A recent meta-analysis involving 1463 cases (39 different studies) of mild traumatic brain injury (TBI) indicated that cognitive dysfunction was typically present in the semi-acute phase of injury (effect size d = .54) but that no neuropsychological deficits were observable at three months post-injury. Of all cognitive deficits following mild TBI, difficulties with attention and distractibility are one of the most commonly reported, and observed, symptoms. However, the neuropathology underlying attentional dysfunction in the first few weeks of injury and the subsequent recovery process are currently understudied using newer neuroimaging techniques. The current application proposes to use neuropsychological testing and two laboratory measures (orienting and selective attention tasks) to quantify this attentional deficit, and functional magnetic resonance imaging (FMRI), diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) to quantify the underlying neuronal changes that occur as a function of time in mild TBI. Specifically, 27 mild TBI patients and 15 non-cranial trauma controls will undergo neuropsychological testing and an extensive imaging battery 3 weeks and 3-5 months post injury. During the FMRI session, participants will be asked to perform a spatial orienting task and a task that requires them to process conflicting information from two sensory modalities (Numeric Stroop). To date, the vast majority of TBI neuroimaging studies have employed only a single imaging modality (MRS or FMRI or DTI), have selected patients without controlling for time post-injury or severity of injury, and have not studied patients longitudinally. Thus, the impact and innovation of the current proposal therefore lies on several levels. Foremost, it addresses an important gap in our current knowledge regarding the development of standardized protocols that are capable of capturing the dynamic neurological changes that occur after a mild TBI. Routine clinical imaging modalities (MRI and CT scans) are usually insensitive to both the neuronal pathology underlying acute cognitive deficits as well as to the subsequent recovery process that occurs in the majority (80-90%) of patients. Second, each of the selected imaging modalities contains different information about the functioning of different classes of neuronal tissues (i.e., FMRI = indirect measure of gray matter functioning and vasculature;DTI = measure of white matter integrity;MRS = direct measure of neuronal and axonal health). The combination of information from these three different imaging techniques is likely to be synergistic and exceed the sum of each individual modality alone. We will directly test this hypothesis by applying novel multivariate statistical techniques (joint independent component analyses;J-ICA) to the acquired imaging data. Finally, a longitudinal study of mild TBI during both the semi-acute and chronic phase using these neuroimaging modalities will provide the foundation for a human recovery model in TBI. While it is unlikely that neuroimaging techniques alone will ever be able to provide an independent objective diagnosis, it is likely that they will provide incremental information that will be important for both differential diagnosis and predictions about future outcome. Importantly, the realization of the above will be critical for eventually identifying the minority of mild TBI patients at risk for developing future complications so that intervention can occur acutely, when there is a better chance of success.

Public Health Relevance

In the United States alone, there are approximately 1.2 million mild traumatic brain injury (TBI) cases per year that result in an estimated cost of $56 billion dollars. The symptoms of mild TBI can range from severe physical and mental disability to subtle problems with attention, concentration, or emotional control. Cognitive difficulties are often present in the first few weeks of injury, but typically remit 3-5 months post injury in the majority (approximately 80-90%) of patients. The first step for understanding these cognitive difficulties is to develop biomarkers that are sensitive to neuronal injury and the subsequent recovery process. This will be critical not only for mild TBI, but also for more severe forms of TBI as well. However, the identification of the pathology underlying cognitive deficits in the acute or chronic phases of mild TBI is often subtle, and hard to detect with conventional imaging techniques such as CT or MRI. This suggests that the diagnostic utility and predictive validity of more research-based neuroimaging techniques, such as functional magnetic resonance imaging (FMRI), diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) needs to be explored. The use of multiple neuroimaging techniques is crucial because different modalities measure different signals (e.g., hemodynamic, metabolic or electrophysiological) that originate from different tissue sources in the brain (e.g., white versus gray matter), which will be important for identifying the diffuse injuries that may occur following head trauma. It is likely that the underlying acute pathology is multifaceted and involves both white and gray matter, suggesting that sampling several different domains of neuronal integrity is a necessary first step to understanding the acute cognitive deficits as well as the subsequent normal recovery process. Moreover, these bio- markers may be useful for distinguishing the small percentage of mild TBI patients who continue to have cognitive problems due to the injury.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21NS064464-02
Application #
7767672
Study Section
Brain Injury and Neurovascular Pathologies Study Section (BINP)
Program Officer
Hicks, Ramona R
Project Start
2009-03-01
Project End
2012-07-31
Budget Start
2010-03-01
Budget End
2012-07-31
Support Year
2
Fiscal Year
2010
Total Cost
$196,027
Indirect Cost
Name
The Mind Research Network
Department
Type
DUNS #
098640696
City
Albuquerque
State
NM
Country
United States
Zip Code
87106
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