Baseline white matter hyperintensities affect the course of cognitive function after small vessel disease-related stroke: a prospective observational study

Cerebral white matter burden is linked to cognitive function in patients undergoing hemodialysis

INTRODUCTION

Chronic kidney disease is related to neurodegeneration and structural changes in the brain which might lead to cognitive decline. The Fazekas scale used for assessing white matter hyperintensities (WMHs) was associated with poor cognitive performance. Therefore, this study investigated the associations between the mini-mental status examination (MMSE), Montreal cognitive assessment (MoCA), cognitive abilities screening instrument (CASI), and Fazekas scale in patients under hemodialysis (HD).

METHODS

The periventricular (PV) WMHs and deep WMHs (DWMHs) in brain magnetic resonance images of 59 patients under dialysis were graded using the Fazekas scale. Three cognition function tests were also performed, then multivariable ordinal regression and logistic regression were used to identify the associations between cognitive performance and the Fazekas scale.

RESULTS

There were inverse associations between the three cognitive function tests across the Fazekas scale of PVWMHs (p = .037, .006, and .008 for MMSE, MoCA, and CASI, respectively), but the associations were attenuated in the DWMHs group. In CASI, significant differences were identified in short-term memory, mental manipulation, abstract thinking, language, spatial construction, and name fluency in the PVWMHs group. However, DWMHs were only significantly correlated with abstract thinking and short-term memory.

CONCLUSION

An inverse correlation existed between the Fazekas scale, predominantly in PVWMHs, and cognition in patients undergoing HD. The PVWMHs were associated with cognitive performance assessed by MMSE, MoCA, and CASI, as well as with subdomains of CASI such as memory, language and name fluency in patients undergoing HD.

Causal relationship between multiparameter brain MRI phenotypes and age: evidence from Mendelian randomization

To explore the causal relationship between age and brain health (cortical atrophy, white matter integrity, white matter hyperintensities and cerebral microbleeds in various brain regions) related multiparameter imaging features using two-sample Mendelian randomization. Age was determined as chronological age of the subject. Cortical volume, white matter micro-integrity, white matter hyperintensity volume and cerebral microbleeds of each brain region were included as phenotypes for brain health. Age and imaging of brain health related genetic data were analysed to determine the causal relationship using inverse-variance weighted model, validated by heterogeneity and horizontal pleiotropy variables. Age is causally related to increased volumes of white matter hyperintensities (β = 0.151). For white matter micro-integrity, fibres of the inferior cerebellar peduncle (axial diffusivity β = -0.128, orientation dispersion index β = 0.173), cerebral peduncle (axial diffusivity β = -0.136), superior fronto-occipital fasciculus (isotropic volume fraction β = 0.163) and fibres within the limbic system were causally deteriorated. We also detected decreased cortical thickness of multiple frontal and temporal regions (P < 0.05). Microbleeds were not related with aging (P > 0.05). Aging is a threat of brain health, leading to cortical atrophy mainly in the frontal lobes, as well as the white matter degeneration especially abnormal hyperintensity and deteriorated white matter integrity around the hippocampus.

Regional white matter hyperintensity volume predicts persistent cognitive impairment in acute lacunar infarct patients

Background

White matter hyperintensity (WMH) is often described in acute lacunar stroke (ALS) patients. However, the specific relationship between regional WMH volume and persistent cognitive impairment remains unclear.

Methods

We enrolled patients with ALS who were hospitalized at the First Affiliated Hospital of Soochow University between January 2020 and November 2022. All patients were assessed for global cognitive function using the Montreal Cognitive Assessment (MoCA) scale at 14 ± 2 days and 6 months after the onset of ALS. Manifestations of chronic cerebral small vessel disease (CSVD) were assessed via MRI scan. The distributions of regional WMH were segmented, and their relationship with cognitive impairment was evaluated.

Results

A total of 129 patients were enrolled. Baseline frontal WMH volume (OR = 1.18, P = 0.04) was an independent risk factor for long-term cognitive impairment after ALS. Furthermore, the presence of WMH at the genu of the corpus callosum (GCC) at baseline (OR = 3.1, P = 0.033) was strongly associated with persistent cognitive decline. Multivariable logistic regression analysis showed that depression (OR = 6.252, P = 0.029), NIHSS score (OR = 1.24, P = 0.011), and albumin at admission (OR = 0.841, P = 0.032) were also important determinants of long-term cognitive impairment after ALS.

Conclusions

Our study found that WMH, especially frontal WMH volume and the presence of WMH at the GCC at baseline, independently contributed to long-term cognitive decline in ALS patients. This study provides new evidence of the clinical relationship between regional WMH volume and cognitive impairment in ALS patients.

Association between lipocalin-2 and mild cognitive impairment or dementia: A systematic review and meta-analysis of population-based evidence

BACKGROUND

The associations between lipocalin-2 (LCN2) with mild cognitive impairment (MCI) and dementia have gained growing interest. However, population-based studies have yielded inconsistent findings. Therefore, we conducted this essential systematic review and meta-analysis to analyze and summarize the existing population-based evidence.

METHODS

PubMed, EMBASE, and Web of Science were systematically searched until Mar 18, 2022. Meta-analysis was performed to generate the standard mean difference (SMD) of peripheral blood and cerebrospinal fluid (CSF) LCN2. A qualitative review was performed to summarize the evidence from postmortem brain tissue studies.

RESULTS

In peripheral blood, the overall pooled results showed no significant difference in LCN2 across Alzheimer's disease (AD), MCI and control groups. Further subgroup analysis revealed higher serum LCN2 levels in AD compared to controls (SMD =1.28 [0.44;2.13], p = 0.003), while the difference remained insignificant in plasma (SMD =0.04 [-0.82;0.90], p = 0.931). Besides, peripheral blood LCN2 were higher in AD when age difference between AD and controls ≥ 4 years (SMD =1.21 [0.37;2.06], p = 0.005). In CSF, no differences were found in LCN2 across groups of AD, MCI and controls. However, CSF LCN2 was higher in vascular dementia (VaD) compared to controls (SMD =1.02 [0.17;1.87], p = 0.018), as well as compared to AD (SMD =1.19 [0.58;1.80], p < 0.001). Qualitative analysis supported that LCN2 was increased in the brain tissue of AD-related areas, especially in astrocytes and microglia; while LCN2 increased in infarct-related brain areas and over-expressed in astrocytes and macrophages in mixed dementia (MD).

CONCLUSION

The difference in peripheral blood LCN2 between AD and controls may be affected by the type of biofluid and age. No differences were found in CSF LCN2 across AD, MCI and controls groups. In contrast, CSF LCN2 was elevated in VaD patients. Moreover, LCN2 was increased in AD-related brain areas and cells in AD, while in infarcts-related brain areas and cells in MD.

Leukoaraiosis as a Predictor of Depression and Cognitive Impairment among Stroke Survivors: A Systematic Review

Stroke survivors are at increased risk of developing depression and cognitive decline. Thus, it is crucial for both clinicians and stroke survivors to be provided with timely and accurate prognostication of post-stroke depression (PSD) and post-stroke dementia (PSDem). Several biomarkers regarding stroke patients' propensity to develop PSD and PSDem have been implemented so far, leukoaraiosis (LA) being among them. The purpose of the present study was to review all available work published within the last decade dealing with pre-existing LA as a predictor of depression (PSD) and cognitive dysfunction (cognitive impairment or PSDem) in stroke patients. A literature search of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of preexisting LA as a prognostic indicator of PSD and PSDem/cognitive impairment. Only full-text articles published in the English language were included. Thirty-four articles were traced and are included in the present review. LA burden, serving as a surrogate marker of "brain frailty" among stroke patients, appears to be able to offer significant information about the possibility of developing PSD or cognitive dysfunction. Determining the extent of pre-existing white matter abnormalities can properly guide decision making in acute stroke settings, as a greater degree of such lesioning is usually coupled with neuropsychiatric aftermaths, such as PSD and PSDem.

Neuroimaging biomarkers of cognitive recovery after ischemic stroke

Post-stroke cognitive impairment affects more than one-third of patients after an ischemic stroke (IS). Identifying markers of potential cognitive recovery after ischemic stroke can guide patients' selection for treatments, enrollment in clinical trials, and cognitive rehabilitation methods to restore cognitive abilities in post-stroke patients. Despite the burden of post-stroke cognitive impairment, biomarkers of cognitive recovery are an understudied area of research. This narrative review summarizes and critically reviews the current literature on the use and utility of neuroimaging as a predictive biomarker of cognitive recovery after IS. Most studies included in this review utilized structural Magnetic Resonance Imaging (MRI) to predict cognitive recovery after IS; these studies highlighted baseline markers of cerebral small vessel disease and cortical atrophy as predictors of cognitive recovery. Functional Magnetic Resonance Imaging (fMRI) using resting-state functional connectivity and Diffusion Imaging are potential biomarkers of cognitive recovery after IS, although more precise predictive tools are needed. Comparison of these studies is limited by heterogeneity in cognitive assessments. For all modalities, current findings need replication in larger samples. Although no neuroimaging tool is ready for use as a biomarker at this stage, these studies suggest a clinically meaningful role for neuroimaging in predicting post-stroke cognitive recovery.

Heterogeneity of White Matter Hyperintensity and Cognitive Impairment in Patients with Acute Lacunar Stroke

Background: The severity of white matter hyperintensity (WMH) in patients with acute lacunar stroke (ALS) may be not completely parallel to cognitive impairment. Controversies persist about the effects of WMH on cognitive dysfunction. It is vital to explore whether the association may be affected by certain factors and whether a subsequent subgroup analysis is necessary. The aim of this study was to evaluate the relationship between WMH and cognitive impairment in acute lacunar stroke patients and the possible causal factors. Methods: We continuously enrolled patients with ALS who were hospitalized at the First Affiliated Hospital of Soochow University between October 2017 and June 2022. The cognitive function of all patients was assessed by using the Montreal Cognitive Assessment (MoCA) scale 14 ± 2 days after the onset of AIS, and the results were adjusted to the education level. The MoCA scale was reevaluated at the 6-month (day 182 ± 7) follow-up by outpatient visit or video. Demographic and clinical data were collected. The manifestations of chronic cerebral small-vessel disease (CSVD), including the total Fazekas score and total CSVD burden score, were assessed with an MRI scan. A mismatch refers to an inconsistency between the severity of WMH and cognitive dysfunction. A Type 1 mismatch refers to cognitive impairment with mild WMH (total Fazekas score = 0−1), and a Type 2 mismatch refers to severe WMH (total Fazekas score = 5−6) in patients with normal cognitive function. Results: Among 213 enrolled ALS patients, 66 patients (31.0%) had cognitive dysfunction, and 40 patients (18.8%) had mismatches. Twenty-seven cases (12.7%) were Type 1 mismatched, and seventeen cases (8.0%) were Type 2 mismatched. Age, gender, fibrinogen and cerebral infarction history were independent risk factors for cognitive impairment in ALS patients. Imaging features, including moderate to severe WMH, deep WMH and the total CSVD burden score, were also independently associated with cognitive impairment. The patients in the mismatched group were older, had more severe deep WMH and had a higher occurrence of depression (p < 0.05). The NIHSS score, depression and microbleeds were significantly different between the Type 1 mismatched group and the matched group (p = 0.018, p = 0.012 and p = 0.047). Patients in the Type 2 mismatched group were male (p = 0.04), had a lower level of fibrinogen (p = 0.005), a lower incidence of CMBs (p = 0.003), a lower total CSVD burden score (p = 0.017), more severe paraventricular WMH (p = 0.035) and milder deep WMH (p = 0.026). Conclusions: Our study examined a homogeneous study cohort of recruited patients with symptomatic ALS. We found heterogeneity between WMH and cognitive function in ALS patients. Despite a similar WMH severity, some baseline clinical features and other conventional CSVD imaging characteristics may account for this heterogeneity phenomenon. Our findings provide data for the early diagnosis and prevention of cognitive impairment in ALS patients and suggest that the severity of WMH is not completely parallel to cognitive impairment. The white matter microstructural injury and remote WMH effects may account for the mismatch phenomenon. More attention should be paid to understanding the underlying mechanisms and finding new imaging markers.

Predictors of post-stroke cognitive impairment using acute structural MRI neuroimaging: A systematic review and meta-analysis

BACKGROUND

Stroke survivors are at an increased risk of developing post-stroke cognitive impairment and post-stroke dementia; those at risk could be identified by brain imaging routinely performed at stroke onset.

AIM

This systematic review aimed to identify features which are associated with post-stroke cognitive impairment (including dementia) on magnetic resonance imaging (MRI) performed at stroke diagnosis.

SUMMARY OF REVIEW

We searched the literature from inception to January 2022 and identified 10,284 records. We included studies that performed MRI at the time of stroke (0-30 days after a stroke) and assessed cognitive outcome at least 3 months after stroke. We synthesized findings from 26 papers, comprising 27 stroke-populations (N = 13,114, average age range = 40-80 years, 19-62% female). When data were available, we pooled unadjusted (OR_u) and adjusted (OR_a) odds ratios.We found associations between cognitive outcomes and presence of cerebral atrophy (three studies, N = 453, OR_u = 2.48, 95% CI = 1.15-4.62), presence of microbleeds (two studies, N = 9151, OR_a = 1.36, 95% CI = 1.08-1.70), and increasing severity of white matter hyperintensities (three studies, N = 704, OR_a = 1.26, 95% CI = 1.06-1.49). Increasing cerebral small vessel disease score was associated with cognitive outcome following unadjusted analysis only (two studies, N = 499, OR_u = 1.34, 95%CI = 1.12-1.61; three studies, N = 950, OR_a = 1.23, 95% CI = 0.96-1.57). Associations remained after controlling for pre-stroke cognitive impairment. We did not find associations between other stroke features and cognitive outcome, or there were insufficient data.

CONCLUSION

Acute stroke MRI features may enable healthcare professionals to identify patients at risk of post-stroke cognitive problems. However, there is still substantial uncertainty about the prognostic utility of acute MRI for this.

Vitamin D and its possible relationship to neuroprotection in COVID-19: evidence in the literature

Abstract:

Vitamin D is a hormone involved in the regulation of important biological processes such as signal transduction, immune response, metabolic regulation and also in the nervous and vascular systems. To date, coronavirus disease 2019 (COVID-19) infection does not have a specific treatment, however various drugs have been proposed, including those that attenuate the intense inflammatory response and recently the use of vitamin D, in clinical trials, as part of the treatment of COVID-19 has provided promising results. It has been observed in some clinical studies that the use of cholecalciferol (vitamin D3) and its two metabolites the circulating form, calcidiol or calcifediol (25-hydroxycalciferol, 25-(OH)-D) and the active form, calcitriol (1,25-(OH)2-D), in different doses, improve the clinical manifestations, prognosis and survival of patients infected with COVID-19 probably because of its anti-inflammatory, antiviral and lung-protective action. In relation to the central nervous system (CNS) it has been shown, in clinical studies, that vitamin D is beneficial in some neurological and psychiatric conditions because of its anti-inflammatory and antioxidant properties, modulation of neurotransmitters actions, regulation of calcium homeostasis between other mechanisms. It has been showed that COVID-19 infection induces CNS complications such as headache, anosmia, ageusia, neuropathy, encephalitis, stroke, thrombosis, cerebral hemorrhages, cytotoxic lesions and psychiatric conditions and it has been proposed that the use of dietary supplements, as vitamin and minerals, can be adjuvants in this disease. In this review the evidence of possible role of vitamin D, and its metabolites, as protector against the neurological manifestations of COVID-19 was summarized.

Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State

The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke. 208 patients with severe stroke who all received MRI examination were recruited as the research objects. According to cerebral small vascular disease (CSVD) score, the patients were divided into CSVD 0∼4 groups. The patients who completed the three-month follow-up were classified into cognitive impairment group (124 cases) and the noncognitive impairment group (84 cases) according to the cut-off point of the Montreal cognitive assessment (MOCA) scale score of 26. A novel image segmentation algorithm was proposed based on U-shaped fully CNN (U-Net) and conditional random field, which was compared with the fully CNN (FCN) algorithm and U-Net algorithm, and was applied to the MRI segmentation training of patients with severe stroke. It was found that the average symmetric surface distance (ASSD) (3.13 ± 1.35), Hoffman distance (HD) (28.71 ± 9.05), Dice coefficient (0.78 ± 1.35), accuracy (0.74 ± 0.11), and sensitivity (0.85 ± 0.13) of the proposed algorithm were superior to those of FCN algorithm and U-Net algorithm. There were significant differences in the MOCA scores among the five groups of patients from CSVD 0 to CSVD 4 in the three time periods (0, 1, and 3 months) (P < 0.05). Differences in cerebral microhemorrhage (CMB), perivascular space (PVS), and number of cavities, Fazekas, and total CSVD scores between the two groups were significant (P < 0.05). Multivariate regression found that the number of PVS, white matter hyperintensity (WMH) Fazekas, and total CSVD score were independent factors of cognitive impairment. In short, MRI images based on deep learning image segmentation algorithm had good application value for clinical diagnosis and treatment of stroke and can effectively improve the detection effect of brain domain characteristics and psychological state of patients after stroke.