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In Vivo Tracking of Edema Development and Microvascular Pathology in a Model of Experimental Cerebral Malaria Using Magnetic Resonance Imaging
Published on: June 8, 2017
Analysis of brain edema in RHAPSODY
Riana L Schleicher1, Pongpat Vorasayan1,2, Megan E McCabe3
1Division of Neurocritical Care and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Background:
Cerebral edema is a secondary complication of acute ischemic stroke, but its time course and imaging markers are not fully understood. Recently, net water uptake (NWU) has been proposed as a novel marker of edema.
Aims:
Studying the RHAPSODY trial cohort, we sought to characterize the time course of edema and test the hypothesis that NWU provides distinct information when added to traditional markers of cerebral edema after stroke by examining its association with other markers.
Methods:
A total of 65 patients had measurable supratentorial ischemic lesions. Patients underwent head computed tomography (CT), brain magnetic resonance imaging (MRI) scans, or both at the baseline visit and after 2, 7, 30, and 90 days following enrollment. CT and MRI scans were used to measure four imaging markers of edema: midline shift (MLS), hemisphere volume ratio (HVR), cerebrospinal fluid (CSF) volume, and NWU using semi-quantitative threshold analysis. Trajectories of the markers were summarized, as available. Correlations of the markers of edema were computed and the markers compared by clinical outcome. Regression models were used to examine the effect of 3K3A-activated protein C (APC) treatment.
Results:
Two measures of mass effect, MLS and HVR, could be measured on all imaging modalities, and had values available across all time points. Accordingly, mass effect reached a maximum level by day 7, normalized by day 30, and then reversed by day 90 for both measures. In the first 2 days after stroke, the change in CSF volume was associated with MLS (ρ = -0.57, p = 0.0001) and HVR (ρ = -0.66, p < 0.0001). In contrast, the change in NWU was not associated with the other imaging markers (all p ⩾ 0.49). While being directionally consistent, we did not observe a difference in the edema markers by clinical outcome. In addition, baseline stroke volume was associated with all markers (MLS (p < 0.001), HVR (p < 0.001), change in CSF volume (p = 0.003)) with the exception of NWU (p = 0.5). Exploratory analysis did not reveal a difference in cerebral edema markers by treatment arm.
Conclusions:
Existing cerebral edema imaging markers potentially describe two distinct processes, including lesional water concentration (i.e. NWU) and mass effect (MLS, HVR, and CSF volume). These two types of imaging markers may represent distinct aspects of cerebral edema, which could be useful for future trials targeting this process.
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