Novel Imaging Markers of Ischemic Cerebral Edema and Its Association with Neurological Outcome

CSF-Based Volumetric Imaging Biomarkers Highlight Incidence and Risk Factors for Cerebral Edema After Ischemic Stroke

BACKGROUND

Cerebral edema has primarily been studied using midline shift or clinical deterioration as end points, which only captures the severe and delayed manifestations of a process affecting many patients with stroke. Quantitative imaging biomarkers that measure edema severity across the entire spectrum could improve its early detection, as well as identify relevant mediators of this important stroke complication.

METHODS

We applied an automated image analysis pipeline to measure the displacement of cerebrospinal fluid (ΔCSF) and the ratio of lesional versus contralateral hemispheric cerebrospinal fluid (CSF) volume (CSF ratio) in a cohort of 935 patients with hemispheric stroke with follow-up computed tomography scans taken a median of 26 h (interquartile range 24-31) after stroke onset. We determined diagnostic thresholds based on comparison to those without any visible edema. We modeled baseline clinical and radiographic variables against each edema biomarker and assessed how each biomarker was associated with stroke outcome (modified Rankin Scale at 90 days).

RESULTS

The displacement of CSF and CSF ratio were correlated with midline shift (r = 0.52 and - 0.74, p < 0.0001) but exhibited broader ranges. A ΔCSF of greater than 14% or a CSF ratio below 0.90 identified those with visible edema: more than half of the patients with stroke met these criteria, compared with only 14% who had midline shift at 24 h. Predictors of edema across all biomarkers included a higher National Institutes of Health Stroke Scale score, a lower Alberta Stroke Program Early CT score, and lower baseline CSF volume. A history of hypertension and diabetes (but not acute hyperglycemia) predicted greater ΔCSF but not midline shift. Both ΔCSF and a lower CSF ratio were associated with worse outcome, adjusting for age, National Institutes of Health Stroke Scale score, and Alberta Stroke Program Early CT score (odds ratio 1.7, 95% confidence interval 1.3-2.2 per 21% ΔCSF).

CONCLUSIONS

Cerebral edema can be measured in a majority of patients with stroke on follow-up computed tomography using volumetric biomarkers evaluating CSF shifts, including in many without visible midline shift. Edema formation is influenced by clinical and radiographic stroke severity but also by chronic vascular risk factors and contributes to worse stroke outcomes.

On Net Water Uptake in Posttraumatic Ischemia Foci

BACKGROUND

The influence of cerebral edema and resultant secondary complications on the clinical outcome of traumatic brain injury (TBI) is well known. Clinical studies of brain water homeostasis dynamics in TBI are limited, which determines the relevance of our work. The purpose is to study changes in brain water homeostasis after TBI of varying severity compared to corresponding cerebral microcirculation parameters.

MATERIALS

This non-randomized retrospective single-center study complies with the Helsinki Declaration for patient's studies. The study included 128 patients with posttraumatic ischemia (PCI) after moderate-to-severe TBI in the middle cerebral artery territory who were admitted to the hospital between July 2015 and February 2022. PCI was evaluated by perfusion computed tomography (CT), and brain edema was determined using net water uptake (NWU) on baseline CT images. The patients were allocated according to Marshall's classification. Multivariate linear regression models were performed to analyze data.

RESULTS

NWU in PCI areas were significantly higher than in patients with its absence (8.1% vs. 4.2%, accordingly; p < 0.001). In the multivariable regression analysis, the mean transit time increase was significantly and independently associated with higher NWU (R2 = 0.089, p < 0.01). In the PCI zone, cerebral blood flow, cerebral blood volume, and time to peak were not significantly associated with NWU values (p > 0.05). No significant differences were observed between the NWU values in PCI foci in different Marshall groups (p = 0.308).

CONCLUSION

Marshall's classification does not predict the progression of posttraumatic ischemia. The blood passage delays through the cerebral microvascular bed is associated with brain tissue water content increase in the PCI focus.

Automated Measurement of Net Water Uptake From Baseline and Follow-Up CTs in Patients With Large Vessel Occlusion Stroke

Quantifying the extent and evolution of cerebral edema developing after stroke is an important but challenging goal. Lesional net water uptake (NWU) is a promising CT-based biomarker of edema, but its measurement requires manually delineating infarcted tissue and mirrored regions in the contralateral hemisphere. We implement an imaging pipeline capable of automatically segmenting the infarct region and calculating NWU from both baseline and follow-up CTs of large-vessel occlusion (LVO) patients. Infarct core is extracted from CT perfusion images using a deconvolution algorithm while infarcts on follow-up CTs were segmented from non-contrast CT (NCCT) using a deep-learning algorithm. These infarct masks were flipped along the brain midline to generate mirrored regions in the contralateral hemisphere of NCCT; NWU was calculated as one minus the ratio of densities between regions, removing voxels segmented as CSF and with HU outside thresholds of 20-80 (normal hemisphere and baseline CT) and 0-40 (infarct region on follow-up). Automated results were compared with those obtained using manually-drawn infarcts and an ASPECTS region-of-interest based method that samples densities within the infarct and normal hemisphere, using intraclass correlation coefficient (ρ). This was tested on serial CTs from 55 patients with anterior circulation LVO (including 66 follow-up CTs). Baseline NWU using automated core was 4.3% (IQR 2.6-7.3) and correlated with manual measurement (ρ = 0.80, p < 0.0001) and ASPECTS (r = -0.60, p = 0.0001). Automatically segmented infarct volumes (median 110-ml) correlated to manually-drawn volumes (ρ = 0.96, p < 0.0001) with median Dice similarity coefficient of 0.83 (IQR 0.72-0.90). Automated NWU was 24.6% (IQR 20-27) and highly correlated to NWU from manually-drawn infarcts (ρ = 0.98) and the sampling-based method (ρ = 0.68, both p < 0.0001). We conclude that this automated imaging pipeline is able to accurately quantify region of infarction and NWU from serial CTs and could be leveraged to study the evolution and impact of edema in large cohorts of stroke patients.

Quantifying Infarct Growth and Secondary Injury Volumes: Comparing Multimodal Image Registration Measures

BACKGROUND AND PURPOSE

Lesion expansion in the week after acute stroke involves both infarct growth (IG) and anatomic distortion (AD) because of edema and hemorrhage. Enabling separate quantification would allow clinical trials targeting these distinct pathological processes. We developed an objective and automated approach to quantify these processes at 24 hours and 1 week.

METHODS

Patients with acute ischemic stroke were scanned at presentation, 24 hours, and 1 week in a magnetic resonance imaging (MRI) cohort study. IG and AD were calculated from follow-up lesion masks after linear and nonlinear registration to a presenting MRI scan. Performance of IG and AD was compared with edema quantified using cerebrospinal fluid displacement. The use of alternative reference images to define AD, including template MRI, mirrored MRI, and presenting computed tomographic scan, was explored.

RESULTS

Thirty-seven patients with nonlacunar stroke were included. AD was responsible for 20% and 36% of lesion expansion at 24 hours (n=30) and 1 week (n=28). Registration-defined IG and AD compared favorably with edema quantified using cerebrospinal fluid displacement, particularly at smaller infarct volumes. Presenting computed tomographic imaging was the preferred alternative reference image to presenting MRI for measuring AD.

CONCLUSIONS

The contributions of IG and AD to lesion expansion can be measured separately over time through the use of image registration. This approach can be used to combine imaging outcome data from computed tomography and MRI.