SBIR-STTR Award

The proposed research focuses on the use of neuroimaging and machine learning to detect and understand the progression of neurodegeneration caused by repetitive brain trauma, and to differentiate this from that caused by Alzheimer's disease (AD) and other dementias. The deliverables defined in this Phase I stage will support the development of a commercial software product for use in pharmaceutical clinical trials and in clinical diagnosis. Traumatic Brain Injury (TBI) has been shown to cause cognitive deterioration and other symptoms that overlap those arising with AD. TBI can also lead to the development of Chronic Traumatic Encephalopathy (CTE), which shares similarities in brain atrophy and tau accumulation with AD. There is mixed evidence as to whether TBI increases the risk or rate of developing AD, but regardless, the likelihoods of co-morbidity and misdiagnosis become high as individuals age. The relevant population includes professional sports athletes, individuals who played head contacting sports during high school or college, military veterans, and persons experiencing falls. However, the process by which TBI causes progressive damage, and the ways in which it can best be discriminated from AD, have not been determined. The aims of this grant focus on characterizing the progressive structural and pathology effects of TBI and discriminating these from AD using imaging of structure, function, and pathology, and machine learning. Classifiers will be developed using these information types alone and in combination. Innovations of this work include the use of a unique, comprehensive data set of imaging, cognitive, and other data acquired on more than 600 fighters by the Cleveland Clinic, a database of more than 10,000 well-characterized scans from persons across the spectrum of pre-symptomatic and symptomatic AD and other dementias, and a sophisticated machine learning software platform that addresses issues such as data overfitting and validation. Specific Aim 1 focuses on characterizing neurodegenerative changes that occur in fighters using volumetric (T1 weighted MRI) and white matter (Diffusion Tensor, DTI) imaging. Aim 2 will characterize tau accumulation in fighters and its relationship to and structural changes, comparing the two tracers 18F-AV1451 and 18F-FDDNP. Specific Aim 3 will determine methods to differentiate TBI related neurodegeneration from AD using structural and tau imaging. Follow on work in Phase II will include model refinement and additional validation with additional independent data, further prediction of cognitive impairment, extension to functional imaging modalities ASL and fMRI BOLD, dissociation of co-existing TBI and AD, comparisons to other forms of trauma, and development of software tools for commercialization. This work can have significant societal benefit through improved detection of TBI effects and precursors to greater damage and impairment, and accurate differentiation of AD and other dementias versus TBI effects to support optimal patient care.

Public Health Relevance Statement:
NARRATIVE This research addresses a critical gap in the understanding of the neurodegenerative effects of Traumatic Brain Injury (TBI), and the ability to differentiate effects of TBI from those caused by Alzheimer's disease (AD) and other neurodegenerative dementias. Advances in machine learning will be applied to a unique multi-modality data set acquired in over 650 boxers and mixed martial arts fighters who have experienced varying exposure to head trauma and years since trauma was incurred, and to a data from a set of more than 10,000 scans acquired in persons at varying stages of mild cognitive impairment and dementia due to Alzheimer's disease and other dementias. Outcomes of the research will enable a diagnostic tool to be developed that enables differentiation of TBI effects from those of other dementias, and that increases the understanding of the path by which TBI can cause progressive cognitive impairment.

Project Terms:
Achievement; Achievement Attainment; Age; ages; Alzheimer's Disease; senile dementia of the Alzheimer type; primary degenerative dementia; dementia of the Alzheimer type; Primary Senile Degenerative Dementia; Alzheimers disease; Alzheimers Dementia; Alzheimer's; Alzheimer syndrome; Alzheimer sclerosis; Alzheimer disease; Alzheimer Type Dementia; Alzheimer; Amyloid; Amyloid Substance; Apolipoprotein E; ApoE; Apo-E; Clinical Trials; Comorbidity; co-morbidity; Cross-Sectional Studies; Disease Frequency Surveys; Cross-Sectional Survey; Cross-Sectional Analyses; Cross Sectional Analysis; Diffusion; Discrimination; Cognitive Discrimination; Education; Educational aspects; Evolution; Patient Care; Patient Care Delivery; Genotype; Grant; Head; Craniocerebral Trauma; Head Trauma; Head Injuries; Craniocerebral Injuries; Influentials; Lead; heavy metal lead; heavy metal Pb; Pb element; Magnetic Resonance Imaging; Zeugmatography; Nuclear Magnetic Resonance Imaging; NMR Tomography; NMR Imaging; Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance; MRI; MR Tomography; MR Imaging; Methods; Military Personnel; Military; Armed Forces Personnel; Persons; Nerve Degeneration; neuronal degeneration; neurological degeneration; neurodegenerative; neurodegeneration; neural degeneration; Neuron Degeneration; Pathology; Patients; Play; Positron-Emission Tomography; positron emitting tomography; positron emission tomographic imaging; positron emission tomographic (PET) imaging; Rad.-PET; Positron Emission Tomography Scan; Positron Emission Tomography Medical Imaging; PETT; PETSCAN; PET imaging; PET Scan; PET; Research; Risk; ROC Curve; ROC Analyses; Sensitivity and Specificity; Computer software; Software; Software Tools; Computer Software Tools; Sports; Time; Veterans; Work; Martial Arts; Measures; tau Proteins; τ Proteins; tau factor; tau; microtubule-bound tau; microtubule bound tau; MT-bound tau; falls; Dissociation; Normal Range; Normal Values; Outcomes Research; Data Set; Dataset; career; improved; Clinical; Phase; Variation; Variant; cortical atrophy; brain atrophy; cerebral atrophy; Individual; data base; Data Bases; Databases; Measurement; Disease Progression; clinical Diagnosis; Exposure to; Deposition; Deposit; tool; Impaired cognition; cognitively impaired; cognitive loss; cognitive dysfunction; Disturbance in cognition; Cognitive function abnormal; Cognitive decline; Cognitive Impairment; Cognitive Disturbance; Diagnostic; Nature; Machine Learning; support vector machine; statistical learning; kernel methods; Functional Magnetic Resonance Imaging; fMRI; Functional MRI; fighting; Frequencies; Event; Scanning; Clinic; Pattern; Dementia; Amentia; college; collegiate; experience; success; high school; Structure; neuroimaging; neuro-imaging; white matter; substantia alba; Modality; Deterioration; Modeling; Sampling; software development; developing computer software; develop software; Traumatic Brain Injury; traumatic brain damage; Brain Trauma; MRI Scans; Magnetic Resonance Imaging Scan; model development; Pharmacologic Substance; Pharmacological Substance; Pharmaceuticals; Pharmaceutical Agent; imaging modality; imaging method; image-based method; Address; Symptoms; Data; Detection; Reproducibility; Sum; Cognitive; physiological imaging; Physiologic Imaging; Functional Imaging; Validation; Characteristics; Process; sex; Tracer; developmental; Development; Behavioral; imaging; Image; preclinical; pre-clinical; τ aggregation; tau-tau interaction; tau polymerization; tau paired helical filament; tau oligomer; tau neurofibrillary tangle; tau filament; tau fibrillization; tau aggregate; tau accumulation; tau PHF; self-aggregate tau; paired helical filament of tau; microtubule associated protein tau deposit; microtubule associated protein tau aggregation; filamentous tau inclusion; abnormally aggregated tau protein; tau aggregation; designing; design; neurodegenerative dementia; Population; Trauma; innovative; innovate; innovation; Impairment; Affective; healthy volunteer; commercialization; mild cognitive disorder; mild cognitive impairment; Traumatic encephalopathy; chronic traumatic encephalopathy; imaging marker; imaging biomarker; head impact; Software Framework; longitudinal data set; longitudinal dataset

The goal or our SBIR Phase II work is to develop a diagnostic tool using brain imaging and other biomarkers to identify Chronic Traumatic Encephalopathy (CTE) and preceding stages in living individuals, and to differentiate these from Alzheimer's disease (AD) and other dementias. CTE is a devastating neurodegenerative disorder found in individuals who have experienced repetitive head impact (RHI), causing symptoms of cognitive impairment that lead to dementia, and mood and behavioral disturbances that may lead to violence or suicide. While CTE has been most publicized in retired NFL players and "punch drunk" boxers, exposure to repetitive head impact occurs in soccer, hockey, military combat, domestic violence, repeated falls in elderly, and other persons, with over 300,000,000 individuals at potential risk. Currently, although a clinical diagnosis of Traumatic Encephalopathy Syndrome (TES) has been developed to suggest probable CTE, CTE can only be diagnosed at autopsy and can be misdiagnosed during life as AD or other dementias. There are no treatments and no means to detect earlier, progressive stages that could support the development of interventional treatments. Neuroimaging biomarkers and their combination with fluid biomarkers have the potential to address the need for a CTE diagnostic by detecting changes in brain connectivity, volume, function, and chemistries that comprise CTE's progressive, cascade-like deterioration. In our Phase I SBIR work, we applied machine learning methods to the volumetric (T1) and diffusion tensor (DTI) magnetic resonance imaging (MRI) scans of fighters in the Cleveland Clinic Professional Fighters Brain Health Study (PFBHS). We demonstrated a progressive pattern of effects and differentiation of persons with TES and likely CTE, patterns of atrophy differentiating the effects of traumatic brain injury (TBI) from those in patients with AD related cognitive impairment, and preliminary relationships to tau. Our Phase II Aims expand this work to include different populations with RHI, within-subject longitudinal data analyses, and inclusion of functional imaging and fluid biomarkers toward achieving a broadly applicable commercially available tool that can (a) detect and differentiate CTE from AD and (b) detect and stage earlier progressive effects of TBI. We will use a uniquely comprehensive data set of multi-modality MRI, tau PET, clinical endpoints, and fluid biomarkers from (a) 719 boxers, mixed martial artists, martial artists, and controls in the PFBHS set, of whom 165 have at least 3 imaging visits; (b) 240 former professional and college football players and controls (DIAGNOSE- CTE); (c) 219 collegiate contact sports athletes and controls (CARE); (d) 600 Vietnam veterans with TBI and/or Post Traumatic Stress Disorder and controls (ADNI-DOD); and (e) individuals from our reference set of over 30,000 MRI and PET scans from individuals representing a spectrum of cognitively normal and cognitively impaired states associated with AD and other dementias. Building on our success from Phase I, we will develop expanded Canonical Variate and deep learning classifiers using imaging and fluid biomarkers that can be applied in the clinic to evaluate persons with a history of RHI. Input regarding clinical utility and interpretability from our expert Advisors will be used to guide report design. These Aims provide the foundation for commercial products and services supporting CTE differential diagnosis and treatment development.

Public Health Relevance Statement:
NARRATIVE Chronic Traumatic Encephalopathy (CTE) is a progressive, devastating condition associated with repeated head impact that causes brain deterioration leading to problems with mood, thinking, and behavior, but which cannot be definitively diagnosed until autopsy. There is a tremendous need for a diagnostic tool that can be used in the clinic to assess persons with a history of RHI, which includes an at-risk population of more than 300,000,000 worldwide involved in contact sports, military combat, and domestic violence. Using artificial intelligence (machine learning) and an extensive collection of brain images and blood measures from boxers, football players, and other settings, we plan to develop a diagnostic tool to enable diagnosis in the clinic and treatment development for CTE.

Project Terms:
Accounting; Achievement; Achievement Attainment; Affect; Elderly; advanced age; elders; geriatric; late life; later life; older adult; older person; senior citizen; Alzheimer's Disease; AD dementia; Alzheimer; Alzheimer Type Dementia; Alzheimer disease; Alzheimer sclerosis; Alzheimer syndrome; Alzheimer's; Alzheimer's disease dementia; Alzheimers Dementia; Alzheimers disease; Primary Senile Degenerative Dementia; dementia of the Alzheimer type; primary degenerative dementia; senile dementia of the Alzheimer type; Artificial Intelligence; AI system; Computer Reasoning; Machine Intelligence; Automation; Autopsy; necropsy; postmortem; Behavior; Blood; Blood Reticuloendothelial System; Brain; Brain Nervous System; Encephalon; Brain Diseases; Brain Disorders; Encephalon Diseases; Intracranial CNS Disorders; Intracranial Central Nervous System Disorders; Cerebral Ventricles; Brain Ventricle; Chemistry; Classification; Systematics; Data Analyses; Data Analysis; data interpretation; Diagnosis; Differential Diagnosis; Diffusion; Evaluation Studies; Feedback; Manufactured football; Football; Foundations; Goals; Recording of previous events; History; Hockey; Lead; Pb element; heavy metal Pb; heavy metal lead; Magnetic Resonance Imaging; MR Imaging; MR Tomography; MRI; MRIs; Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance; NMR Imaging; NMR Tomography; Nuclear Magnetic Resonance Imaging; Zeugmatography; Methods; Military Personnel; Armed Forces Personnel; Military; military population; Moods; Persons; Neuron Degeneration; neural degeneration; neurodegeneration; neurodegenerative; neurological degeneration; neuronal degeneration; Nerve Degeneration; Pathology; Patients; PET; PET Scan; PET imaging; PETSCAN; PETT; Positron Emission Tomography Medical Imaging; Positron Emission Tomography Scan; Rad.-PET; positron emission tomographic (PET) imaging; positron emission tomographic imaging; positron emitting tomography; Positron-Emission Tomography; Rest; Risk; aberrant sleep; disrupted sleep; disturbed sleep; impaired sleep; irregular sleep; sleep disruption; sleep dysregulation; Sleep disturbances; Soccer; PTSD; Post-Traumatic Neuroses; Posttraumatic Neuroses; Posttraumatic Stress Disorders; post-trauma stress disorder; posttrauma stress disorder; traumatic neurosis; Post-Traumatic Stress Disorders; fatal attempt; fatal suicide; intent to die; suicidality; Suicide; Syndrome; Testing; thoughts; Thinking; Veterans; Vietnam; Viet Nam; Violence; violent; violent behavior; Work; Martial Arts; Measures; tau Proteins; MT-bound tau; microtubule bound tau; microtubule-bound tau; tau; tau factor; τ Proteins; falls; Data Set; Dataset; Brain imaging; brain visualization; Clinical; Phase; Domestic Violence; Training; Blood flow; insight; Individual; Neurologist; Data Bases; data base; Databases; Populations at Risk; Measurement; fluid; liquid; Liquid substance; clinical diagnosis; Exposure to; Deposit; Deposition; Atrophy; Atrophic; tool; Frontal Temporal Dementia; front temporal dementia; frontal lobe dementia; fronto-temporal dementia; fronto-temporal lobar dementia; frontotemporal lobar dementia; frontotemporal lobe degeneration associated with dementia; Frontotemporal Dementia; Cognitive Disturbance; Cognitive Impairment; Cognitive decline; Cognitive function abnormal; Disturbance in cognition; cognitive dysfunction; cognitive loss; Impaired cognition; Diagnostic; machine learned; Machine Learning; Functional MRI; fMRI; Functional Magnetic Resonance Imaging; Life; artist; fighting; Clinic; Protocol; Protocols documentation; Source; Pattern; Amentia; Dementia; Degenerative Neurologic Diseases; Degenerative Neurologic Disorders; Nervous System Degenerative Diseases; Neural Degenerative Diseases; Neural degenerative Disorders; Neurodegenerative Diseases; Neurologic Degenerative Conditions; degenerative diseases of motor and sensory neurons; degenerative neurological diseases; neurodegenerative illness; Neurodegenerative Disorders; Cognitive Manifestations; Cognitive Symptoms; Neurobehavioral Signs and Symptoms; neurobehavioral symptom; Neurobehavioral Manifestations; Visit; meetings; collegiate; college; Services; early detection; Early Diagnosis; experience; success; Structure; neuro-imaging; neurological imaging; neuroimaging; Participant; substantia alba; white matter; Modality; Reporting; Deterioration; Modeling; data integrity; Brain Trauma; traumatic brain damage; Traumatic Brain Injury; Magnetic Resonance Imaging Scan; MRI Scans; disorder control; disease control; brain volume; image-based method; imaging method; imaging modality; Address; Symptoms; Data; Detection; Cognitive; Collection; Functional Imaging; Physiologic Imaging; physiological imaging; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Validation; Behavioral; Image; imaging; tau mutation; abnormal tau; microtubule associated protein tau mutation; microtubule-associated protein tau mutation; mutant tau; mutation in microtubule associated protein tau; mutation in microtubule-associated protein tau; pathogenic tau; pathogenic tau gene mutation; pathological change in tau; tau abnormality; tau intronic mutation; tau pathological change; τ mutation; tau aggregation; abnormally aggregated tau protein; filamentous tau inclusion; microtubule associated protein tau aggregation; microtubule associated protein tau deposit; paired helical filament of tau; self-aggregate tau; tau PHF; tau accumulation; tau aggregate; tau fibrillization; tau filament; tau neurofibrillary tangle; tau oligomer; tau paired helical filament; tau polymerization; tau-tau interaction; τ aggregation; design; designing; Population; data acquisition; clinical effect; nonalzheimer dementia; non-alzheimer dementia; non-alzheimer's associated dementia; non-alzheimer's disease associated dementia; non-alzheimer's disease dementia; non-alzheimer's disease related dementia; non-alzheimer's related dementia; nonalzheimer's associated dementia; nonalzheimer's disease associated dementia; nonalzheimer's disease dementia; nonalzheimer's disease related dementia; nonalzheimer's related dementia; therapy development; develop therapy; intervention development; treatment development; combat; multimodality; multi-modality; Biological Markers; bio-markers; biologic marker; biomarker; chronic traumatic encephalopathy; Traumatic encephalopathy; imaging biomarker; imaging marker; imaging-based biological marker; imaging-based biomarker; imaging-based marker; head impact; rate of change; support tools; brain health; neuroimaging marker; neuroimaging biomarker; biomarker validation; marker validation; deep learning; learning classifier; diverse data; data diversity; machine learning method; machine learning based method; machine learning methodologies; combat veteran; contact sports; collision sports; machine learning classifier; machine learning based classifier; arterial spin labeling; arterial spin tagging; diagnostic tool