The broader impact/commercial potential of this I-Corps project is the development of a technology that may dramatically reduce the time-to-diagnosis of ischemic stroke. As one of the world’s most consequential and prevalent neurological diseases, stroke affects a large portion of the population and costs the healthcare system billions of dollars. The time-to-diagnosis is critical within the “golden hour†normally associated with stroke management. The ability to provide a rapid diagnosis with equipment less costly than currently perfusion-scan computed tomography (CT) machines may increase the number of patients in less affluent locations who are correctly diagnosed and rapidly treated for a stroke. The immediate benefits are reduction in the rate of mortality and post-stroke disabilities due to faster treatment, as well as an increase in the accessibility of treatment, and a significant decrease in costs. Despite the focus on ischemic strokes, this method may have applications on a variety of neurological diseases related to the brain’s hemodynamic systems, such as cerebrovascular accident, traumatic brain injury (TBI), and brain tumors.
This I-Corps project is based on the development of a medical device that uses medical image processing, sensor measurements, computational modeling, and machine learning to replicate CT perfusion images quantifying cerebral blood flow, which is the most significant metric in stroke severity assessment and patient management. This novel hardware/software system also provides real-time non-invasive patient-specific estimates for stroke severity and risk assessment, along with predictive measures for differentiating infarct tissue from salvageable penumbra. The proposed technology, as an enhancement to existing CT scans, addresses the global demand, especially from small community hospitals and stroke centers that lack perfusion imaging devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
