Dataset Information

Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study.

ABSTRACT: Traumatic brain injury (TBI) is often characterized by alterations in brain connectivity. We explored connectivity alterations from a network perspective, using graph theory, and examined whether injury severity affected structural connectivity and modulated the association between brain connectivity and cognitive deficits post-TBI. We performed diffusion imaging network analysis on chronic TBI patients, with different injury severities and healthy subjects. From both global and local perspectives, we found an effect of injury severity on network strength. In addition, regions which were considered as hubs differed between groups. Further exploration of graph measures in the determined hub regions showed that efficiency of six regions differed between groups. An association between reduced efficiency in the precuneus and nonverbal abstract reasoning deficits (calculated using actual pre-injury scores) was found in the controls but was lost in TBI patients. Our results suggest that disconnection of network hubs led to a less efficient network, which in turn may have contributed to the cognitive impairments manifested in TBI patients. We conclude that injury severity modulates the disruption of network organization, reflecting a "dose response" relationship and emphasize the role of efficiency as an important diagnostic tool to detect subtle brain injury specifically in mild TBI patients.

SUBMITTER: Raizman R

PROVIDER: S-EPMC7272462 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study.

Raizman Reut R Tavor Ido I Biegon Anat A Harnof Sagi S Hoffmann Chen C Tsarfaty Galia G Fruchter Eyal E Tatsa-Laur Lucian L Weiser Mark M Livny Abigail A

Scientific reports 20200604 1

Traumatic brain injury (TBI) is often characterized by alterations in brain connectivity. We explored connectivity alterations from a network perspective, using graph theory, and examined whether injury severity affected structural connectivity and modulated the association between brain connectivity and cognitive deficits post-TBI. We performed diffusion imaging network analysis on chronic TBI patients, with different injury severities and healthy subjects. From both global and local perspectiv ...[more]

PMID: 32499553

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Project description:ObjectiveTraumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient's long-term prognosis.MethodsDiffusion-weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate-to-severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient.ResultsWe were able to identify the subject-specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal-hippocampal network and the cortico-striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI.InterpretationThese findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., "diaschisis") from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject-specific biomarkers relevant for disease monitoring and personalized therapies in TBI.

Project description:Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Project description:Mild traumatic brain injury is the most prevalent neurological insult and frequently results in neurobehavioural sequelae. However, little is known about the pathophysiology underlying the injury and how these injuries change as a function of time. Although diffusion tensor imaging holds promise for in vivo characterization of white matter pathology, both the direction and magnitude of anisotropic water diffusion abnormalities in axonal tracts are actively debated. The current study therefore represents both an independent replication effort (n = 28) of our previous findings (n = 22) of increased fractional anisotropy during semi-acute injury, as well as a prospective study (n = 26) on the putative recovery of diffusion abnormalities. Moreover, new analytical strategies were applied to capture spatially heterogeneous white matter injuries, which minimize implicit assumptions of uniform injury across diverse clinical presentations. Results indicate that whereas a general pattern of high anisotropic diffusion/low radial diffusivity was present in various white matter tracts in both the replication and original cohorts, this pattern was only consistently observed in the genu of the corpus callosum across both samples. Evidence for a greater number of localized clusters with increased anisotropic diffusion was identified across both cohorts at trend levels, confirming heterogeneity in white matter injury. Pooled analyses (50 patients; 50 controls) suggested that measures of diffusion within the genu were predictive of patient classification, albeit at very modest levels (71% accuracy). Finally, we observed evidence of recovery in lesion load in returning patients across a 4-month interval, which was correlated with a reduction in self-reported post-concussive symptomatology. In summary, the corpus callosum may serve as a common point of injury in mild traumatic brain injury secondary to anatomical (high frequency of long unmyelinated fibres) and biomechanics factors. A spatially heterogeneous pattern of increased anisotropic diffusion exists in various other white matter tracts, and these white matter anomalies appear to diminish with recovery. This macroscopic pattern of diffusion abnormalities may be associated with cytotoxic oedema following mechanical forces, resulting in changes in ionic homeostasis, and alterations in the ratio of intracellular and extracellular water. Animal models more specific to the types of mild traumatic brain injury typically incurred by humans are needed to confirm the histological correlates of these macroscopic markers of white matter pathology.

Dataset Information

Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study.

Publications

Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study.

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