Graham Robart

Date of Award

2013

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

McDonald, Patrick

Keywords

Neuroimaging, Traumatic Brain Injury, DTI, MRI

Area of Concentration

Neuroscience, Computational Science

Abstract

Mild traumatic brain injury (mTBI) is a silent but costly epidemic, affecting millions of people worldwide every year. The inability for traditional medical imaging technologies to detect some types of damage that occur in mTBI has prevented the injury from receiving appropriate attention in research and clinical settings for decades. A continually growing body of research establishes diffusion tensor imaging (DTI) as an imaging modality sensitive to the subtle sequalae of diffuse axonal injury (DAI), common in mTBI. With the development of better imaging and analysis techniques for DTI, and the establishment of certain imaging biomarkers for identifying mTBI, a shift is occuring in the medical standards and practices for how we recognize and treat mTBI. Using T1-weighted MRI (sMRI) and DTI data obtained from the Mind Research Network (MRN), voxel-based analysis is performed to determine the relative merits of these data types in identifying mTBI and producing predictive biomarkers. These results demonstrate that diffusion tensor imaging (DTI) may be used to discriminate mTBI pathophysiology more effectively than standard imaging modalities such as T1-weighted magnetic resonance imaging (sMRI). A case is made for adopting DTI as part of standard clinical protocol in the diagnostic evaluations of head injury.

Rights

The author has granted New College of Florida the nonexclusive right to archive, make accessible, and distribute for educational purposes this work in whole or in part in all forms of media, now or hereafter known. The copyright of this work remains with the author.

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