Traumatic brain injury (TBI) is a major cause of death and disability in both civilian and military populations. Several publications regarding TBI including those involving imaging have hinted towards potential clinical and imaging biomarkers. However, no clear picture has emerged regarding the prognostic value of these biomarkers or imaging markers that could be used to initiate drug development and validate novel therapeutic interventions. Thanks to the efforts of NIH and the DOD, in recent years there has been a tremendous growth in TBI imaging research across the nation and worldwide. We have been fortunate to participate in TBI research since early 2000's, which has generated significant amount of clinical, behavioral and advanced MR imaging data. We and the larger TBI research community would significantly benefit if we pool our data into a single unified database such as the FITBIR information system. This would provide us access to a large amount of data that is not possible to generate at single site, and allow individual investigators to test their hypothese using novel algorithms. This may be the only way to arrive at imaging markers that have high sensitivity and specificity for a disease that can take such variable paths. Besides data from conventional MR, the imaging data that we can provide to FITBIR includes advanced imaging techniques such as diffusion tensor imaging, diffusion kurtosis imaging, MR spectroscopy, arterial spin labeling, high-resolution volumetrics, susceptibility-weighted imaging, and resting state and task based fMRI. In addition, we will also be providing longitudinal imaging data across 18 months (four total time points) on a subset of these patients. We are also interested in testing our preliminary findings from our study to determine if our results extend to larger datasets from various other institutes given their own experimental variations. The effect of an impact to the head on any given location can have varied consequences, and will depend on several factors including the acceleration forces involved, type of injury (whether mechanical or blast), and the demographics of the patient. Therefore, a clear picture can only emerge from studies with much larger sample sizes to account for the heterogeneous disease processes. A database such as FITBIR which is poised to collect data from various investigators and continue to add data from future research projects would be enormously beneficial to individual researchers interested in various aspects of TBI. As a group, we have already been trained on the use of FITBIR and are familiar with creating new common data elements and unique data elements when necessary. In addition we will benefit from FITBIR by having access to larger amounts of DTI, resting state, and volumetric data to further study the role of the thalamus and the mid-brain and to understand the involvement of different brain networks that leads to both neurodegeneration and reparation. It is hoped that we and other TBI researchers alike can benefit from this large database to identify clinical and imaging biomarkers that can lead to the development of novel therapies and can be used to monitor the effects of such therapies longitudinally.
Traumatic Brain Injury Data for FITBIR Information System Project Narrative This project will facilitate the addition of legacy data from four separate projects that will result in 800 advanced MRI datasets on nearly 400 patients along with neuropsychological assessments to be uploaded into the FITBIR system. All data will be stringently quality controlled prior to upload to the FITBIR system to ensure other researchers access high quality data. Furthermore, it is hoped that access to the data that other researchers contribute to FITBIR will allow us to validate our preliminary findings regarding the involvement of the changes in the connectivity of various brain networks, including the connectivity between thalamus/mid-brain and the cortex, in post concussive symptoms
|Sours, Chandler; Rosenberg, Joseph; Kane, Robert et al. (2015) Associations between interhemispheric functional connectivity and the Automated Neuropsychological Assessment Metrics (ANAM) in civilian mild TBI. Brain Imaging Behav 9:190-203|