Neuroimaging Markers of Brain Reserve and Associations with Delirium in Patients with Intracerebral Hemorrhage

Nathaniel B Rex; Carlin C Chuck; Hari G Dandapani; Helen Y Zhou; Thomas Y Yi; Scott A Collins; Harrison X Bai; Ani Eloyan; Richard N Jones; Jerrold L Boxerman; Timothy D Girard; Olga Boukrina; Michael E Reznik

doi:10.1007/s12028-024-02148-2

Neuroimaging Markers of Brain Reserve and Associations with Delirium in Patients with Intracerebral Hemorrhage

Neurocrit Care. 2024 Nov 19. doi: 10.1007/s12028-024-02148-2. Online ahead of print.

Authors

Affiliations

¹ Department of Neurology, Alpert Medical School, Brown University, Providence, RI, USA.
² Department of Diagnostic Imaging, Alpert Medical School, Brown University, Providence, RI, USA.
³ Department of Biostatistics, Brown University, Providence, RI, USA.
⁴ Department of Psychiatry, Alpert Medical School, Brown University, Providence, RI, USA.
⁵ Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA.
⁶ Kessler Institute for Rehabilitation, West Orange, NJ, USA.
⁷ Department of Neurology, Alpert Medical School, Brown University, Providence, RI, USA. michael.reznik@pitt.edu.

PMID: 39562387
DOI: 10.1007/s12028-024-02148-2

Abstract

Background: Delirium occurs frequently in patients with stroke, but the role of preexisting neural substrates in delirium pathogenesis remains unclear. We sought to explore associations between acute and chronic neural substrates of delirium in patients with intracerebral hemorrhage (ICH).

Methods: Using data from a single-center ICH registry, we identified consecutive patients with acute nontraumatic ICH and available magnetic resonance imaging scans. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria were used to classify each patient as delirious or nondelirious during their hospitalization. Magnetic resonance imaging scans were processed and analyzed using semiautomated software, with volumetric measurement of acute ICH volume as well as white matter hyperintensity volume (WMHV) and gray and white matter volumes from the contralateral hemisphere. We tested associations between WMHV and incident delirium using multivariable regression models, and then determined the predictive accuracy of these neuroimaging models via area under the curve (AUC) analysis.

Results: Of 139 patients in our cohort (mean [standard deviation] age 67.3 [17.3] years, 53% male), 58 (42%) patients experienced delirium. In our primary analyses, WMHV was significantly associated with delirium after adjusting for ICH features (odds ratio 1.56 per 10 cm³, 95% confidence interval 1.13-2.13), and this association was strengthened after further adjustment for segmented brain volume in patients with high-resolution scans (odds ratio 1.89 per 10 cm³, 95% confidence interval 1.24-2.86). Neuroimaging-based models predicted delirium with high accuracy (AUC 0.81), especially in patients with Glasgow Coma Scale score > 13 (AUC 0.85) and smaller ICH (AUC 0.91).

Conclusions: Chronic white matter disease is independently associated with delirium in patients with acute ICH, and neuroimaging biomarkers may have utility in predicting delirium occurrence.

Keywords: Delirium; ICH; Neuroimaging; Stroke.