Related Experiment Video
Updated: May 7, 2026
Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
Published on: November 19, 2020
Integrating Brain Imaging Volumetrics and Quantitative Pupillometry for Predicting Neurologic Deterioration after
Yili Du1,2, Leigh Ann Mallinger1, Allyson L Reinert1
1Department of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
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 computed tomography (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 h and within the subsequent 24 h 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:
A total of 71 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 h 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); 32 (46%) of 69 eligible patients experienced neurologic deterioration. Models including CSF volume and pupillometry outperformed those with pupillometry only (AUC 83.2% vs. 79.9%; χ2 = 4.35, p = 0.04).
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.
