To determine whether delirium in acute ischemic stroke is localizable to specific neural networks.

Delirium is estimated to occur in one-fourth of patients with acute stroke. Despite its associated morbidity and mortality, prediction and pathophysiological understanding of delirium remains challenging. A recent meta-analysis of patients with delirium and stroke found increased risks of delirium in supratentorial, cortical, and anterior circulation strokes, raising the possibility of an underlying neural network for delirium. 

We performed a retrospective cohort study of patients admitted to a comprehensive stroke center with acute ischemic stroke from January 2016 to April 2019. Patients were assessed for delirium by trained clinical nursing staff using the Confusion Assessment Method (CAM) framework. Acute stroke lesions from MRI diffusion weighted images (DWI) lesions were automatically segmented using a machine learning algorithm. Lesions were registered to a 2mm Montreal Neurological Institute template (MNI-152). We then used lesion network mapping to identify potential unifying brain networks for delirium in patients with acute stroke.

907 scans from unique patients were analyzed. 274 patients had delirium (30.2%), 47.5% were women (431), and the mean age was 69.6 years old. In comparison to a general stroke cohort, patients with delirium had lesions connected to the right and left inferior frontal gyri and left middle temporal gyrus and left temporo-parietal junction (one-sample t-test, family-wise error p<0.05). Sensitivity analysis showed that delirium was not associated with parietal, occipital, brainstem, and cerebellar lesions.