Each year in the United States, approximately 1.35 million people are a ected by
mTBI (aka concussion) and subsequent cognitive impairment. Approximately 33% of
mTBI cases results in persistent long-term cognitive de cits despite no abnormalities
appearing on conventional neuroimaging scans. Therefore, an accurate and reliable
imaging method is needed to determine injury location and extent of healing. The goal
of this study was to characterize and quantify mTBI through DTI, an advanced MRI
technique that encodes voxel-wise tissue water microstructural di usivity as a tensor,
as well as QSM, which measures iron deposition within tissues. We hypothesized that
personalizing the analysis of DTI and QSM will provide a better understanding of
trauma-induced microstructural damage leading to improved diagnosis and prognosis
accuracy. Through regression analysis, a preliminary comparison between DTI data
to QSM measurements was performed to determine potential correlations between
the two MRI techniques. Further, a large database of healthy pediatric brain DTI
data was downloaded and each was warped into a standardized brain template to
ultimately use for voxel-wise z-score analysis of individual mTBI patients (n=26).
This allowed localization and quantitation of abnormal regions on a per-patient basis.
Signi cant abnormalities were commonly observed in a number of regions including
the longitudinal fasciculus, fronto-occipital fasciculus, and corticospinal tract, while
unique abnormalities were localized in a host of other areas (due to the individuality
of each childs injury). Further, through group-based Bonferroni corrected T-test
analysis, the mTBI group was signi cantly di erent from controls in approximately
65% of regions analyzed. These results show that DTI is sensitive to the detection
of microstructural changes caused by mTBI and has potential to be a useful tool for
improving mTBI diagnosis accuracy / Thesis / Master of Applied Science (MASc) / Concussions affect over one million people in the United States each year. In a number
of cases, these individuals must cope with persistent long-term cognitive impairment
resulting from the injury. A current, significant problem is that concussion cannot
be reliably diagnosed using conventional CT and MR imaging methods. Therefore,
an accurate and reliable imaging method is needed to determine both injury location
and severity, as well as to monitor healing. The goal of this study was to quantify concussion through MR imaging techniques known as Di ffusion Tensor Imaging
and Quantitative Susceptibility Mapping, which accurately model the brain's mi-
crostructure. Analysis utilizing these MRI methods found signifi cant abnormalities
in a number of brain regions of concussed subjects relative to healthy individuals.
These results suggest that DTI, in particular, is sensitive to microstructural changes
caused by concussions and has the potential to be a useful tool for improving diagnosis
accuracy.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/20399 |
| Date | January 2016 |
| Creators | Stillo, David |
| Contributors | Noseworthy, Michael, Biomedical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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