Faisal Rashid

Diverging white matter trajectories in children after traumatic brain injury: The RAPBI study

Objective: To examine longitudinal trajectories of white matter organization in pediatric moderate/severe traumatic brain injury (msTBI) over a 12-month period. Methods: We studied 21 children (16 M/5 F) with msTBI, assessed 2–5 months postinjury and again 13–19 months postinjury, as well as 20 well-matched healthy control children. We assessed corpus callosum function through interhemispheric transfer time (IHTT), measured using event-related potentials, and related this to diffusion-weighted MRI measures of white matter (WM) microstructure. At the first time point, half of the patients with TBI had significantly slower IHTT (TBI-slow-IHTT, n = 11) and half were in the normal range (TBI-normal-IHTT, n = 10). Results: The TBI-normal-IHTT group did not differ significantly from healthy controls, either in WM organization in the chronic phase or in the longitudinal trajectory of WM organization between the 2 evaluations. In contrast, the WM organization of the TBI-slow-IHTT group was significantly lower than in healthy controls across a large portion of the WM. Longitudinal analyses showed that the TBI-slow-IHTT group experienced a progressive decline between the 2 evaluations in WM organization throughout the brain. Conclusions: We present preliminary evidence suggesting a potential biomarker that identifies a subset of patients with impaired callosal organization in the first months postinjury who subsequently experience widespread continuing and progressive degeneration in the first year postinjury.

Diverging volumetric trajectories following pediatric traumatic brain injury

Traumatic brain injury (TBI) is a significant public health concern, and can be especially disruptive in children, derailing on-going neuronal maturation in periods critical for cognitive development. There is considerable heterogeneity in post-injury outcomes, only partially explained by injury severity. Understanding the time course of recovery, and what factors may delay or promote recovery, will aid clinicians in decision-making and provide avenues for future mechanism-based therapeutics. We examined regional changes in brain volume in a pediatric/adolescent moderate-severe TBI (msTBI) cohort, assessed at two time points. Children were first assessed 2–5 months post-injury, and again 12 months later. We used tensor-based morphometry (TBM) to localize longitudinal volume expansion and reduction. We studied 21 msTBI patients (5 F, 8–18 years old) and 26 well-matched healthy control children, also assessed twice over the same interval. In a prior paper, we identified a subgroup of msTBI patients, based on interhemispheric transfer time (IHTT), with significant structural disruption of the white matter (WM) at 2–5 months post injury. We investigated how this subgroup (TBI-slow, N = 11) differed in longitudinal regional volume changes from msTBI patients (TBI-normal, N = 10) with normal WM structure and function. The TBI-slow group had longitudinal decreases in brain volume in several WM clusters, including the corpus callosum and hypothalamus, while the TBI-normal group showed increased volume in WM areas. Our results show prolonged atrophy of the WM over the first 18 months post-injury in the TBI-slow group. The TBI-normal group shows a different pattern that could indicate a return to a healthy trajectory.

A network approach to examining injury severity in pediatric TBI

Traumatic brain injury (TBI) is the leading cause of death and disability in children, and can lead to long lasting functional impairment. Many factors influence outcome, but imaging studies examining effects of individual variables are limited by sample size. Roughly 20–40% of hospitalized TBI patients experience seizures, but not all of these patients go on to develop a recurrent seizure disorder. Here we examined differences in structural network connectivity in pediatric patients who had sustained a moderate-severe TBI (msTBI). We compared those who experienced early post-traumatic seizures to those who did not; we found network differences months after seizure activity stopped. We also examined correlations between network measures and a common measure of injury severity, the Glasgow Coma Scale (GCS). The global GCS score did not have a detectable relationship to brain integrity, but sub-scores of the GCS (eyes, motor, verbal) were more closely related to imaging measures.

FiberNET: An Ensemble Deep Learning Framework for Clustering White Matter Fibers

White matter tracts are commonly analyzed in studies of micro-structural integrity and anatomical connectivity in the brain. Over the last decade, it has been an open problem as to how best to cluster white matter fibers, extracted from whole-brain tractography, into anatomically meaningful groups. Some existing techniques use region of interest (ROI) based clustering, atlas-based labeling, or unsupervised spectral clustering. ROI-based clustering is popular for analyzing anatomical connectivity among a set of ROIs, but it does not always partition the brain into recognizable fiber bundles. Here we propose an approach using convolutional neural networks (CNNs) to learn shape features of the fiber bundles, which are then exploited to cluster white matter fibers. To achieve such clustering, we first need to re-parameterize the fibers in an intrinsic space. The clustering is performed in induced parameterized coordinates. To our knowledge, this is one of the first approaches for fiber clustering using deep learning techniques. The results show strong accuracy - on a par with or better than other state-of-the-art methods.

Magnetic resonance spectroscopy of fiber tracts in children with traumatic brain injury: A combined MRS - Diffusion MRI study

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on‐going post‐injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI‐normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI‐slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate‐severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N‐acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi‐modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post‐injury in a subgroup of msTBI children and indicate the utility of multi‐modal imaging.

White Matter Alterations In Parkinson's Disease Mapped Using Tractometry

Neurodegenerative disorders are characterized by a progressive loss of brain function. Improved precision in mapping the altered brain pathways can provide a deep understanding of the trajectory of decline. We propose a tractometry workflow for conducting group statistical analyses of point-wise microstructural measures along white matter fasciculi to identify patterns of abnormalities associated with disease. We combined state-of-the-art tools including fiber registration, tract simplification and fiber matching for accurate point-wise statistical analyses across populations. We test the utility of this method by identifying group differences between Parkinson’s disease (PD) patients and healthy controls. We find statistically significant group differences in diffusion MRI derived measures along the anterior thalamic radiations (ATR), corticospinal tract (CST) and regions of the corpus callosum (CC). These pathways are essential for motor control systems within cortico-cortical and cortico-subcortical brain networks. Moreover, the reported pathological changes were not widespread but rather localized along several tracts. Point-wise tract analyses may therefore offer an advantage in anatomical specificity over traditional methods that assess mean microstructural measures across large regions of interest.

Examination of corticothalamic fiber projections in United States service members with mild traumatic brain injury

Mild traumatic brain injury (mTBI) is characterized clinically by a closed head injury involving differential or rotational movement of the brain inside the skull. Over 3 million mTBIs occur annually in the United States alone. Many of the individuals who sustain an mTBI go on to recover fully, but around 20% experience persistent symptoms. These symptoms often last for many weeks to several months. The thalamus, a structure known to serve as a global networking or relay system for the rest of the brain, may play a critical role in neurorehabiliation and its integrity and connectivity after injury may also affect cognitive outcomes. To examine the thalamus, conventional tractography methods to map corticothalamic pathways with diffusion-weighted MRI (DWI) lead to sparse reconstructions that may contain false positive fibers that are anatomically inaccurate. Using a specialized method to zero in on corticothalamic pathways with greater robustness, we noninvasively examined corticothalamic fiber projections using DWI, in 68 service members. We found significantly lower fractional anisotropy (FA), a measure of white matter microstructural integrity, in pathways projecting to the left pre- and postcentral gyri – consistent with sensorimotor deficits often found post-mTBI. Mapping of neural circuitry in mTBI may help to further our understanding of mechanisms underlying recovery post-TBI.

Brain cortical structural differences between non-central nervous system cancer patients treated with and without chemotherapy compared to non-cancer controls: A cross-sectional pilot MRI study using clinically indicated scans

Background: Increases in cancer survival have made understanding the basis of cancer-related cognitive impairment (CRCI) more important. CRCI neuroimaging studies have traditionally used dedicated research brain MRIs in breast cancer survivors with small sample sizes; little is known about other non-CNS cancers. However, there is a wealth of unused data from clinically-indicated MRIs that could be used to study CRCI. Objective: Evaluate brain cortical structural differences in those with non-CNS cancers using clinically-indicated MRIs. Design: Cross-sectional Patients: Adult non-CNS cancer and non-cancer control (C) patients who underwent clinically-indicated MRIs. Methods: Brain cortical surface area and thickness were measured using 3D T1-weighted images. An age-adjusted linear regression model was used and the Benjamini and Hochberg false discovery rate (FDR) corrected for multiple comparisons. Group comparisons were: cancer cases with chemotherapy (Ch+), cancer cases without chemotherapy (Ch-) and subgroup of lung cancer cases with and without chemotherapy vs C. Results: Sixty-four subjects were analyzed: 22 Ch+, 23 Ch- and 19 C patients. Subgroup analysis of 16 LCa was also performed. Statistically significant decreases in either cortical surface area or thickness were found in multiple ROIs primarily within the frontal and temporal lobes for all comparisons. Limitations: Several limitations were apparent including a small sample size that precluded adjustment for other covariates. Conclusions: Our preliminary results suggest that various types of non-CNS cancers, both with and without chemotherapy, may result in brain structural abnormalities. Also, there is a wealth of untapped clinical MRIs that could be used for future CRCI studies.

Altered network topology in pediatric traumatic brain injury

Outcome after a traumatic brain injury (TBI) is quite variable, and this variability is not solely accounted for by severity or demographics. Identifying sub-groups of patients who recover faster or more fully will help researchers and clinicians understand sources of this variability, and hopefully lead to new therapies for patients with a more prolonged recovery profile. We have previously identified two subgroups within the pediatric TBI patient population with different recovery profiles based on an ERP-derived (event-related potential) measure of interhemispheric transfer time (IHTT). Here we examine structural network topology across both patient groups and healthy controls, focusing on the ‘rich-club’ - the core of the network, marked by high degree nodes. These analyses were done at two points post-injury - 2-5 months (post-acute), and 13-19 months (chronic). In the post-acute time-point, we found that the TBI-slow group, those showing longitudinal degeneration, showed hyperconnectivity within the rich-club nodes relative to the healthy controls, at the expense of local connectivity. There were minimal differences between the healthy controls and the TBI-normal group (those patients who show signs of recovery). At the chronic phase, these disruptions were no longer significant, but closer analysis showed that this was likely due to the loss of power from a smaller sample size at the chronic time-point, rather than a sign of recovery. We have previously shown disruptions to white matter (WM) integrity that persist and progress over time in the TBI-slow group, and here we again find differences in the TBI-slow group that fail to resolve over the first year post-injury.

Tract-based spectroscopy to investigate pediatric brain trauma

Traumatic brain injury (TBI) causes extensive damage to the white matter (WM) of the brain, which can be evaluated with diffusion-weighted magnetic resonance imaging (dMRI). Diffusion MRI can be used to map the WM tracts and their integrity, but offers limited understanding of the biochemical basis of any differences. Magnetic resonance spectroscopy (MRS) measures neural metabolites that reflect neuronal health, inflammation, demyelination, and other consequences of TBI. We combined whole-brain MRS with dMRI to investigate WM dysfunction following pediatric TBI, using “tract-based spectroscopy”. Deficits in N-acetylaspartate (NAA) correspond to regions of deficits in WM integrity, but choline showed minimal overlap with WM deficits. NAA is a marker of neuronal health, while choline is an inflammatory marker. A partial F-test showed that MRS measures improved our ability to predict long-term cognitive function. This is the first paper to combine MRS with dMRI-derived tracts on a whole-brain scale, offering insights into the biochemical correlates of WM tract dysfunction, following injury and potentially in other WM disorders.