Whole Brain Approaches for Identification of Microstructural Abnormalities in Individual Patients: Comparison of Techniques Applied to Mild Traumatic Brain Injury
Author(s) -
Namhee Kim,
Craig A. Branch,
Mimi Kim,
Michael L. Lipton
Publication year - 2013
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0059382
Subject(s) - receiver operating characteristic , traumatic brain injury , voxel , fractional anisotropy , white matter , medicine , corpus callosum , psychology , magnetic resonance imaging , pathology , radiology , psychiatry
Purpose Group-wise analyses of DTI in mTBI have demonstrated evidence of traumatic axonal injury (TAI), associated with adverse clinical outcomes. Although mTBI is likely to have a unique spatial pattern in each patient, group analyses implicitly assume that location of injury will be the same across patients. The purpose of this study was to optimize and validate a procedure for analysis of DTI images acquired in individual patients, which could detect inter-individual differences and be applied in the clinical setting, where patients must be assessed as individuals. Materials and Methods After informed consent and in compliance with HIPAA, 34 mTBI patients and 42 normal subjects underwent 3.0 Tesla DTI. Four voxelwise assessment methods (standard Z-score, “one vs. many” t-test, Family-Wise Error Rate control using pseudo t-distribution, EZ-MAP) for use in individual patients, were applied to each patient’s fractional anisotropy (FA) maps and tested for its ability to discriminate patients from controls. Receiver Operating Characteristic (ROC) analyses were used to define optimal thresholds (voxel-level significance and spatial extent) for reliable and robust detection of mTBI pathology. Results ROC analyses showed EZ-MAP (specificity 71%, sensitivity 71%), “one vs. many” t-test and standard Z-score (sensitivity 65%, specificity 76% for both methods) resulted in a significant area under the curve (AUC) score for discriminating mTBI patients from controls in terms of the total number of abnormal white matter voxels detected while the FWER test was not significant. EZ-MAP is demonstrated to be robust to assumptions of Gaussian behavior and may serve as an alternative to methods that require strict Gaussian assumptions. Conclusion EZ-MAP provides a robust approach for delineation of regional abnormal anisotropy in individual mTBI patients.
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