Dataset Information

Cerebrospinal fluid volume improves prediction of malignant edema after endovascular treatment of stroke.

ABSTRACT:

Background

The ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) has been identified as a potential predictor of malignant edema formation in patients with acute ischemic stroke.

Aims

We aimed to evaluate the added value of the CSF/ICV ratio in a model to predict malignant edema formation in patients who underwent endovascular treatment.

Methods

We included patients from the MR CLEAN Registry, a prospective national multicenter registry of patients who were treated with endovascular treatment between 2014 and 2017 because of acute ischemic stroke caused by large vessel occlusion. The CSF/ICV ratio was automatically measured on baseline thin-slice noncontrast CT. The primary outcome was the occurrence of malignant edema based on clinical and imaging features. The basic model included the following predictors: age, National Institutes of Health Stroke Scale, Alberta Stroke Program Early CT score, occlusion of the internal carotid artery, collateral score, time between symptom onset and groin puncture, and unsuccessful reperfusion. The extended model included the basic model and the CSF/ICV ratio. The performance of the basic and the extended model was compared with the likelihood ratio test.

Results

Malignant edema occurred in 40 (6%) of 683 patients. In the extended model, a lower CSF/ICV ratio was associated with the occurrence of malignant edema (odds ratio (OR) per percentage point, 1.2; 95% confidence interval (CI) 1.1-1.3, p < 0.001). Age lost predictive value for malignant edema in the extended model (OR 1.1; 95% CI 0.9-1.5, p = 0.372). The performance of the extended model was higher than that of the basic model (p < 0.001).

Conclusions

Adding the CSF/ICV ratio improves a multimodal prediction model for the occurrence of malignant edema after endovascular treatment.

SUBMITTER: Kauw F

PROVIDER: S-EPMC9896253 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Cerebrospinal fluid volume improves prediction of malignant edema after endovascular treatment of stroke.

Kauw Frans F Bernsen Marie Louise E MLE Dankbaar Jan W JW de Jong Hugo Wam HW Kappelle L Jaap LJ Velthuis Birgitta K BK van der Worp H Bart HB van der Lugt Aad A Roos Yvo Bwem YB Yo Lonneke Sf LS van Walderveen Marianne Aa MA Hofmeijer Jeannette J Bennink Edwin E

International journal of stroke : official journal of the International Stroke Society 20220512 2

<h4>Background</h4>The ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) has been identified as a potential predictor of malignant edema formation in patients with acute ischemic stroke.<h4>Aims</h4>We aimed to evaluate the added value of the CSF/ICV ratio in a model to predict malignant edema formation in patients who underwent endovascular treatment.<h4>Methods</h4>We included patients from the MR CLEAN Registry, a prospective national multicenter registry of ...[more]

PMID: 35373655

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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.

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:ObjectiveTo investigate the effect of endovascular treatment on cognitive function as a prespecified secondary analysis of the REVASCAT (Endovascular Revascularization With Solitaire Device Versus Best Medical Therapy in Anterior Circulation Stroke Within 8 Hours) trial.MethodsREVASCAT randomized 206 patients with anterior circulation proximal arterial occlusion stroke to Solitaire thrombectomy or best medical treatment alone. Patients with established dementia were excluded from enrollment. Cognitive function was assessed in person with Trail Making Test (TMT) Parts A and B at 3 months and 1 year after randomization by an investigator masked to treatment allocation. Test completion within 5 minutes, time of completion (seconds), and number of errors were recorded.ResultsFrom November 2012 to December 2014, 206 patients were enrolled in REVASCAT. TMT was assessed in 82 of 84 patients undergoing thrombectomy and 86 of 87 control patients alive at 3 months and in 71 of 79 patients undergoing thrombectomy and 72 of 78 control patients alive at 1 year. Rates of timely TMT-A completion were similar in both treatment arms, although patients undergoing thrombectomy required less time for TMT-A completion and had higher rates of error-free TMT-A performance. Thrombectomy was also associated with a higher probability of timely TMT-B completion (adjusted odds ratio 3.17, 95% confidence interval 1.51-6.66 at 3 months; and adjusted ratio 3.66, 95% confidence interval 1.60-8.35 at 1 year) and shorter time for TMT-B completion. Differences in TMT completion times between treatment arms were significant in patients with good functional outcome but not in those who were functionally dependent (modified Rankin Scale score >2). Poorer cognitive outcomes were significantly associated with larger infarct volume, higher modified Rankin Scale scores, and worse quality of life.ConclusionsThrombectomy improves TMT performance after stroke, especially among patients who reach good functional recovery.Clinicaltrialsgov identifierNCT01692379.Classification of evidenceThis study provides Class I evidence that for patients with stroke from acute anterior circulation proximal arterial occlusion, thrombectomy improves performance on the TMT at 3 months.

Project description:BackgroundMalignant cerebral edema is a devastating complication of stroke, resulting in deterioration and death if hemicraniectomy is not performed prior to herniation. Current approaches for predicting this relatively rare complication often require advanced imaging and still suffer from suboptimal performance. We performed a pilot study to evaluate whether neural networks incorporating data extracted from routine computed tomography (CT) imaging could enhance prediction of edema in a large diverse stroke cohort.MethodsAn automated imaging pipeline retrospectively extracted volumetric data, including cerebrospinal fluid (CSF) volumes and the hemispheric CSF volume ratio, from baseline and 24 h CT scans performed in participants of an international stroke cohort study. Fully connected and long short-term memory (LSTM) neural networks were trained using serial clinical and imaging data to predict those who would require hemicraniectomy or die with midline shift. The performance of these models was tested, in comparison with regression models and the Enhanced Detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score, using cross-validation to construct precision-recall curves.ResultsTwenty of 598 patients developed malignant edema (12 required surgery, 8 died). The regression model provided 95% recall but only 32% precision (area under the precision-recall curve [AUPRC] 0.74), similar to the EDEMA score (precision 28%, AUPRC 0.66). The fully connected network did not perform better (precision 33%, AUPRC 0.71), but the LSTM model provided 100% recall and 87% precision (AUPRC 0.97) in the overall cohort and the subgroup with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 (p = 0.0001 vs. regression and fully connected models). Features providing the most predictive importance were the hemispheric CSF ratio and NIHSS score measured at 24 h.ConclusionsAn LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients for surgery prior to deterioration.

Dataset Information

Cerebrospinal fluid volume improves prediction of malignant edema after endovascular treatment of stroke.

Background

Aims

Methods

Results

Conclusions

Publications

Cerebrospinal fluid volume improves prediction of malignant edema after endovascular treatment of stroke.

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