Predicting malignant middle cerebral artery (MCA) infarction can help to identify patients who may benefit from preventive decompressive surgery. We aimed to investigate the association between the ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) and malignant MCA infarction.

Patients with an occlusion proximal to the M3 segment of the MCA were selected from the DUST (Dutch Acute Stroke Study). Admission imaging included noncontrast computed tomography (CT), CT perfusion, and CT angiography. Patient characteristics and CT findings were collected. The ratio of intracranial CSF volume to ICV (CSF/ICV) was quantified on admission thin-slice noncontrast CT. Malignant MCA infarction was defined as a midline shift of >5 mm on follow-up noncontrast CT, which was performed 3 days after the stroke or in case of clinical deterioration. To test the association between CSF/ICV and malignant MCA infarction, odds ratios and 95% CIs were calculated for 3 multivariable models by using binary logistic regression. Model performances were compared by using the likelihood ratio test.

Of the 286 included patients, 35 (12%) developed malignant MCA infarction. CSF/ICV was independently associated with malignant MCA infarction in 3 multivariable models: (1) with age and admission National Institutes of Health Stroke Scale (odds ratio, 3.3; 95% CI, 1.1–11.1), (2) with admission National Institutes of Health Stroke Scale and poor collateral score (odds ratio, 7.0; 95% CI, 2.6–21.3), and (3) with terminal internal carotid artery or proximal M1 occlusion and poor collateral score (odds ratio, 7.7; 95% CI, 2.8–23.9). The performance of model 1 (areas under the receiver operating characteristic curves, 0.795 versus 0.824; P=0.033), model 2 (areas under the receiver operating characteristic curves, 0.813 versus 0.850; P<0.001), and model 3 (areas under the receiver operating characteristic curves, 0.811 versus 0.856; P<0.001) improved significantly after adding CSF/ICV.

The CSF/ICV ratio is associated with malignant MCA infarction and has added value to clinical and imaging prediction models in limited numbers of patients.