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Poster ‐ 06: Fractal Analysis of the brain blood oxygenation level dependent (BOLD) signal of mild traumatic brain injury (mTBI) patients
Author(s) -
Lemus Olga Maria Dona,
Noseworthy Michael
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4961780
Subject(s) - traumatic brain injury , fractal analysis , blood oxygen level dependent , hurst exponent , voxel , fractal dimension , medicine , amygdala , nuclear medicine , fractal , magnetic resonance imaging , mathematics , radiology , statistics , psychiatry , mathematical analysis
Conventional imaging techniques are unable to detect abnormalities in the brain of Mild traumatic brain injury (mTBI) patients that have shown delayed response on neuropsychological evaluation. Our goal was to explore a novel analysis approach involving measurement of the temporal fractal nature of the resting state blood oxygen level depending (rsBOLD) signal. Fifteen subjects (13.4±2.3 y/o) and 56 age‐matched (13.5±2.34 y/o) healthy controls were scanned using a GE‐MR750‐3T MRI and 32‐channel RF‐coil. Axial FSPGR‐3D images were used to prescribe the rsBOLD. Motion correction was performed and the anatomical and functional images were aligned and spatially warped to a standard space. Fractal analysis, performed over the gray matter, was assessed by calculating the Hurst exponent according to Eke's procedure . Voxel‐based fractal dimension (FD) was calculated for every subject in the control group to generate the mean and standard deviation maps for the Z‐score analysis. We generated Z‐score maps for each mTBI patient and the regions where |Z|>2 were analyzed. We found that the most affected regions were the amygdala, the vermis, the caudate head, the hippocampus, and the hypothalamus, which have been previously reported as dysfunctional after mTBI. This preliminary study suggests that fractal analysis of the rsBOLD signal could possibly provide further information in mTBI. It is well known that the brain is best modeled as a complex system and therefore a measure of complexity using FD could provide an additional method to approach this global problem.