Noninvasive transcranial detection of intracranial hemorrhage using a tri-coil handheld portable eddy current damping imaging device Stroke and traumatic brain injury (TBI) are common causes of death and permanent disability worldwide, costing the U.S. health system more than $71 billion per year in lost productivity and medical expenses. Existing paradigms for stroke/TBI diagnosis require computed tomography (CT) or magnetic resonance (MR) imaging to classify ischemic versus hemorrhagic variants prior to intervention, as treatment for these conditions varies widely. Delays in diagnosis and issues related to transport of unstable patients associated with diagnostic imaging increase the likelihood of neurological injury and death. Translational medical devices that accelerate time-to-treatment in the field or hospital setting may help to reduce morbidity and mortality in stroke/TBI patients on a global level. Our team has developed a portable, rapid and noninvasive imaging and detection device based on eddy current damping (ECD) sensors that can detect brain hemorrhages associated with stroke and TBI, and have demonstrated feasibility in a benchtop, human cadaver and clinical patient setting. This device can potentially diagnose and classify hemorrhagic stroke/TBI subtypes with accurate spatial localization in minutes, rather than hours, thereby guiding early responders and medical providers in making time-sensitive medical decisions for clinical intervention, such as administration of tissue plasminogen activator for ischemic stroke. Our overall goal is to demonstrate the effectiveness of this novel stroke detection device in rapidly triaging stroke/TBI patients and achieving a level of diagnostic accuracy capable of guiding clinical intervention. We hypothesize that: 1) Regional conductivity changes in brain tissue can be imaged and detected using the portable ECD sensor; 2) Hemorrhagic stroke and TBI-related hemorrhages will increase regional conductivity, whereas ischemic stroke will decrease dependent brain conductivity in affected ischemic regions; and 3) Portable stroke imaging may reduce time-to-treatment and diagnosis associated with stroke/TBI. To test these hypotheses, we aim to: 1) Perform benchtop laboratory experiments to further elucidate how direction and magnitude of measured conductivity changes can differentiate stroke subtype and location, 2) Use validated human cadaver stroke simulation models to optimize ECD tri-coil array sensor detection of hemorrhage depth, volume, and location, 3) Utilize machine learning algorithms to quickly classify brain lesions with high accuracy, and 4) Implement early clinical stroke/TBI ECD sensor device testing to gauge effectiveness in live human patients, compared to CT/MR imaging. Development of methods for rapid bedside stroke/TBI diagnosis will provide practitioners with knowledge required to rapidly administer life-saving treatments, thereby improving patient quality of life and survival. Knowledge derived from this will help to reduce time-to-treatment and guide triage and intervention, which is likely to translate to improved morbidity and mortality associated with these common conditions.

Public Health Relevance

Stroke and traumatic brain injury (TBI) are leading causes of major disability and death, and delays in diagnosis and treatment are associated with higher morbidity and mortality. Current diagnostic standards in stroke and TBI require that patients undergo computed tomography or magnetic resonance imaging in a hospital setting to differentiate ischemic and hemorrhagic subtypes before initiating treatment. Our study proposes to develop a portable, noninvasive stroke/TBI detection and imaging system based on tri-coil eddy current damping technology, thereby rapidly identifying stroke subtypes, accelerating time-to-treatment, and providing early responders with information necessary to more efficiently administer triaged and appropriate intervention in the field or acute care setting.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Acute Neural Injury and Epilepsy Study Section (ANIE)
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Koenig, James I
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University of Southern California
Los Angeles
United States
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