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Validating imaging biomarkers of cerebral edema in patients with severe ischemic stroke.

ABSTRACT: There is no validated neuroimaging marker for quantifying brain edema. We sought to test whether magnetic resonance imaging (MRI)-based metrics would reliably change during the early subacute period in a manner consistent with edema and whether they would correlate with relevant clinical endpoints.Serial MRI studies from patients in the Echoplanar Imaging Thrombolytic Evaluation Trial with initial diffusion-weighted imaging (DWI) lesion volume >82 cm(3) were analyzed. Two independent readers outlined the hemisphere and lateral ventricle on the involved side and calculated respective volumes at baseline and days 3 to 5. We assessed interrater agreement, volume change between scans, and the association of volume change with early neurologic deterioration (National Institutes of Health Stroke Scale score worsening of ? 4 points), a 90-day modified Rankin scale (mRS) score of 0 to 4, and mortality.Of 12 patients who met study criteria, average baseline and follow-up DWI lesion size was 138 cm(3) and 234 cm(3), respectively. The mean time to follow-up MRI was 62 hours. Concordance correlation coefficients between readers were >0.90 for both hemisphere and ventricle volume assessment. Mean percent hemisphere volume increase was 16.2 ± 8.3% (P < .0001), and the mean percent ventricle volume decrease was 45.6 ± 16.9% (P < .001). Percent hemisphere growth predicted early neurologic deterioration (area under the curve [AUC] 0.92; P = .0005) and 90-day mRS 0 to 4 (AUC 0.80; P = .02).In this exploratory analysis of severe ischemic stroke patients, statistically significant changes in hemisphere and ventricular volumes within the first week are consistent with expected changes of cerebral edema. MRI-based analysis of hemisphere growth appears to be a suitable biomarker for edema formation.

SUBMITTER: Yoo AJ

PROVIDER: S-EPMC3529850 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Validating imaging biomarkers of cerebral edema in patients with severe ischemic stroke.

Yoo Albert J AJ Sheth Kevin N KN Kimberly W Taylor WT Chaudhry Zeshan A ZA Elm Jordan J JJ Jacobson Sven S Davis Stephen M SM Donnan Geoffrey A GA Albers Gregory W GW Stern Barney J BJ González R Gilberto RG

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 20120209 6

<h4>Background</h4>There is no validated neuroimaging marker for quantifying brain edema. We sought to test whether magnetic resonance imaging (MRI)-based metrics would reliably change during the early subacute period in a manner consistent with edema and whether they would correlate with relevant clinical endpoints.<h4>Methods</h4>Serial MRI studies from patients in the Echoplanar Imaging Thrombolytic Evaluation Trial with initial diffusion-weighted imaging (DWI) lesion volume >82 cm(3) were an ...[more]

PMID: 22325573

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Project description:IntroductionMalignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-h. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema.MethodsWe identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-h clinical and CT imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-h data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC).ResultsTwenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66).ConclusionIncorporating quantitative CT-based imaging features from baseline and 24-h CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine-learning models are required.

Project description:Background and Purpose- Cerebral edema (CED) develops in the hours to days after stroke; the resulting increase in brain volume may lead to midline shift (MLS) and neurological deterioration. The time course and implications of edema formation are not well characterized across the spectrum of stroke. We analyzed displacement of cerebrospinal fluid (ΔCSF) as a dynamic quantitative imaging biomarker of edema formation. Methods- We selected subjects enrolled in a stroke cohort study who presented within 6 hours of onset and had baseline and ≥1 follow-up brain computed tomography scans available. We applied a neural network-based algorithm to quantify hemispheric CSF volume at each imaging time point and modeled CSF trajectory over time (using a piecewise linear mixed-effects model). We evaluated ΔCSF within the first 24 hours as an early biomarker of CED (defined as developing MLS on computed tomography beyond 24 hours) and poor outcome (modified Rankin Scale score, 3-6). Results- We had serial imaging in 738 subjects with stroke, of whom 91 (13%) developed CED with MLS. Age did not differ (69 versus 70 years), but baseline National Institutes of Health Stroke Scale was higher (16 versus 7) and baseline CSF volume lower (132 versus 161 mL, both P<0.001) in those with CED. ΔCSF was faster in those developing MLS, with the majority seen by 24 hours (36% versus 11% or 2.4 versus 0.8 mL/h; P<0.0001). Risk of CED almost doubled for every 10% ΔCSF within 24 hours (odds ratio, 1.76 [95% CI, 1.46-2.14]), adjusting for age, glucose, and National Institutes of Health Stroke Scale. Risk of neurological deterioration (1.6-point increase in National Institutes of Health Stroke Scale at 24 hours) and poor outcome (adjusted odds ratio, 1.34 [95% CI, 1.15-1.56]) was also greater for every 10% increase in ΔCSF. Conclusions- CSF volumetrics provides quantitative evaluation of early edema formation. ΔCSF from baseline to 24-hour computed tomography is a promising early biomarker for the development of MLS and worse neurological outcome.

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Validating imaging biomarkers of cerebral edema in patients with severe ischemic stroke.

Publications

Validating imaging biomarkers of cerebral edema in patients with severe ischemic stroke.

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