Grant: Alliance Grants

Monitoring of brain physiology, such as intracranial pressure (ICP), mean arterial pressure, and derived subject-specific physiologic targets (optimal mean arterial blood pressure (MAPopt)) is fraught with challenges. Obtaining ICP, and its derived measures, requires the use of invasively placed devices into brain tissue, carrying significant limitations, including: cost, risk to subject, specialized expertise to place, and limited spatial resolution. Medical device companies, such as Medtronic, have explored potentially cheaper, non-invasive alternatives, including cerebral near infrared spectroscopy (NIRS), for continuous regional cerebral oxygen saturation (rSO2) measurements. Such rSO2 measures are believed to represent, in high-temporal resolution, a surrogate for pulsatile cerebral blood volume, of which ICP is also a surrogate. Despite enthusiasm for NIRS devices, their adoption over "standard" invasive technologies have not widely occurred. This is related to existing knowledge gaps related to the signal sources. These existing knowledge gaps include: i. the statistical behavior of NIRS signals, ii. temporal relation between rSO2 and ICP, iii. the relation between rSO2 and pressure-flow physiology, iv. the ability of NIRS-based measures to derive MAPopt metrics, and v. a robust algorithm for continuous live-time MAPopt derivation. Furthermore, data sets containing rSO2, ICP and MAP signals are globally rare, requiring significant natural sciences and engineering (NSE) expertise to process. Leveraging the globally unique existing archived dataset and NSE expertise at University of Manitoba, Medtronic will partner with the Zeiler lab for the purposes of bridging these existing fundamental gaps in our understanding of non-invasive NIRS cerebral monitoring, while building solutions for non-invasive ICP estimation and continuous algorithms for MAPopt derivation using NIRS. Such advances will benefit several NSE fields (signal processing, physiologic state models, NIRS technology applications, and big data approaches), provide leading biotechnology training experiences for several graduate/undergraduate trainees, and enhance the utility and accessibility of Medtronic's devices.