Huiberdina L. Koek

Disruption of cerebral networks and cognitive impairment in Alzheimer disease.

Objective: To examine the relation between measures of whole-brain white matter connectivity and cognitive performance in patients with early Alzheimer disease (AD) using a network-based approach and to assess whether network parameters provide information that is complementary to conventional MRI markers of AD. Methods: Fifty patients (mean age 78.8 ± 7.1 years) with early AD were recruited via a memory clinic. In addition, 15 age-, sex-, and education-matched control participants were used as a reference group. All participants underwent a 3-T MRI scan and cognitive assessment. Diffusion tensor imaging–based tractography was used to reconstruct the brain network of each individual, followed by graph theoretical analyses. Overall network efficiency was assessed by measures of local (clustering coefficient, local efficiency) and global (path length, global efficiency) connectivity. Age-, sex-, and education-adjusted cognitive scores were related to network measures and to conventional MRI parameters (i.e., degree of cerebral atrophy and small-vessel disease). Results: The structural brain network of patients showed reduced local efficiency compared to controls. Within the patient group, worse performance in memory and executive functioning was related to decreased local efficiency (r = 0.434; p = 0.002), increased path length (r = −0.538; p < 0.001), and decreased global efficiency (r = 0.431; p = 0.005). Measures of network efficiency explained up to 27% of the variance in cognitive functioning on top of conventional MRI markers (p < 0.01). Conclusion: This study shows that network-based analysis of brain white matter connections provides a novel way to reveal the structural basis of cognitive dysfunction in AD.

Improved sensitivity to cerebral white matter abnormalities in Alzheimer's disease with spherical deconvolution based tractography.

Diffusion tensor imaging (DTI) based fiber tractography (FT) is the most popular approach for investigating white matter tracts in vivo, despite its inability to reconstruct fiber pathways in regions with “crossing fibers.” Recently, constrained spherical deconvolution (CSD) has been developed to mitigate the adverse effects of “crossing fibers” on DTI based FT. Notwithstanding the methodological benefit, the clinical relevance of CSD based FT for the assessment of white matter abnormalities remains unclear. In this work, we evaluated the applicability of a hybrid framework, in which CSD based FT is combined with conventional DTI metrics to assess white matter abnormalities in 25 patients with early Alzheimer’s disease. Both CSD and DTI based FT were used to reconstruct two white matter tracts: one with regions of “crossing fibers,” i.e., the superior longitudinal fasciculus (SLF) and one which contains only one fiber orientation, i.e. the midsagittal section of the corpus callosum (CC). The DTI metrics, fractional anisotropy (FA) and mean diffusivity (MD), obtained from these tracts were related to memory function. Our results show that in the tract with “crossing fibers” the relation between FA/MD and memory was stronger with CSD than with DTI based FT. By contrast, in the fiber bundle where one fiber population predominates, the relation between FA/MD and memory was comparable between both tractography methods. Importantly, these associations were most pronounced after adjustment for the planar diffusion coefficient, a measure reflecting the degree of fiber organization complexity. These findings indicate that compared to conventionally applied DTI based FT, CSD based FT combined with DTI metrics can increase the sensitivity to detect functionally significant white matter abnormalities in tracts with complex white matter architecture.

Psychotropic medications, including short acting benzodiazepines, strongly increase the frequency of falls in elderly

OBJECTIVES Falls in the elderly are common and often serious. The aim of this study was to examine the association between the use of different classes of psychotropic medications, especially short acting benzodiazepines, and the frequency of falling in elderly. Study design This retrospective cohort study was performed with patients who visited the day clinic of the department of geriatric medicine of the University Medical Center Utrecht in the Netherlands between 1 January 2011 and 1 April 2012. Measurements Frequencies of falling in the past year and medication use were recorded. Logistic regression analysis was performed to assess the relationship between the frequency of falling in the past year and the use of psychotropic medications. RESULTS During this period 404 patients were included and 238 (58.9%) of them had experienced one or more falls in the past year. After multivariate adjustment, frequent falls remained significantly associated with exposure to psychotropic medications (odds ratio [OR] 1.96; 95% confidence interval [CI] 1.17-3.28), antipsychotics (OR 3.62; 95% CI 1.27-10.33), hypnotics and anxiolytics (OR 1.81; 95% CI 1.05-3.11), short-acting benzodiazepines or Z-drugs (OR 1.94; 95% CI 1.10-3.42) and antidepressants (OR 2.35; 95% CI 1.33-4.16). CONCLUSIONS This study confirms that taking psychotropic medication, including short-acting benzodiazepines, strongly increases the frequency of falls in elderly. This relation should be explicitly recognized by doctors prescribing for older people, and by older people themselves. If possible such medication should be avoided for elderly patients especially with other risk factors for falling.

High Prevalence of Cerebral Microbleeds at 7Tesla MRI in Patients with Early Alzheimer's Disease

The prevalence of microbleeds on magnetic resonance imaging (MRI) in patients with Alzheimers disease (AD) is lower than that of its presumed pathological correlate, cerebral amyloid angiopathy. We examined 18 patients with early AD or mild cognitive impairment (MCI) and 18 non-demented controls with ultra-high field strength 7Tesla MRI, to assess if the actual prevalence of microbleeds could be higher than is currently reported. One or more microbleeds were visualized in 78% of the MCI/AD patients and in 44% of the controls (p = 0.04). 7Tesla MRI shows that presence of microbleeds may be the rule, rather than exception in patients with MCI/AD.

A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms

To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.

The influence of vascular risk factors on cognitive decline in patients with dementia: A systematic review

BACKGROUND AND OBJECTIVE Vascular risk factors (VRF) are associated with a higher incidence of dementia. However, the relationship with disease progression is unclear. This review examined the association of VRF (hypertension, hypercholesterolemia, diabetes mellitus, overweight, smoking or multiple VRF) and cognitive decline in patients suffering from dementia. METHODS Literature was searched in four databases (Pubmed, Embase, Cochrane, PsychInfo) and 1779 articles were identified. This resulted in a total of 20 articles which were included. RESULTS Twelve studies on hypertension (HT) were inconsistent about the association with cognitive decline. For hypercholesterolemia (HC) 2 (out of 7) studies were associated with increased cognitive decline, as were both (2/2) studies which researched LDL-cholesterol. Articles were inconclusive about the effect of diabetes mellitus (DM): five (out of 13) found less cognitive decline, 2 found more cognitive decline, and 6 found no significant effect of DM. Overweight (BMI>25 kg/m(2)) was associated in 2/4 studies with a slower rate of cognitive decline, while the other 2 studies found no effect. All studies (5/5) that researched smoking did not find a significant effect. Four studies (out of 7) that looked at multiple VRF found faster cognitive decline, and 3/7 found no effect. DISCUSSION The results of this review suggest an association between LDL-cholesterol and the progression of dementia, while inconsistent results were found for other VRF. Additional prospective cohort studies and experimental studies should be performed to better understand the causal contribution of VRF on cognitive decline in dementia.

Multiple Microbleeds are Related to Cerebral Network Disruptions in Patients with Early Alzheimer's Disease

BACKGROUND Cerebral microbleeds are a manifestation of small vessel disease and are common in patients with Alzheimers disease (AD). However, their clinical significance in this condition is uncertain. We hypothesized that microbleeds contribute to disturbances of the cerebral network in AD and as such may affect cognition. OBJECTIVE The goal of this study was to examine the relationship between microbleeds and brain networks in patients with amnestic mild cognitive impairment (aMCI) or early AD. METHODS Sixty-seven patients (77.9 ± 7.5 years) with aMCI (n = 29) or early AD (n = 38) underwent cognitive testing and 3Tesla MRI. Microbleeds were rated visually. Diffusion tensor imaging and graph theoretical analysis were used to reconstruct brain networks and to quantify network efficiency for each patient. Network measures were compared between patients without and with ≥1 microbleeds and between patients without or with ≥3 microbleeds. In secondary analyses, cognitive functioning was compared between groups. Analyses were adjusted for age and gender, and additionally for other markers of small vessel disease and atrophy. RESULTS Network measures did not differ between patients with ≥1 microbleed (n = 26) and patients without microbleeds (n = 41). However, patients with ≥3 microbleeds (n = 11) showed significant white matter disruptions, longer path length, and less global efficiency than patients without microbleeds, independent of other markers of small vessel disease and atrophy. Cognitive functioning did not differ between patients without microbleeds and patients with ≥1 or ≥3 microbleeds. CONCLUSION Multiple microbleeds are related to structural network disruption in patients with early AD, but their direct impact on cognitive functioning appears to be limited.

The association of chronic kidney disease with brain lesions on MRI or CT: A systematic review

BACKGROUND AND PURPOSE This review reports on the association between chronic kidney disease (CKD) established with glomerular filtration rate (GFR) and brain lesions established with MRI or CT. METHODS Literature was searched combining synonyms of kidney function, brain lesions and terms for the definitions thereof, and MRI or CT. This resulted in 1507 articles, of which 20 were finally included. RESULTS Cross-sectional studies found an association between GFR and white matter lesions (WML) with 7 out of 11 associations significant (odds ratios (OR) GFR, continuous variable: 0.84-0.89 per 10 ml/min/1.73 m(2)). Most significant results were found in studies including subjects from the general population. GFR was associated with silent cerebral infarcts (SCI) with 9 out of 12 associations significant (OR GFR, continuous variable: 0.96-0.99 per ml/min/1.73 m(2)). Brain atrophy was reported significant 4 out of 5 associations (OR GFR, continuous variable: 0.64 per 10 ml/min/1.73 m(2)). Additionally, 2 follow up studies were included. One established that serum creatinine at baseline is a significant predictor of the presence of SCI; the other that the presence of SCI at baseline is a significant predictor of a decrease in GFR. CONCLUSION The results from this review show that CKD is associated with brain lesions. These brain lesions include WML, SCI and brain atrophy. This finding is of clinical importance because these brain lesions are predictive of stroke, cognitive decline and dementia. Additional follow up studies should be performed to better understand the causative pathway and to establish whether screening and preventive programs are beneficial.

Delirium Detection Using EEG: What and How to Measure

BACKGROUND Despite its frequency and impact, delirium is poorly recognized in postoperative and critically ill patients. EEG is highly sensitive to delirium but, as currently used, it is not diagnostic. To develop an EEG-based tool for delirium detection with a limited number of electrodes, we determined the optimal electrode derivation and EEG characteristic to discriminate delirium from nondelirium. METHODS Standard EEGs were recorded in 28 patients with delirium and 28 age- and sex-matched patients who had undergone cardiothoracic surgery and were not delirious, as classified by experts using Diagnostic and Statistical Manual of Mental Disorders, 4th edition, criteria. The first minute of artifact-free EEG data with eyes closed as well as with eyes open was selected. For each derivation, six EEG parameters were evaluated. Using Mann-Whitney U tests, all combinations of derivations and parameters were compared between patients with delirium and those without. Corresponding P values, corrected for multiple testing, were ranked. RESULTS The largest difference between patients with and without delirium and highest area under the receiver operating curve (0.99; 95% CI, 0.97-1.00) was found during the eyes-closed periods of the EEG, using electrode derivation F8-Pz (frontal-parietal) and relative δ power (median [interquartile range (IQR)] for delirium, 0.59 [IQR, 0.47-0.71] and for nondelirium, 0.20 [IQR, 0.17-0.26]; P = .0000000000018). With a cutoff value of 0.37, it resulted in a sensitivity of 100% (95% CI, 100%-100%) and specificity of 96% (95% CI, 88%-100%). CONCLUSIONS In a homogenous population of nonsedated patients who had undergone cardiothoracic surgery, we observed that relative δ power from an eyes-closed EEG recording with only two electrodes in a frontal-parietal derivation can distinguish among patients who have delirium and those who do not.

Decreased Functional Connectivity and Disturbed Directionality of Information Flow in the Electroencephalography of Intensive Care Unit Patients with Delirium after Cardiac Surgery

Background:In this article, the authors explore functional connectivity and network topology in electroencephalography recordings of patients with delirium after cardiac surgery, aiming to improve the understanding of the pathophysiology and phenomenology of delirium. The authors hypothesize that disturbances in attention and consciousness in delirium may be related to alterations in functional neural interactions. Methods:Electroencephalography recordings were obtained in postcardiac surgery patients with delirium (N = 25) and without delirium (N = 24). The authors analyzed unbiased functional connectivity of electroencephalography time series using the phase lag index, directed phase lag index, and functional brain network topology using graph analysis. Results:The mean phase lag index was lower in the &agr; band (8 to 13 Hz) in patients with delirium (median, 0.120; interquartile range, 0.113 to 0.138) than in patients without delirium (median, 0.140; interquartile range, 0.129 to 0.168; P < 0.01). Network topology in delirium patients was characterized by lower normalized weighted shortest path lengths in the &agr; band (t = −2.65; P = 0.01). &dgr; Band–directed phase lag index was lower in anterior regions and higher in central regions in delirium patients than in nondelirium patients (F = 4.53; P = 0.04, and F = 7.65; P < 0.01, respectively). Conclusions:Loss of &agr; band functional connectivity, decreased path length, and increased &dgr; band connectivity directed to frontal regions characterize the electroencephalography during delirium after cardiac surgery. These findings may explain why information processing is disturbed in delirium.