Simulation of spreading depolarization trajectories in cerebral cortex: Correlation of velocity and susceptibility in patients with aneurysmal subarachnoid hemorrhage.

Denny Milakara,Jed A Hartings,Alon Friedman,Johannes Woitzik,Sebastian Major,Karl Schoknecht,Svetlana Lublinsky,Markus Dahlem,Michael Scheel,Peter Martus,Maren K.L Winkler,Jens P Dreier,Vasilis Kola,Janos Lückl,Cristian Grozea

doi:10.1016/j.nicl.2017.09.005

Abstract

In many cerebral grey matter structures including the neocortex, spreading depolarization (SD) is the principal mechanism of the near-complete breakdown of the transcellular ion gradients with abrupt water influx into neurons. Accordingly, SDs are abundantly recorded in patients with traumatic brain injury, spontaneous intracerebral hemorrhage, aneurysmal subarachnoid hemorrhage (aSAH) and malignant hemispheric stroke using subdural electrode strips. SD is observed as a large slow potential change, spreading in the cortex at velocities between 2 and 9 mm/min. Velocity and SD susceptibility typically correlate positively in various animal models. In patients monitored in neurocritical care, the Co-Operative Studies on Brain Injury Depolarizations (COSBID) recommends several variables to quantify SD occurrence and susceptibility, although accurate measures of SD velocity have not been possible. Therefore, we developed an algorithm to estimate SD velocities based on reconstructing SD trajectories of the wave-front's curvature center from magnetic resonance imaging scans and time-of-SD-arrival-differences between subdural electrode pairs. We then correlated variables indicating SD susceptibility with algorithm-estimated SD velocities in twelve aSAH patients. Highly significant correlations supported the algorithm's validity. The trajectory search failed significantly more often for SDs recorded directly over emerging focal brain lesions suggesting in humans similar to animals that the complexity of SD propagation paths increase in tissue undergoing injury.

Highlights

It is increasingly recognized that spreading depolarization (SD) is the principal mechanism of the mass edema of neurons in many grey matter structures of the brain including the neocortex (Dreier and Reiffurth, 2017)
According to Leão's original notion that SD is the principal response of neurons to a prolonged episode of cerebral ischemia (Leão, 1947; Marshall, 1959), this apparent diffusion coefficient (ADC) decline represents the gold standard for diagnosis of acute ischemia in the cortex in clinical neurology (Dreier and Reiffurth, 2015)
It corresponds well with this notion that electrophysiological evidence of SDs has been found in practically 100% of patients with malignant hemispheric stroke (MHS) (Dohmen et al, 2008; Woitzik et al, 2013), 70–80% of patients with poor-grade aneurysmal subarachnoid hemorrhage (Dreier et al, 2009; Dreier et al, 2006), 60–70% of patients with intracerebral hemorrhage (ICH) (Fabricius et al, 2006; Helbok et al, 2017) and 50–60% of patients with severe traumatic brain injury (TBI) (Fabricius et al, 2006; Hartings et al, 2011a)

Summary

Introduction

It is increasingly recognized that spreading depolarization (SD) is the principal mechanism of the mass edema of neurons in many grey matter structures of the brain including the neocortex (Dreier and Reiffurth, 2017). SD-induced cytotoxic edema is observed in animals using electron microscopy (Van Harreveld and Khattab, 1967) and the quaternary ammonium salt method (Mazel et al, 2002; Perez-Pinzon et al, 1995; Windmuller et al, 2005) as an abrupt decrease of the extracellular volume fraction and increase in tortuosity, which describes the average path length for diffusion between two points in the extracellular compartment It is visualized as swelling of the neuronal somata and dendritic beading using two-photon microscopy (Murphy et al, 2008; Obeidat et al, 2000; Rungta et al, 2015; Steffensen et al, 2015; Takano et al, 2007). Similar to electrographic seizures, SDs never occur spontaneously in healthy brain (Dreier and Reiffurth, 2017; Hartings et al, 2017b)

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