Analysis of Various Automated Structural Computing Methods Inpatient with Early Traumatic Brain Injury
Author(s) -
Neeraj Upadhyay,
Ashok Munivenkatappa,
Bhagavatula Indira Devi,
D. K. Subbakrishna,
Jamuna Rajeswaran
Publication year - 2014
Publication title -
the open access journal of science and technology
Language(s) - English
Resource type - Journals
ISSN - 2314-5234
DOI - 10.11131/2014/101069
Subject(s) - traumatic brain injury , computer science , medical emergency , data science , medicine , psychiatry
Aim: To assess Surface Based Morphometry (SBM) and Voxel Based Morphometry (VBM), the automated computation methods to demonstrate volume and thickness changes in brain among early Traumatic Brain Injury (TBI) and their correlation with cognitive test scores. Methods: 22 mild to moderate TBI patients and 20 age, gender matched healthy individuals were recruited (mean ± SD, age range: 27.7 ± 6.5 years). MRI scans were acquired in the Siemens 3T Magnetom Skyra Scanner. TheT1-weighted magnetization preparation rapid acquisition gradient echo (MP-RAGE) sequence used for morphometric analysis provided excellent gray-white matter contrast. The structural data was processed using SBM and VBM methods with statistical significance of P<0.05 corrected for multiple comparisons. Results: both methods did not show any significant changes in brain measures after correcting for false discovery rate. However, on correlating neuropsychological score with structural changes, SBM demonstrated significant voxels survived in animal naming and Token Test after correcting for multiple comparisons. No significant change was found while using VBM. Conclusion: The study emphasizes the similarities in the results obtained after using different automatedmethods. Our findings suggest that SBM is more sensitive as compared to VBM in detecting structural changes correlated with Neuropsychological scores during early phase of TBI.
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