Neural substrates of vulnerability to postsurgical delirium as revealed by presurgical diffusion MRI

Abstract

Despite the significant impact of postoperative delirium on surgical outcomes and the long-term prognosis of older patients, its neural basis has not yet been clarified. In this study we investigated the impact of premorbid brain microstructural integrity, as measured by diffusion tensor imaging before surgery, on postoperative delirium incidence and severity, as well as the relationship among presurgical cognitive performance, diffusion tensor imaging abnormalities and postoperative delirium. Presurgical diffusion tensor imaging scans of 136 older (≥70 years), dementia-free subjects from the prospective Successful Aging after Elective Surgery study were analysed blind to the clinical data and delirium status. Primary outcomes were postoperative delirium incidence and severity during the hospital stay, as assessed by the Confusion Assessment Method. We measured cognition before surgery using general cognitive performance, a composite score based on a battery of neuropsychological tests. We investigated the association between presurgical diffusion tensor imaging parameters of brain microstructural integrity (i.e. fractional anisotropy, axial, mean and radial diffusivity) with postoperative delirium incidence and severity. Analyses were adjusted for the following potential confounders: age, gender, vascular comorbidity status, and general cognitive performance. Postoperative delirium occurred in 29 of 136 subjects (21%) during hospitalization. Presurgical diffusion tensor imaging abnormalities of the cerebellum, cingulum, corpus callosum, internal capsule, thalamus, basal forebrain, occipital, parietal and temporal lobes, including the hippocampus, were associated with delirium incidence and severity, after controlling for age, gender and vascular comorbidities. After further controlling for general cognitive performance, diffusion tensor imaging abnormalities of the cerebellum, hippocampus, thalamus and basal forebrain still remained associated with delirium incidence and severity. This study raises the intriguing possibility that structural dysconnectivity involving interhemispheric and fronto-thalamo-cerebellar networks, as well as microstructural changes of structures involved in limbic and memory functions predispose to delirium under the stress of surgery. While the diffusion tensor imaging abnormalities observed in the corpus callosum, cingulum, and temporal lobe likely constitute the neural substrate for the association between premorbid cognition, as measured by general cognitive performance, and postoperative delirium, the microstructural changes observed in the cerebellum, hippocampus, thalamus and basal forebrain seem to constitute a separate phenomenon that predisposes to postsurgical delirium independent of presurgical cognitive status.

Keywords: cognitive ageing; delirium; neuropsychiatry; structural MRI; temporal lobe.

Postoperative delirium is a risk factor for faster age-related cognitive decline. Cavallari et al. report that MRI-evident microstructural abnormalities of the cerebellum, hippocampus, thalamus and basal forebrain predict delirium incidence and severity independent of pre-surgical cognitive status. The results may improve our understanding of delirium and ultimately guide its clinical management.

Figure 1

Spatial distribution and significance of association between DTI abnormalities and delirium severity, adjusting for age, gender and vascular comorbidity. Areas showing decrease in fractional anisotropy (top) and increase in mean diffusivity (bottom) are overlaid to canonical T₁-weighted images. Colours refer to T-values of significant DTI abnormalities (P < 0.05 after correction for multiple comparison within each cluster, cluster size ≥ 5000) on a scale of 1.5 (red) to 5 (yellow).

Figure 2

Spatial distribution and significance of association between DTI abnormalities and delirium severity, adjusting for age, gender, vascular comorbidity and GCP. Areas showing decrease in fractional anisotropy (top) and increase in mean diffusivity (bottom) are overlaid to canonical T₁-weighted images. Colours refer to T-values of significant DTI abnormalities (P < 0.05 after correction for multiple comparison within each cluster, cluster size ≥ 5000) on a scale of 1.5 (red) to 5 (yellow).

Figure 3

Anatomical detail of the DTI abnormalities of the temporal lobe associated with postoperative delirium. The colour map indicates significant association between regional mean diffusivity (MD) values and delirium severity in the bilateral temporal lobe, including hippocampal head and body, fimbria, and fornix, as well as entorhinal and perirhinal cortices (ERC/PRC). Significant associations are also noted in the subthalamic nucleus (STN) bilaterally and temporal stem white matter as well as dorsomedial thalamus. Colours refer to T-values of significant DTI abnormalities (P < 0.05 after correction for multiple comparison within each cluster, cluster size ≥ 5000; general linear model adjusted for age, gender and vascular comorbidity) on a scale of 1.5 (red) to 5 (yellow).

Figure 4

Detail of the DTI abnormalities of the basal forebrain associated with postoperative delirium. The colour map indicates significant association between regional mean diffusivity (MD) values and delirium severity in the bilateral substantia innominata (SI) and anterior commissure (AC). Colours refer to T-values of significant DTI abnormalities (P < 0.05 after correction for multiple comparison within each cluster, cluster size ≥ 5000; general linear model adjusted for age, gender and vascular comorbidity) on a scale of 1.5 (red) to 5 (yellow).

Figure 5

Spatial distribution and significance of association between DTI abnormalities and GCP, adjusting for age, gender and education. Areas showing decrease in fractional anisotropy (top) and increase in mean diffusivity (bottom) are overlaid to canonical T₁-weighted images. Colours refer to T-values of significant DTI abnormalities (P < 0.05 after correction for multiple comparison within each cluster, cluster size ≥ 5000) on a scale of 1.5 (red) to 5 (yellow).