Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction☆

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q \u3c 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age-dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans

Investigating the neural basis of self-awareness deficits following traumatic brain injury

Self-awareness deficits are a common and disabling consequence of traumatic brain injury (TBI). ‘On-line’ awareness is one facet of self-awareness that can be studied by examining how people monitor their performance and respond to their errors. Performance monitoring, like many of the cognitive functions disrupted after TBI, is believed to depend on the coordinated activity of neural networks. The fronto-parietal control network (FPCN) is one such network that contains a sub-network called the salience network (SN). The SN consists of the dorsal anterior cingulate (dACC) and bilateral insulae cortex and is thought to monitor salient events (e.g. errors). I used advanced structure and function MRI techniques to investigate these networks and test two overarching hypotheses: first, performance monitoring is regulated by regions within the FPCN; and second, dysfunction of the FPCN leads to impaired self-awareness after TBI. My first study demonstrated two distinct frontal networks that respond to different error types. Predictable/internally signalled errors caused SN activation; whereas unpredictable/externally signalled errors caused activation of the ventral attentional network, a network thought to respond to unexpected events. This suggested the presence of parallel performance monitoring systems within the FPCN. My second study established that the ‘driving’ input into the SN originated in right anterior insula and subsequent behavioural adaptation was regulated by enhanced effective connectivity from the dACC to the left anterior insula. In my third study I identified a large group of TBI patients with impaired performance monitoring. These patients had additional metacognitive evidence of impaired self-awareness and demonstrated reduced functional connectivity between the dACC and the remainder of the FPCN at ‘rest’, and abnormally large insulae activation in response to errors. These studies clarified how the brain monitors and responds to salient events; and, provided evidence that self-awareness deficits after TBI are due to FPCN dysfunction, identifying this network as a potential target for future treatments.Open Acces

Predictors of Swallowing Outcomes in Patients with Combat-Injury Related Dysphagia

Background: Traumatic injuries, such as those from combat-related activities, can lead to complicated clinical presentations that may include dysphagia. Methods: This retrospective observational database study captured dysphagia-related information for 215 US military service members admitted to the first stateside military treatment facility after sustaining combat-related or combat-like traumatic injuries. A multidimensional relational database was developed to document the nature, course, and management for dysphagia in this unique population and to explore variables predictive of swallowing recovery using Bayesian statistical modeling and inferential statistical methods. Results: Bayesian statistical modeling revealed the importance of maxillofacial fractures and soft tissue loss as primary predictors of poor swallowing outcomes. The presence of traumatic brain injury (TBI), though common, did not further complicate dysphagia outcomes. A more detailed examination and rating of videofluoroscopic swallow studies from a subset of 161 participants supported greater impairment for participants with maxillofacial trauma and no apparent relationship between having sustained a TBI and swallow functioning. Conclusion: These analyses revealed that maxillofacial trauma is a stronger indicator than TBI of dysphagia severity and slower or incomplete recovery following combat-related injuries. Level of evidence: Therapeutic/Care Management study, level IV

Physical and Cognitive Functioning After 3 Years Can Be Predicted Using Information From the Diagnostic Process in Recently Diagnosed Multiple Sclerosis

Objective\ud To predict functioning after 3 years in patients with recently diagnosed multiple sclerosis (MS).\ud \ud Design\ud Inception cohort with 3 years of follow-up. At baseline, predictors were obtained from medical history taking, neurologic examination, and magnetic resonance imaging (MRI).\ud \ud Setting\ud Neurology outpatient clinic.\ud \ud Participants\ud Patients with MS (N=156); 146 with complete follow-up.\ud \ud Interventions\ud Not applicable.\ud \ud Main Outcome Measures\ud Inability to walk at least 500m, impaired dexterity, cognitive impairments, incontinence, inability to drive a car or use public transportation, social dysfunction, and reliance on a disability pension.\ud \ud Results\ud Clinical prediction rules were constructed for the models that were well calibrated (sufficient agreement between predicted and observed outcomes, based on visual inspection of calibration curves) and that showed sufficient discrimination (area under the receiver operation characteristic curve >.70) after internal bootstrap validation. The models for the inability to walk at least 500m, impaired dexterity, and cognitive impairments were well calibrated. Discrimination was sufficient for all 7 models, except the one predicting social dysfunction (.67). The inability to walk at least 500m was predicted by the perceived ability to walk, impairment of the cerebellar tract, and the number of MRI lesions in the spinal cord. Impaired dexterity was predicted by the perceived ability to use the hands, impairments of the pyramidal, cerebellar, and sensory tracts, and the T2-weighted infratentorial lesion load. Cognitive impairment was predicted by age, gender, the perceived ability to concentrate, and the T2-weighted supratentorial lesion load.\ud \ud Conclusions\ud Inability to walk at least 500m, impaired dexterity, and cognitive impairments can be predicted with predictors that are derived from medical history taking, neurologic examination, and MRI shortly after a definite diagnosis of MS has been made.\ud \u

Behavioral and neural correlates of chronic blast-related mild traumatic brain injury

Blast-related mild traumatic brain injury (mTBI) is a common injury among Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veterans due to the frequent use of improvised explosive devices (IEDs). A significant minority of veterans with blast-related mTBI complain of postconcussion symptoms (PCS) and cognitive difficulties, even years after the injury. Studies have suggested that these behavioral sequelae are primarily linked to mental health disorders such as posttraumatic stress disorder (PTSD). However, mTBI is associated with neural changes and the impact of these changes on behavioral sequelae is unclear. As such, this dissertation had three goals. First, this dissertation assessed whether the severity of PCS in blast-exposed individuals is associated with the extent of mTBI-related neural injury. Results revealed that individuals with mTBI with loss of consciousness (LOC) had significantly more white matter abnormalities than no-TBI controls and that these white matter abnormalities were spatially variable across individuals. Importantly, the extent of white matter abnormality was associated with physical PCS severity and mediated the relationship between mTBI with LOC and physical PCS. Second, this dissertation examined whether these white matter abnormalities were also associated with overall cognitive impairment. In light of the observed variability in white matter injury, a measure of overall cognitive status that takes into account heterogeneity of cognitive impairment was used. Results showed that the extent of white matter abnormality was associated with cognitive status and mediated the relationship between mTBI with LOC and cognitive impairment. Third, this dissertation examined performance and brain function in the context of an experimental measure of cognitive control known to be sensitive to residual effects of mTBI. Results revealed that although behavioral performance was similar across groups, the mTBI group had enhanced functional connectivity between brain networks important for task performance, suggesting a potential compensatory mechanism in mTBI. Together, the findings of this dissertation suggest that mTBI is associated with structural and functional connectivity alterations years after the injury. Further, this dissertation suggests that whereas structural connectivity changes may have negative behavioral consequences, changes in functional connectivity may serve as a compensatory mechanism for successful performance