A Novel Visually Graded CT Biomarker of Preinjury Brain Structure to Improve Prediction of Cognitive Decline After Mild Traumatic Brain Injury
Abstract
Mild traumatic brain injury (mTBI) is a signature injury of modern warfare and affects an estimated 42 million people worldwide each year. mTBI may lead to chronic cognitive problems (in memory and thinking ability) in up to half of patients. Even more concerning is that mTBI may lead to progressive cognitive decline and eventual Alzheimer s dementia (AD) and AD-related disorders (ADRD), increasing risk by up to 3-fold. Emerging evidence suggests that a sub-set of particularly vulnerable patients may even experience progressive cognitive decline within a few months to years of TBI. While we know that, in general, patients with more education fare better and those with pre-existing conditions like depression or post-traumatic stress disorder fare worse after mTBI, there are currently no practical tools to accurately predict who will suffer from chronic or progressive cognitive consequences of mTBI and who will recover uneventfully. Most patients presenting to a trauma center with mTBI get a computed tomography (CT) scan of their head soon after injury to look for signs of trauma such as bleeding or bruising of the brain. These scans simultaneously collect a wealth of data about the underlying structure of the brain beneath and around any signs of trauma. Thus, head CT tells us not only about the injury itself, but also about the health and structure of the brain at baseline before the injury. Brain structure is a well-established predictor of cognitive function and risk of AD/ADRD in the general population. Using information about pre-injury brain structure that is routinely captured on trauma head CT may help predict whether an individual patient will make a good recovery or will suffer from chronic or progressive cognitive consequences. We hypothesize that using this routinely collected (but currently un-measured/un-used) information about pre-injury brain structure captured on head CT soon after injury will dramatically improve our ability to accurately identify those patients at highest risk for early decline in memory and thinking within 1 year of mTBI who may then be at exceptionally high risk for future AD/ADRD. To test this hypothesis, we will develop an objective scoring method based on the structure of the un-injured brain regions seen on CT right after injury, to develop and validate a novel CT biomarker of pre-injury brain structure (PBS): the PBS score. We propose a 3-year project that will cost-efficiently harness existing data from more than 1,260 adults age 16 years and older presenting to 18 trauma centers across the U.S. within 24 hours of mTBI, who participated in the US Department of Defense/NIH-funded Transforming Research And Clinical Knowledge in TBI (TRACK-TBI) study. Dr. Gardner, a dementia neurologist with advanced training in clinical research methods whose research program is focused on post-TBI AD/ADRD, is ideally positioned to lead this innovative project. Dr. Gardner has assembled an outstanding team of co-investigators and scientific advisors, including experts in dementia, TBI, CT imaging, and prognostic modeling, to further support successful completion of the following Specific Aims: Aim 1: Use state-of-the-art modeling techniques to develop and validate a practical prediction tool to identify which patients will develop early cognitive decline 1 year after mTBI using only information that is easily and routinely collected in the acute trauma setting (e.g., demographics, military and prior TBI history, clinical and CT measures of TBI severity, lab values, and pre-existing medical/psychiatric comorbidities). Aim 2: Develop and validate a novel CT biomarker of pre-injury brain structure, the PBS score, and determine whether PBS score predicts cognitive function and early cognitive decline 1 year after mTBI. Aim 3: Determine whether the PBS score improves the prediction tool developed in Aim 1 and then create a final, optimized, open-access, web-based, "clinical risk ca
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810514
Entities
People
- Raquel C Gardner
Organizations
- United States Army
- VA Northern California Health Care System