ArticleResearch square2025
Integrating Brain Imaging Volumetrics and Quantitative Pupillometry for Predicting Neurologic Deterioration after Large Hemispheric Stroke.
Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Cerebral edema is a life-threatening complication of large ischemic stroke. Imaging assessment of global and hemispheric cerebrospinal fluid (CSF) volumetrics quantifies edema progression, while quantitative pupillometry provides real-time bedside assessment of neurologic decline. However, the relationship between the two and their combined value for predicting neurologic deterioration remains unclear. Methods: We conducted a retrospective study of patients with large middle cerebral artery strokes admitted to Boston Medical Center between 2019 and 2024. Eligible patients had ≥1 head CT and ≥3 pupillometry measurements. Total and hemispheric CSF volumes were extracted using an automated image analysis pipeline. Average pupillometry variables, including the Neurological Pupil index (NPi) and dilation velocity, were aligned to imaging within ±1 hour and within the subsequent 24-hours of each image. Associations between pupillometry and CSF volumetrics were evaluated using Spearman's correlations and linear mixed-effects models adjusted for age, sex, and standardized baseline brain volume. Cox proportional hazards models with time-dependent covariates were used to assess the predictive value of CSF and pupillometry markers for time-to-neurologic deterioration. We compared model performance using likelihood ratio tests and time-dependent area under the curve (AUC) metrics. Results: Seventy-one patients (mean age 66 ±16 years; 59% women) with 249 CT images were included. Pupillometry and CSF measures were significantly correlated in the first 48-hours post-stroke. In adjusted models, lower hemispheric CSF volume ratio was associated with lower NPi (β=1.55, p=0.02) and greater NPi difference (β=-1.53, p<0.01). Thirty-two (46%) of 69 eligible patients experienced neurologic deterioration. Models including CSF volume and pupillometry outperformed those with pupillometry only (AUC 83.5% v. 81.0%; χ Conclusions: Pupillometry and imaging-derived CSF volumetrics are temporally aligned biomarkers that improve prediction of neurologic deterioration, supporting their complementary roles in monitoring cerebral edema.
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