Traumatic Brain Injury- TBI
TBI Background
TBI represents a significant and growing public health concern as a leading cause of mortality and morbidity among young people in the industrialized world. In Israel, approximately 7,000 people sustain TBI annually. In the United States, approximately 1.7 million people sustain TBI each year with 80,000 people becoming disabled annually.
TBI is caused by external mechanical forces that cause damage to vascular or neural components of the brain. In general, TBI may be classified as either focal or diffuse injuries. Focal brain damage consists mainly of vascular injury in the form of cortical or subcortical contusions, brain lacerations as well as intracranial bleedings (such as subarachnoid hemorrhages), which can further lead to hematomas. Diffuse injury is caused by stretching and tearing of the brain tissue and is not necessarily caused by a direct impact to the brain surface. Diffuse brain injuries mostly involve scattered damage to the white matter (diffuse axonal injury-DAI) that lead to shearing of axons.
Long-term TBI-related disabilities vary widely in type and duration and commonly result in reduced quality of life for the patient and prolonged social, medical and economic effects on society. In the majority of cases, TBI results in significant and lifelong interpersonal, emotional, occupational and cognitive problems. The main congnitive impairments are memory impairment, executive function and slowed speed of processing.
Our goal is to deepen the scientific knowledge on TBI, its diagnosis and prediction of cognitive outcome
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In our lab, we use various tools including: advanced structural MRI and fMRI protocols using tailor-made fMRI tasks to examine the deficits after TBI. We apply also extensive neuropsychological batteries in order to investigate cognitive impairments. Also, we examine symptoms and emotional status using validated questionnaires and scales. This data is integrated and analyzed to identify networks and patterns which will further our understanding of neuropathology and neuronal reorganization.
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We conduct research on acute or chronic TBI patients, regardless of their injury severity, namely, patients suffering from mild, moderate or severe head injuries. Furthermore, we study both children and adults who sustained TBI.
TBI Studies
PATENT
Platform Analysis of TBI's Effects using Neuroimaging Techniques
In collaboration with Prof. Yaniv Assaf, Prof. Ofer Keren, Dr. Zion Zibly, and ElMinda
The main objective of this study is to create a clinical tool to assist in the diagnosis, monitoring and predicting of the neurocognitive status of TBI's patients. Neuroimaging can enable a more thorough understanding of cognitive recovery and neuroplasticity after head injury. Participants will be followed for a year post-injury using advanced neuroimaging techniques and cognitive assessments.
We aim to better understand the mechanisms of brain injury and brain recovery processes, and to further develop an objective tool for quantifying the damage and brain recovery process.
MISTIC
Multi-Imaging Study of TBI In Children
In collaboration with Dr. Amichai Brezner , Dr. Tamar Silberg
In children, TBI is the most common cause of acquired brain damage causing physical,cognitive and psychological impairment. The evaluation of outcomes following pediatric-TBI in the still maturing brain poses a major challenge to the research in this field. This study offers a unique multimodality approach using brain structural and functional imaging, together with cognitive assessment to predict longitudinal changes in brain plasticity and cognitive performance following pediatric-TBI. Our major aim is to test a developmental model postulating the joint contribution of injury severity, age at injury and time since injury on different phases of child’s recovery following TBI.
Graph-Theory Study of DTI
Injury severity modulates the association between structural network topology and cognition in TBI
Thesis of Reut Raizman; In collaboration with Dr. Ido Tavor
TBI is often characterized by white matter damage, producing alterations in brain connectivity. These alterations are commonly suspected to disrupt the function of large-scale networks that support cognition. One approach to explore these alternations is graph theory, which examines the brain from a network perspective. The present study aims to examine whether injury severity modulates white matter connectivity and the association between the connectivity and cognition in TBI using a diffusion MRI based network analysis.
Voxel-Mirrored-Homotopic Functional Connectivity
The effect of Injury severity on VMHC following traumatic brain injury
and its association with cognitive deficits
Thesis of Nitzan Meizels
This study aims to explore the interhemispheric intrinsic connectivity in TBI. TBI often cause diffuse axonal injury, described as shearing of white matter tracts, specifically the corpus callosum and other interhemispheric white matter microstructure. In this study, we examine the hypothesis that TBI will exhibit decreased interhemispheric functional connectivity by using voxel-mirrored homotopic connectivity. VMHC quantifies the resting-state functional connectivity between each voxel in one hemisphere and its mirrored counterpart in the opposite hemisphere.
fMRI- Working-Memory Task
Modulation of WM task activation following TBI by injury severity and premorbid intelligence
In collaboration with Prof. Mark Weiser, Dr. Sagi Har-Nof, Dr. Tammar Kushnir, and Prof. Anat Biegon
Cognitive deficits are the most common outcome post-TBI, they are also the most difficult to quantify due to the wide range of cognitive performance in the population and the lack of actual premorbid data.We examined to what extent the level of premorbid intelligence (using data collected by the Israeli defense forces) influences cognitive outcome and contributes to differential patterns of brain function while performing a working-menory (n-back) task, as demonstrated by measurements of brain activity using fMRI. We also examined the effect of injury severity on cognitive performance, brain structure and function (Livny et al. 2016)
