Pratik Mukherjee - US grants

DESCRIPTION (provided by applicant): Traumatic brain injury (TBI) is the leading cause of death and disability in Americans under age 45, and is increasing in prevalence worldwide. Neuroimaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI) are important diagnostic tools for the clinical management of acute TBI. However, the focal lesions detected by CT or MRI in acute TBI, such as contusions and axonal shearing injuries, are often not predictive of long-term functional disability after TBI, especially in mild cases. The objective of this research proposal is to establish quantitative macrostructural and microstructural imaging biomarkers for predicting patient outcome after mild TBI. The macrostructural biomarker measures post- traumatic focal atrophy using deformation-based morphometry (DBM) of serial high-resolution 3D MR scans of the brain. The microstructural biomarker measures post-traumatic decreases in white matter integrity using quantitative fiber tracking based on serial diffusion tensor imaging (DTI). One hundred mild TBI patients will undergo high-resolution 3D structural MRI and DTI on 3 Tesla MR scanners at 1 month after injury, at 6 months after injury, and then again at 1 year after injury. Comparison will be made to the same imaging protocol in 40 age-, gender-, and education-matched healthy control subjects. All subjects will undergo neurocognitive and functional outcome tests at the same time points as the MRI/DTI scans. The hypothesis will be tested that increasing spatial extent of progressive focal atrophy detected by DBM of serial MRI and/or progressive white matter microstructural injury on serial DTI is correlated with worse neurocognitive and functional outcomes at one year after injury, after controlling for clinical measures of injury severity including Glasgow Coma Scale, duration of unconsciousness, and duration of post-traumatic amnesia. These macrostructural and microstructural imaging biomarkers will also be correlated with functional and metabolic imaging data using fMRI and 3D MR spectroscopic imaging, respectively. If the proposed investigation is successful in establishing these quantitative macrostructural and microstructural imaging biomarkers of long-term outcome in TBI, then they could potentially serve as surrogate endpoints for clinical intervention trials. They might also yield endophenotypes for studies of genetic susceptibility factors that worsen outcome after TBI. Towards this purpose, DNA will be banked from patients in this study for genotype analysis. Specifically, we will examine whether ApoE genotype influences the degree of regional brain atrophy and microstructural white matter injury. The allelic variants of ApoE are already known to modulate clinical outcome after TBI, and this study will determine if DBM and DTI can provide "intermediate phenotypes" for the effect of ApoE genotype on TBI outcome. PUBLIC HEALTH RELEVANCE: The objective of this research proposal is to apply two new advanced magnetic resonance imaging (MRI) technologies to the study of patients with mild traumatic brain injury: (1) deformation-based morphometry, and (2) diffusion tensor imaging. This research may advance the scientific understanding of brain injury as well as improve the diagnosis of patients suffering from the long-term effects of concussion.

DESCRIPTION (provided by applicant): Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will deliver better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes and thereby improving the next generation of clinical trials. Specific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. Specific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate selection and stratification of patients for clinical trils, and contribute to the development of a new taxonomy for TBI. Specific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. Specific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. The project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers.

? DESCRIPTION (provided by applicant): MRI is the only technology that can image the connectivity of the human brain in vivo and non-invasively. However, neither BOLD fMRI nor diffusion-based fiber tracking has been able to break the barrier of 1-mm voxel spatial resolution. Yet, 1-mm voxel contains roughly 50,000 neuronal cells and the human cortex is less than 5 mm thick. The disparity between the spatial scales has thus created a large gap between MRI studies of the whole brain and optical imaging and cell recordings of groups of neurons. The overarching objective of this proposal is to bring noninvasive human brain imaging into the microscale resolution and begin to bridge studies of neuronal circuitry and network organization in the human brain. Our breakthrough technology, termed MR Corticography (MRCoG), will achieve dramatic gains in spatial and temporal resolutions by focusing exclusively to the cortex. Higher-sensitivity coil sensors will be designed that tailor to the superficial volume of the brain MRCoG will also be used to map intracortical axonal connectivity, overcoming a fundamental resolution limit inherent to all in vivo human neuronal fiber tractography to date by replacing diffusion imaging with a novel susceptibility contrast mapping of axon fibers. Innovative imaging pulse sequences will be designed to complement the high-sensitivity coil arrays to achieve higher spatial resolution in the neocortex. The improved capabilities of these sensors will be further exploited using new, vastly more efficient spatial multiplexed and temporal multiplexed image acquisition to further accelerate scanning by taking advantage of spatiotemporal sparsity. In summary, the proposed research will create a novel technology for imaging the human brain's neocortex with barrier-breaking resolution and contrast. MRCoG will facilitate the integration between in vivo non-invasive human-brain MRI and cellular and genetic imaging techniques. If successful, it will fundamentally transform our ability to study the human brain. Because it is based on MRI, MRCoG can be readily translated to patient care, providing potential high impact in the care of mental health, traumatic brain injuries, epilepsy among many other debilitating brain diseases and disorders.

SUMMARY The overarching objective of our proposal is to bring noninvasive human brain imaging into the microscale (50-500 micron isotropic) resolution in order to create a tool for studies of neuronal circuitry and network organization in the human brain. Our breakthrough technology, MR Corticography (MRCoG), represents substantial advances over existing MRI approaches. MRCoG achieves dramatic gains in spatial and temporal resolutions by focusing several different types of coil arrays on the cerebral cortex of the live human brain. These optimized high-density receiver arrays with 128 coils also serve as a shim array and thereby obtain much higher quality imaging. High-performance magnetic field gradients will be combined with state-of-the-art pulse sequences to produce over 30-times acceleration in echo planar imaging. This will enable us to reach 0.4 mm resolution in fMRI studies of the entire cerebral cortex. This unprecedented spatial resolution in human fMRI is sufficient to identify functional activity at different depth in the cortex corresponding to different cortical layers. MRCoG will also be used to achieve 100-200 micron resolution susceptibility contrast images and this enables us to map intra-cortical axon connections and the cytoarchitecture of human cortex. With over 10 times higher resolution than current 7T scanners, MRCoG will overcome current scale limitations in imaging the function and structure of cortical layers and columns. The evaluation and refinement of MRCoG will entail using advanced computational models of brain circuitry, feedforward and feedback neuronal circuit models and computational models for decoding the brain using data from layer specific and column specific fMRI. Functional and structural MRI performed with MRCoG will generate new avenues to explore human brain circuitry at an order of magnitude higher spatial resolution, while importantly image the entire cortex rather than by current approaches (e.g. zoomed imaging) that measure only small areas of cortex. Many existing 7T MRI scanners will be able to incorporate MRCoG high-resolution technology; therefore, MRCoG can be rapidly disseminated to neuroscience research centers and used to advance medical discoveries. We will evaluate MRCoG ability to resolve currently unobservable cortex abnormalities in epilepsy and autism spectrum disorder (ASD) and to improve localization and mapping of abnormal circuitry in the brain.

Project Summary Sensory over-responsivity (SOR), the unusual negative response to typically non-noxious stimuli, represents a prominent feature of many neurodevelopmental conditions, including Autism Spectrum Disorder (ASD), Anxiety, Attention Deficit/Hyperactivity, and Developmental Coordination Disorders. SOR severely disrupts all aspects of a child's development, including the ability to learn and socially engage. Despite growing recognition of SOR as a core feature in neurodevelopmental conditions, the neural mechanisms of SOR remain unclear. As a result of this gap, SOR has historically been thought to be ?behavioral? or due to ?bad parenting? or a consequence of ?having autism?. This percept has been challenged by data from our lab and others showing white matter microstructural and functional imaging differences in children with sensory processing dysfunction (SPD) and in children with ASD/SOR. Delineating the underlying neural networks that subserve SOR, both auditory and tactile, will not only guide our understanding of this condition, but also shift the conceptualization of SOR to that of a treatable neurologic condition. Obtaining the neural signature of SOR will contribute to finding a biomarker for neural remodeling with cognitive training paradigms similar to what we have piloted in the domain of cognitive control. Our work utilizing in-lab direct assessment of auditory SOR will test the scientific premise that SOR results from the disconnection of a higher-order SOR network: the Posterior Corona Radiata, Superior Longitudinal Fasciculus, and the Cingulate Bundle. We will further determine whether this putative SOR network reflects a general vulnerability in the posterior periventricular regions, which are rich in highly connecting white matter tracts, or is specific to auditory SOR. Furthermore, if this microstructural disconnection is SOR specific, then is it a multi-domain SOR network or does each sensory domain (e.g. auditory and tactile) rely on a unique set of connections-- as is suggested by the non-overlapping sensory domain phenotypes in affected children? A multifaceted phenotype and neuroimaging approach is required to answer these questions. The objective of this proposal is to advance our direct assessment of sensory related behavior and apply novel structural neuroimaging methods to elucidate the neural architecture of SOR using an RDoC approach. To achieve this goal, we will assess auditory and tactile SOR using the Sensory Processing: Three Dimensions Assessment (SP-3D:A) paired with innovative structural imaging, Neurite Orientation Dispersion and Density Imaging, for detailed microstructural assessment, and Edge Density Imaging, for advance connectome assessment, in 170 children, ages 8-12 years, with neurodevelopmental concerns. All phenotype and neuroimaging data will be made available to the field in order to support ongoing understanding of sensory processing in this unique data set.