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Delirium is associated with long-term cognitive dysfunction and with increased brain atrophy. However, it is unclear whether these problems result from or predisposes to delirium. We aimed to investigate preoperative to postoperative brain changes, as well as the role of delirium in these changes over time. We investigated the effects of surgery and postoperative delirium with brain MRIs made before and 3 months after major elective surgery in 299 elderly patients, and an MRI with a 3 months follow-up MRI in 48 non-surgical control participants. To study the effects of surgery and delirium, we compared brain volumes, white matter hyperintensities and brain infarcts between baseline and follow-up MRIs, using multiple regression analyses adjusting for possible confounders. Within the patients group, 37 persons (12%) developed postoperative delirium. Surgical patients showed a greater decrease in grey matter volume than non-surgical control participants [linear regression: B (95% confidence interval) = -0.65% of intracranial volume (-1.01 to -0.29, P < 0.005)]. Within the surgery group, delirium was associated with a greater decrease in grey matter volume [B (95% confidence interval): -0.44% of intracranial volume (-0.82 to -0.06, P = 0.02)]. Furthermore, within the patients, delirium was associated with a non-significantly increased risk of a new postoperative brain infarct [logistic regression: odds ratio (95% confidence interval): 2.8 (0.7-11.1), P = 0.14]. Our study was the first to investigate the association between delirium and preoperative to postoperative brain volume changes, suggesting that delirium is associated with increased progression of grey matter volume loss.

The underlying structural correlates of predisposition to postoperative delirium remain largely unknown. A combined analysis of preoperative brain magnetic resonance imaging (MRI) markers could improve our understanding of the pathophysiology of delirium. Therefore, we aimed to identify different MRI brain phenotypes in older patients scheduled for major elective surgery, and to assess the relation between these phenotypes and postoperative delirium. Markers of neurodegenerative and neurovascular brain changes were determined from MRI brain scans in older patients (n = 161, mean age 71, standard deviation 5 years), of whom 24 (15%) developed delirium. A hierarchical cluster analysis was performed. We found six distinct groups of patients with different MRI brain phenotypes. Logistic regression analysis showed a higher odds of developing postoperative delirium in individuals with multi-burden pathology (n = 15 (9%), odds ratio (95% confidence interval): 3.8 (1.1–13.0)). In conclusion, these results indicate that different MRI brain phenotypes are related to a different risk of developing delirium after major elective surgery. MRI brain phenotypes could assist in an improved understanding of the structural correlates of predisposition to postoperative delirium.

We determined the occurrence and association of cortical cerebral microinfarcts (CMIs) at 7 T MRI with risk factors, neuroimaging markers of small and large vessel disease, and cognitive functioning. Within the Medea-7T study, a diverse cohort of older persons with normal cognition, patients with vascular disease, and memory clinic patients, we included 386 participants (68 ± 9 years) with available 7 T and 1.5 T/3T brain MRI, and risk factor and neuropsychological data. CMIs were found in 10% of participants and were associated with older age (RR = 1.79 per +10 years, 95%CI 1.28–2.50), history of stroke or TIA (RR = 4.03, 95%CI 2.18–7.43), cortical infarcts (RR = 5.28, 95%CI 2.91–9.55), lacunes (RR = 5.66, 95%CI 2.85–11.27), cerebellar infarcts (RR = 2.73, 95%CI 1.27–5.84) and decreased cerebral blood flow (RR = 1.35 per −100 ml/min, 95%CI 1.00–1.83), after adjustment for age and sex. Furthermore, participants with >2 CMIs had 0.5 SD (95%CI 0.05–0.91) lower global cognitive performance, compared to participants without CMIs. Our results indicate that CMIs on 7 T MRI are observed in vascular and memory clinic patients with similar frequency, and are associated with older age, history of stroke or TIA, other brain infarcts, and poorer global cognitive functioning.

Frailty is a common syndrome in older individuals that is associated with poor cognitive outcome. The underlying brain correlates of frailty are unclear. The aim of this study was to investigate the association between frailty and MRI features of cerebral small vessel disease in a group of non-demented older individuals. We included 170 participants who were classified as frail (n = 30), pre-frail (n = 85) or non-frail (n = 55). The association of frailty and white matter hyperintensity volume and shape features, lacunar infarcts and cerebral perfusion was investigated by regression analyses adjusted for age and sex. Frail and pre-frail participants were older, more often female and showed higher white matter hyperintensity volume (0.69 [95%-CI 0.08 to 1.31], p = 0.03 respectively 0.43 [95%-CI: 0.04 to 0.82], p = 0.03) compared to non-frail participants. Frail participants showed a non-significant trend, and pre-frail participants showed a more complex shape of white matter hyperintensities (concavity index: 0.04 [95%-CI: 0.03 to 0.08], p = 0.03; fractal dimensions: 0.07 [95%-CI: 0.00 to 0.15], p = 0.05) compared to non-frail participants. No between group differences were found in gray matter perfusion or in the presence of lacunar infarcts. In conclusion, increased white matter hyperintensity volume and a more complex white matter hyperintensity shape may be structural brain correlates of the frailty phenotype.

Neurodegenerative and neurovascular diseases lead to heterogeneous brain abnormalities. A combined analysis of these abnormalities by phenotypes of the brain might give a more accurate representation of the underlying aetiology. We aimed to identify different MRI phenotypes of the brain and assessed the risk of future stroke and mortality within these subgroups. In 1003 patients (59 ± 10 years) from the Second Manifestations of ARTerial disease-Magnetic Resonance (SMART-MR) study, different quantitative 1.5T brain MRI markers were used in a hierarchical clustering analysis to identify 11 distinct subgroups with a different distribution in brain MRI markers and cardiovascular risk factors, and a different risk of stroke (Cox regression: from no increased risk compared to the reference group with relatively few brain abnormalities to HR = 10.34; 95% CI 3.80↔28.12 for the multi-burden subgroup) and mortality (from no increased risk compared to the reference group to HR = 4.00; 95% CI 2.50↔6.40 for the multi-burden subgroup). In conclusion, within a group of patients with manifest arterial disease, we showed that different MRI phenotypes of the brain can be identified and that these were associated with different risks of future stroke and mortality. These MRI phenotypes can possibly classify individual patients and assess their risk of future stroke and mortality.

Lacunes and white matter hyperintensities (WMHs) are features of cerebral small vessel disease (CSVD) that are associated with poor functional outcomes. However, how the two are related remains unclear. In this study, we examined the association between lacunes and several WMH features in patients with a history of vascular disease. A total of 999 patients (mean age 59 ± 10 years) with a 1.5 T brain magnetic resonance imaging (MRI) scan were included from the SMART-MR study. Lacunes were scored visually and WMH features (volume, subtype and shape) were automatically determined. Analyses consisted of linear and Poisson regression adjusted for age, sex, and total intracranial volume (ICV). Patients with lacunes (n = 188; 19%) had greater total (B = 1.03, 95% CI: 0.86 to 1.21), periventricular/confluent (B = 1.08, 95% CI: 0.89 to 1.27), and deep (B = 0.71, 95% CI: 0.44 to 0.97) natural log-transformed WMH volumes than patients without lacunes. Patients with lacunes had an increased risk of confluent type WMHs (RR = 2.41, 95% CI: 1.98 to 2.92) and deep WMHs (RR = 1.41, 95% CI: 1.22 to 1.62) and had a more irregular shape of confluent WMHs than patients without lacunes, independent of total WMH volume. In conclusion, we found that lacunes on MRI were associated with WMH features that correspond to more severe small vessel changes, mortality, and poor functional outcomes.