Poster No:
1977
Submission Type:
Late-Breaking Abstract Submission
Authors:
Sonya Ashikyan1, Martin Monti2
Institutions:
1University of California, Los Angeles (UCLA), Burbank, CA, 2University of California Los Angeles, Los Angeles, CA
First Author:
Co-Author:
Martin Monti
University of California Los Angeles
Los Angeles, CA
Late Breaking Reviewer(s):
Naomi Gaggi, PhD
New York University Grossman School of Medicine
Rockaway Park, NY
Introduction:
Worldwide, about 42 million individuals endure a mild traumatic brain injury (mTBI) every year with over 5.3 million individuals currently living with disability that was caused by a TBI in the United States alone (Gardner & Yaffe, 2015; Pavlovic et al., 2019). The vast majority of studies tend to focus on one Magnetic Resonance Imaging (MRI) modality/type only, which is an important limitation since different MR images can capture different aspects of the brain (Narayana, 2017).
Methods:
We have designed a study which will allow us to leverage multiple types of scans and fuse them using FSL-PALM (Permutation Analysis of Linear Models) coupled with non-parametric combination (NPC) to correlate MRI scans to behavioral variables (Winkler et al., 2016). We used a total of four modalities: T1-weighted, T2-weighted echo 1, T2-weighted echo 2, and Fluid-Attenuated Inversion Recovery (FLAIR) imaging. We used pre-existing data from the Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System. Data from 90 mTBI patients was obtained across two timepoints, immediately after injury (baseline) and 3-months post-injury. Functional Data Analysis (FDA) with Clustering was performed on three behavioral variables and both sex and age were accounted for. These variables include the Posttraumatic Stress Disorder (PTSD) Checklist for Acute Stress Disorder, Center for Epidemiologic Studies-Depression Scale, and Connor-Davidson Resilience Scale. We aimed to answer two questions: (1) What is the relationship between neural damage and cognitive impairments; (2) Can the fusion of multiple types of MRI images be leveraged to predict outcomes at three-months post-injury based on behavioral data? This study will be one of the first to leverage the power of fused multimodal MRI data to assess the link between brain and mind in the context of mTBI.
Results:
The FDA clustering approach across the two timepoints on the behavioral data has revealed two distinct clusters of equally diagnosed mTBI patients; cluster group one (n=59), patients who have high resiliency levels (M=85.86,SD=12.03) and low PTSD (M=30.07, SD=7.96) and depression (M=6.50, SD=5.82) symptom ratings and cluster group two (n=31), patients who have lower resiliency levels (M=75.33, SD=17.76), and clinically high PTSD (M=50.81, SD=15.13) and depression (M=19.01, SD=10.34) ratings. A repeated measures ANOVA shows, for all three scores, a significant cluster by time interaction (F(3,285)=14.739, F(3,285)=6.822, F(3,285)=3.686). The next step of our analysis is to correlate these two cluster groups to potential structural differences using FSL-PALM across the four modalities.
Conclusions:
We aim to better understand mTBI because it is crucial for the development of effective discharge and return to active-duty guidelines for military personnel, return-to-play protocols, and sport gears (helmets) for athletes, and motor vehicle airbag advancement for the general civilian population.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Modeling and Analysis Methods:
Motion Correction and Preprocessing
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Multi-Modal Imaging 1
Keywords:
Computational Neuroscience
MRI
Neurological
Trauma
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
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Not applicable
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Not applicable
Were any animal research approved by the relevant IACUC or other animal research panel?
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Not applicable
Please indicate which methods were used in your research:
Structural MRI
Computational modeling
For human MRI, what field strength scanner do you use?
1T
Which processing packages did you use for your study?
FSL
Provide references using APA citation style.
Gardner, R. C., & Yaffe, K. (2015). Epidemiology of mild traumatic brain injury and neurodegenerative disease. Molecular and cellular neurosciences, 66(PtB), 75–80. https://doi.org/10.1016/j.mcn.2015.03.001
Pavlovic, D., Pekic, S., Stojanovic, M., & Popovic, V. (2019). Traumatic brain injury: neuropathological, neurocognitive and neurobehavioral sequelae. Pituitary, 22, 270-282.
Narayana, P. A. (2017). White matter changes in patients with mild traumatic brain injury: MRI perspective. Concussion, 2(2), CNC35.
Winkler, A. M., Webster, M. A., Brooks, J. C., Tracey, I., Smith, S. M., & Nichols, T. E. (2016). Non-parametric combination and related permutation tests for neuroimaging. Human brain mapping, 37(4), 1486-1511.
No