Development of a Non-invasive Cerebrovascular Status Algorithm to Estimate Cerebral Perfusion Pressure and Intracranial Pressure in a Porcine Model of Focal Brain Injury

Abstract

Background New tools for diagnosis, monitoring, and treatment of elevated intracranial pressure (ICP) or compromised cerebral perfusion pressure (CPP) are urgently needed to improve outcomes after brain injury. Previous success in applying advanced data analytics to build precision monitors based on large, noisy sensor datasets suggested applying the same approach to monitor cerebrovascular status. In these experiments, a new algorithm was developed to estimate ICP and CPP using the arterial pressure waveform. Methods Sixty-five porcine subjects were subjected to a focal brain injury to simulate a mass lesion with elevated ICP. The arterial pressure waveform and the measured ICP from these subjects during injury and treatment were then utilized to develop and calibrate an ICP and CPP estimation algorithm. These estimation algorithms were then subsequently evaluated on 14 new subjects. Results The root mean square difference between actual ICP and estimated ICP was 2.0961 mmHg. The root mean square difference between the actual CPP and the estimated CPP was 2.6828 mmHg. Conclusion A novel ICP or CPP monitor based on the arterial pressure signal produced a very close approximation to actual measured ICP and CPP and warrants further evaluation.