Visualisation of the ‘optimal cerebral perfusion’ landscape in severe traumatic brain injury patients

Abstract

Objective: An ‘optimal’ cerebral perfusion pressure (CPPopt) can be defined as the point on the CPP scale corresponding to the greatest autoregulatory capacity. This can be established by examining the pressure reactivity index PRx–CPP relationship, which is approximately U-shaped but suffers from noise and missing data. In this paper, we present a method for plotting the whole PRx-CPP relationship curve against time in the form of a colour-coded map depicting the ‘landscape’ of that relationship extending back for several hours and to display this robustly at the bedside. This is a short version of a full paper recently published in Critical Care Medicine (2016) containing some new insights and details of a novel bedside implementation based on a presentation during Intracranial Pressure 2016 Symposium in Boston. methods: Recordings from routine monitoring of traumatic brain injury patients were processed using ICM+. Time-averaged means for arterial blood pressure, intracranial pressure, cerebral perfusion pressure (CPP) and pressure reactivity index (PRx) were calculated and stored with time resolution of 1 min. ICM+ functions have been extended to include not just an algorithm of automatic calculation of CPPopt but also the ‘CPPopt landscape’ chart. Results: Examining the ‘CPPopt landscape’ allows the clinician to differentiate periods where the autoregulatory range is narrow and needs to be targeted from periods when the patient is generally haemodynamically stable, allowing for more relaxed CPP management. This information would not have been conveyed using the original visualisation approaches. Conclusions: We describe here a natural extension to the concept of autoregulatory assessment, providing the retrospective ‘landscape’ of the PRx-CPP relationship extending over the past several hours. We have incorporated such visualisation techniques online in ICM+. The proposed visualisation may facilitate clinical evaluation and use of autoregulation-guided therapy.