koerte, I. K., Bouix, S., Fredman, E., Sasaki, T., Mayinger, M., et al. (2014). Hockey Concussion Education Project, Part 2. Microstructural white matter alterations in acutely concussed ice hockey players: a longitudinal free-water MRI study. Journal Neurosurgery, 120(4), 873–881.CrossRefGoogle Scholar
- Solmaz, B., Tunc, B., Parker, D., Whyte, J., Hart, T., Rabinowitz, A., et al. (2017). Assessing connectivity related injury burden in diffuse traumatic brain injury. Human Brain Mapping.Google Scholar
- Ware, J. B., Hart, T., Whyte, J., Rabinowitz, A., Detre, J. A., & Kim, J. (2017). Inter-subject variability of axonal injury in diffuse traumatic brain injury. Journal of Neurotrauma.Google Scholar