Evidence map›Paper›PMID 42087035›Full record

ArticleNeurocritical care2026

Integrating Brain Imaging Volumetrics and Quantitative Pupillometry for Predicting Neurologic Deterioration after Large Hemispheric Stroke.

Yili Du, Leigh Ann Mallinger, Allyson L Reinert, Stefanos Chatzidakis, Nawal J Ibrahim, Gabriella Wirth, Atul Kumar, Amrit Avula, Huimin Cheng, David M Greer and 2 more

Abstract read
In one paragraph

Article in Neurocritical care, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Yili DuDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
Leigh Ann MallingerDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
Allyson L ReinertDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
Stefanos ChatzidakisDepartment of Neurology, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02115, USA.
Nawal J IbrahimDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave., Boston, MA, 02118, USA.
Gabriella WirthDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
Atul KumarDepartment of Neurology, Washington University School of Medicine, 660 S Euclid Avenue, Box 8111, St. Louis, MO, 63110, USA.
Amrit AvulaDepartment of Neurology, Washington University School of Medicine, 660 S Euclid Avenue, Box 8111, St. Louis, MO, 63110, USA.
Huimin ChengDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave., Boston, MA, 02118, USA.
David M GreerDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA.
Rajat DharDepartment of Neurology, Washington University School of Medicine, 660 S Euclid Avenue, Box 8111, St. Louis, MO, 63110, USA.
Charlene J OngDepartment of Neurology, Boston Medical Center, 1 Boston Medical Center PI, Boston, MA, 02118, USA. cjong@bu.edu.ORCID http://orcid.org/0000-0003-2377-3025

Funding

An Imaging Repository for the Cerebrovascular Disease Knowledge Portal (iCDKP)U24NS132940 · NINDS · BROAD INSTITUTE, INC. · PI Daniel Scott Marcus, JONATHAN ROSAND · 2023 to 2026
$2.9M
Dynamic Risk Prediction of Life-Threatening Mass Effect After Ischemic StrokeK23NS116033 · NINDS · BOSTON MEDICAL CENTER · PI ONG, CHARLENE J · 2021 to 2025
$1.0M
American Heart Association 23CDA1041762NINDS NIH HHS K23 NS116033NINDS NIH HHS K23NS116033NINDS NIH HHS R01NS1121218NINDS NIH HHS U24 NS132940NINDS NIH HHS U24NS132940
6 · The paper itself

Abstract

backgroundCerebral 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.

methodsWe 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.

resultsA 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%; χ

conclusionsPupillometry and imaging-derived CSF volumetrics are temporally aligned biomarkers that improve prediction of neurologic deterioration, supporting their complementary roles in monitoring cerebral edema.

Indexed as

Brain EdemaInfarction, Middle Cerebral ArteryIschemic StrokePupilAgedAged, 80 and overDisease ProgressionFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesTomography, X-Ray ComputedBiomarkersCerebral edemaCerebrospinal fluidPrognosisPupilStroke

Identifiers

PMID42087035
PMCPMC13151991

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.