SBIR Phase I:A cognitive dashboard to support clinical decision making in neurosurgery

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to support the ability of neurosurgeons to remove brain tumors or brain tissue that is causing seizures while protecting the patient’s mental function. As many as 4 in 5 neurosurgery patients self-report a cognitive difficulty after surgery that negatively impacts their quality of life. Neurosurgical interventions to remove brain tumors or treat medically refractory epilepsy try not to cause post-operative cognitive deficits in patients, but sometimes the pathological tissue that needs to be removed is involved with brain tissue that supports critical abilities, like the abilities to talk, remember, or move. Because there is inter-individual variability in the precise location of higher critical functions (e.g., language, memory, locomotion), each patient’s brain must be mapped in a personalized way. Ultimately, patients want confidence they will be the same person coming out of brain surgery as they were going into surgery, and clinical teams want tools that support quantitative pre-operative surgical planning and evidence-based projections of post-operative function.This Small Business Innovation Research Phase I project seeks to support the development of a software product that enables neurosurgical teams to track patients’ mental function over the trajectory of their care, i.e., a type of cognitive dashboard. Current practice lacks a tool that identifies brain tissue that, if removed, would result in long-term cognitive deficits. This project’s core deliverable is a turn-key software platform that supports brain mapping protocols, as well as assessment, scoring, archiving and sharing of measures of mental function across the timeline of care of each patient. The software platform will integrate with critical existing systems already in place in all medical centers (e.g., cranial navigation, electroencephlogram (EEG), and magnetic resonance imaging (MRI) stimulus display systems). Follow-on work to this project’s core deliverable is based on the premise that data from prior studied patients can be used to train artificial intelligence/machinge learning (AI/ML) algorithms which can then be used to simulate the expected effect of a given surgical plan on a new patient’s future cognitive function.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.