Multimodality Monitoring: Illuminating the Comatose Human Brain

Abstract

The field of neurocritical care has evolved tremendously in recent years, a development explained vastly by the advent of neurophysiological monitoring. From basic intracranial pressure measurements to brain tissue oxygenation, microdialysis, cerebral blood flow (CBF), and surface and intracortical electroencephalography (EEG), our ability to detect and control physiologic endpoints of brain function in comatose patients has grown substantially. The integration of these data gave birth to the concept of multimodality monitoring (MMM). Real-time data acquisition and analysis systems are crucial for fully understanding the relationship between physiologic drivers such as blood pressure, temperature and end-tidal CO, and end-point measures of brain metabolism such as brain tissue oxygen tension, CBF, lactate/pyruvate ratio, and EEG. Multimodality monitoring provides an early warning system for detecting physiological derangements that can be corrected before secondary brain injury occurs. Multimodality monitoring also allows for the creation of an optimized physiological environment for the injured brain, with the goal of preventing secondary injury events. The authors review the basic ideas and technical aspects of MMM, and therefore provide a unique window of illumination into the comatose human brain.

Practice Standards for the Use of Multimodality Neuromonitoring: A Delphi Consensus Process*

“…Disease-specific practice surveys from Europe and Latin America have focused on MNM for traumatic brain injury (TBI) (6)(7)(8). Narrative reviews of invasive and noninvasive MNM (9)(10)(11)(12)(13)(14)(15), or MNM for patients with TBI (16,17), aneurysmal subarachnoid hemorrhage (aSAH) (18,19), and cardiac arrest (20) also exist. Yet, there remains no consensus regarding: a) the minimum set of technologies required for MNM, b) which patients may benefit from care guided by MNM, c) the effort required to integrate MNM measurements and interpret the resulting data, and d) the training required to understand and accurately interpret MNM information.…”