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1.
Alzheimers Dement ; 2024 Sep 04.
Article in English | MEDLINE | ID: mdl-39229896

ABSTRACT

INTRODUCTION: Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study. METHODS: We analyzed the Systolic Blood Pressure Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aß)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aß risk, (3) WMH risk, and (4) combined high risk. RESULTS: In the cohort of 467 participants (mean age 69.7 ± 7.1, 41.8% female, 31.9% nonwhite or Hispanic) during 4.8 years of follow-up and across the four exposure categories the rates of cognitive impairment were 5.3%, 7.8%, 11.8%, and 22.6%. Compared to the combined low-risk category, the adjusted hazard ratio for cognitive impairment was 4.12 (95% confidence interval, 1.71 to 9.94) in the combined high-risk category. DISCUSSION: This study emphasizes the potential impact of therapeutic approaches to dementia prevention that target both vascular and amyloid pathology. HIGHLIGHTS: White matter hyperintensity (WMH) and plasma amyloid (Aß42/40) are additive risk factors for the development of cognitive impairment in the SPRINT MIND trial. Individuals in the high-risk categories of both WMH and Aß42/40 had a near fivefold increase in risk of cognitive impairment during 4.8 years of follow-up on average. These findings suggest that treatment strategies targeting both vascular health and amyloid burden warrant further research.

2.
Sensors (Basel) ; 24(15)2024 Aug 02.
Article in English | MEDLINE | ID: mdl-39124050

ABSTRACT

To improve the performance of roller bearing fault diagnosis, this paper proposes an algorithm based on subtraction average-based optimizer (SABO), variational mode decomposition (VMD), and weighted Manhattan-K nearest neighbor (WMH-KNN). Initially, the SABO algorithm uses a composite objective function, including permutation entropy and mutual information entropy, to optimize the input parameters of VMD. Subsequently, the optimized VMD is used to decompose the signal to obtain the optimal decomposition characteristics and the corresponding intrinsic mode function (IMF). Finally, the weighted Manhattan function (WMH) is used to enhance the classification distance of the KNN algorithm, and WMH-KNN is used for fault diagnosis based on the optimized IMF features. The performance of the SABO-VMD and WMH-KNN models is verified through two experimental cases and compared with traditional methods. The results show that the accuracy of motor-bearing fault diagnosis is significantly improved, reaching 97.22% in Dataset 1, 98.33% in Dataset 2, and 99.2% in Dataset 3. Compared with traditional methods, the proposed method significantly reduces the false positive rate.

3.
Quant Imaging Med Surg ; 14(8): 6002-6014, 2024 Aug 01.
Article in English | MEDLINE | ID: mdl-39144016

ABSTRACT

Background: Both intracranial atherosclerosis and white matter hyperintensity (WMH) are prevalent among the stroke population. However, the relationship between intracranial atherosclerosis and WMH has not been fully elucidated. Therefore, the aim of this study was to investigate the relationship between the characteristics of intracranial atherosclerotic plaques and the severity of WMH in patients with ischemic stroke using high-resolution magnetic resonance vessel wall imaging. Methods: Patients hospitalized with ischemic stroke and concurrent intracranial atherosclerosis at Beijing Tsinghua Changgung Hospital, a tertiary comprehensive stroke center, who underwent high-resolution magnetic resonance vessel wall imaging and conventional brain magnetic resonance imaging were continuously recruited from January 2018 to December 2018. Both intracranial plaque characteristics (plaque number, maximum wall thickness, luminal stenosis, T1 hyperintensity, and plaque length) and WMH severity (Fazekas score and volume) were evaluated. Spearman correlation or point-biserial correlation analysis was used to determine the association between clinical characteristics and WMH volume. The independent association between intracranial plaque characteristics and the severity as well as WMH score was analyzed using logistic regression. The associations of intracranial plaque characteristics with total white matter hyperintensity (TWMH) volume, periventricular white matter hyperintensity (PWMH) volume and deep white matter hyperintensity (DWMH) volume were determined using multilevel mixed-effects linear regression. Results: A total of 159 subjects (mean age: 64.0±12.5 years; 103 males) were included into analysis. Spearman correlation analysis indicated that age was associated with TWMH volume (r=0.529, P<0.001), PWMH volume (r=0.523, P<0.001) and DWMH volume (r=0.515, P<0.001). Point-biserial correlation analysis indicated that smoking (r=-0.183, P=0.021) and hypertension (r=0.159, P=0.045) were associated with DWMH volume. After adjusting for confounding factors, logistic regression analysis showed plaque number was significantly associated with the presence of severe WMH [odds ratio (OR), 1.590; 95% CI, 1.241-2.035, P<0.001], PWMH score of 3 (OR, 1.726; 95% CI, 1.074-2.775, P=0.024), and DWMH score of 2 (OR, 1.561; 95% CI, 1.150-2.118, P=0.004). Intracranial artery luminal stenosis was associated with presence of severe WMH (OR, 1.032; 95% CI, 1.002-1.064, P=0.039) and PWMH score of 2 (OR, 1.057; 95% CI, 1.008-1.109, P=0.023). Multilevel mixed-effects linear regression analysis showed that plaque number was associated with DWMH volume (ß=0.128; 95% CI, 0.016-0.240; P=0.026) after adjusted for age and sex. Conclusions: In ischemic stroke patients, intracranial atherosclerotic plaque characteristics as measured by plaque number and luminal stenosis were associated with WMH burden.

4.
Neuroradiology ; 66(9): 1565-1575, 2024 Sep.
Article in English | MEDLINE | ID: mdl-38953988

ABSTRACT

PURPOSE: To investigate the prevalence of cerebrovascular MRI markers in unselected patients hospitalized for COVID-19 (Coronavirus disease 2019), we compared these with healthy controls without previous SARS-CoV-2 infection or hospitalization and subsequently, investigated longitudinal (incidental) lesions in patients after three months. METHODS: CORONIS (CORONavirus and Ischemic Stroke) was an observational cohort study in adult hospitalized patients for COVID-19 and controls without COVID-19, conducted between April 2021 and September 2022. Brain MRI was performed shortly after discharge and after 3 months. Outcomes included recent ischemic (DWI-positive) lesions, previous infarction, microbleeds, white matter hyperintensities (WMH) and intracerebral hemorrhage and were analysed with logistic regression to adjust for confounders. RESULTS: 125 patients with COVID-19 and 47 controls underwent brain MRI a median of 41.5 days after symptom onset. DWI-positive lesions were found in one patient (1%) and in one (2%) control, both clinically silent. WMH were more prevalent in patients (78%) than in controls (62%) (adjusted OR: 2.95 [95% CI: 1.07-8.57]), other cerebrovascular MRI markers did not differ. Prevalence of markers in ICU vs. non-ICU patients was similar. After three months, five patients (5%) had new cerebrovascular lesions, including DWI-positive lesions (1 patient, 1.0%), cerebral infarction (2 patients, 2.0%) and microbleeds (3 patients, 3.1%). CONCLUSION: Overall, we found no higher prevalence of cerebrovascular markers in unselected hospitalized COVID-19 patients compared to controls. The few incident DWI-lesions were most likely to be explained by risk-factors of small vessel disease. In the general hospitalized COVID-19 population, COVID-19 shows limited impact on cerebrovascular MRI markers shortly after hospitalization.


Subject(s)
COVID-19 , Magnetic Resonance Imaging , Humans , COVID-19/diagnostic imaging , COVID-19/epidemiology , Male , Female , Prevalence , Aged , Middle Aged , Magnetic Resonance Imaging/methods , Hospitalization , Follow-Up Studies , SARS-CoV-2 , Cerebrovascular Disorders/diagnostic imaging , Cerebrovascular Disorders/epidemiology , Cohort Studies , Case-Control Studies
5.
Rev Neurol (Paris) ; 2024 Jul 13.
Article in English | MEDLINE | ID: mdl-39004559

ABSTRACT

BACKGROUND AND AIMS: The association between white matter abnormalities (WMA) and cognitive decline previously reported in poststroke patients has been mainly documented using visual scales. However, automated segmentation of WMA provides a precise determination of the volume of WMA. Nonetheless, it is rarely used in the stroke population and its potential advantage over visual scales is still unsettled. The objective of this study was to examine whether automated segmentation of WMA provides a better account than the visual Fazekas and Wahlund scales of the decline in executive functions and processing speed in stroke patients. METHODS: The analyses were conducted on the 358 patients of the GRECogVASC cohort with an MRI performed at six months poststroke in the Amiens center. WMA were visually analyzed using the Fazekas (subcortical abnormalities) and Wahlund scales. Segmentation was performed using LST (3.0.3). Following preliminary studies to determine the optimal segmentation threshold, we examined the relationship between cognitive status and WMA volume computed at each threshold using receiver operating characteristic (ROC) curves. Finally, we assessed the ability of both Fazekas and Wahlund visual scores and WMA volume to account for cognitive scores by using a bivariate Pearson correlation analysis, comparing correlation coefficients with the Fisher transformation and repeating correlation analysis after adjustment for the lesion volume. RESULTS: Increasing the threshold led to an underestimation of WMA (P=0.0001) (significant for a threshold ≥0.2) and an improvement in correct rejection of signal changes in the stroke cavity (P=0.02) (significant for a threshold ≤0.5), susceptibility artifacts (P=0.002) (significant for a threshold ≤0.6), and corticospinal degeneration (P=0.03) (significant for a threshold ≤0.5). WMA volume decreased with increasing threshold (P=0.0001). Areas under the curve (AUC) did not differ according to the threshold (processing speed: P=0.85, executive cognitive functions: P=0.7). Correlation coefficients between cognitive scores and WMA were higher for WMA volume than the Fazekas (processing speed: Z=-3.442, P=0.001; executive functions: Z=-2.751, P=0.006) and Wahlund scores (processing speed: Z=-3.615, P=0.0001; executive functions: Z=-2.769, P=0.006). Adjustment for lesion volume did not alter the correlations with WMA volume (processing speed: r=-0.327 [95%CI: -0.416; -0.223], P=0.0001; executive functions: r=-0.262 [95%CI: -0.363; -0.150], P=0.0001). CONCLUSION: This study shows that WMA volume assessed by automated segmentation provides a better account of cognitive disorders than visual analysis. This should favor its wider use to refine imaging determinants of poststroke cognitive disorders.

6.
Comput Biol Med ; 178: 108684, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38852399

ABSTRACT

PURPOSE: White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors. MATERIALS AND METHODS: A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All participants underwent formal neuropsychological assessments to determine cognitive status. Automated identification and segmentation of WMH were conducted using VB-net, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validated on the testing set to detect cognitive impairment. Model performances were evaluated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment. RESULTS: Among the models, the logistic regression (LR) model based on white matter features demonstrated the highest performance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nuclei were causal factors of cognitive impairment. CONCLUSION: The LR model based on white matter features exhibited high accuracy in detecting cognitive impairment in WMH patients. Furthermore, the possible causal relationships among alterations in cortex, white matter, nuclei, and cognitive impairment were elucidated.


Subject(s)
Cognitive Dysfunction , Magnetic Resonance Imaging , White Matter , Humans , Cognitive Dysfunction/diagnostic imaging , Female , Male , White Matter/diagnostic imaging , White Matter/pathology , Magnetic Resonance Imaging/methods , Aged , Middle Aged , Artificial Intelligence , Aged, 80 and over , Deep Learning , Image Interpretation, Computer-Assisted/methods
7.
J Thorac Dis ; 16(5): 2713-2722, 2024 May 31.
Article in English | MEDLINE | ID: mdl-38883627

ABSTRACT

Background: Although aortic aneurysm is associated with vascular aging and atherosclerosis, carotid and intracranial vascular disease prevalence in patients with aortic arch aneurysm remains unclear. Similarly, the effect of carotid and intracranial lesions on postoperative outcomes is unknown. This study aimed to investigate the prevalence of carotid artery stenosis and intracranial lesions in patients with aortic arch aneurysm and its association with intraoperative regional cerebral oxygen saturation (rScO2) and postoperative neurological outcomes, including delirium and cerebral infarction. Methods: This retrospective observational study included 133 patients with true aortic arch aneurysm who underwent preoperative magnetic resonance imaging (MRI). We evaluated the prevalence of carotid and intracranial arterial lesions. Symptomatic cerebral infarction and delirium, defined by the confusion assessment method for the intensive care unit, were evaluated for their association with preoperative cerebrovascular lesions. Additionally, changes in regional saturation of the cerebral tissue at different surgical phases were evaluated for patients with and without cerebrovascular lesions. Results: Fifteen (11.3%) patients experienced symptomatic cerebral infarction, and 64 (48.1%) had postoperative delirium. Preoperative MRI showed old infarction, microbleeds, significant carotid artery stenosis, and intracranial lesions in 21.1%, 14.3%, 10.5%, and 7.5% of the patients, respectively. White matter hyperintensities with Fazekas scale 2 were observed in 40.6% of the patients, while Fazekas scale 3 were observed in 18.8% of the patients. Preoperative MRI findings and postoperative neurological outcomes were not significantly different. Seventy-six patients underwent rScO2 monitoring intraoperatively. Changes in rScO2 in patients with and without carotid/cerebrovascular lesions were not significantly different. However, rScO2 was significantly lower in patients who developed cerebral infarction. Conclusions: Significant carotid artery stenosis and intracranial lesions were observed in 10.5% and 7.5% of the patients, respectively. Although preoperative MRI findings and changes in rScO2 or postoperative outcomes showed no significant association, patients with postoperative cerebral infarction showed significantly lower rScO2 intraoperatively.

8.
Neurosci Biobehav Rev ; 161: 105677, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38636832

ABSTRACT

White matter damage quantified as white matter hyperintensities (WMH) may aggravate cognitive and motor impairments, but whether and how WMH burden impacts these problems in Parkinson's disease (PD) is not fully understood. This study aimed to examine the association between WMH and cognitive and motor performance in PD through a systematic review and meta-analysis. We compared the WMH burden across the cognitive spectrum (cognitively normal, mild cognitive impairment, dementia) in PD including controls. Motor signs were compared in PD with low/negative and high/positive WMH burden. We compared baseline WMH burden of PD who did and did not convert to MCI or dementia. MEDLINE and EMBASE databases were used to conduct the literature search resulting in 50 studies included for data extraction. Increased WMH burden was found in individuals with PD compared with individuals without PD (i.e. control) and across the cognitive spectrum in PD (i.e. PD, PD-MCI, PDD). Individuals with PD with high/positive WMH burden had worse global cognition, executive function, and attention. Similarly, PD with high/positive WMH presented worse motor signs compared with individuals presenting low/negative WMH burden. Only three longitudinal studies were retrieved from our search and they showed that PD who converted to MCI or dementia, did not have significantly higher WMH burden at baseline, although no data was provided on WMH burden changes during the follow up. We conclude, based on cross-sectional studies, that WMH burden appears to increase with PD worse cognitive and motor status in PD.


Subject(s)
Cognitive Dysfunction , Parkinson Disease , White Matter , Humans , Parkinson Disease/complications , Parkinson Disease/pathology , Parkinson Disease/diagnostic imaging , Parkinson Disease/physiopathology , White Matter/diagnostic imaging , White Matter/pathology , Cognitive Dysfunction/etiology , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/pathology , Cognitive Dysfunction/diagnostic imaging , Dementia/pathology , Dementia/etiology , Dementia/physiopathology
9.
J Affect Disord ; 356: 424-435, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38631424

ABSTRACT

BACKGROUND: Previous studies conducted in various nationally representative samples of the general population show that positive mental health is related to social prosperity. However, specific studies in university populations are scarce. In this study, we set out to explore factors associated with mental well-being (MWB) in a representative sample of first-year university students in Spain. METHODS: MWB was assessed with the short version of the Warwick-Edinburgh Mental Well-Being Scale. Multinomial logistic regressions were performed to explore the association between different blocks of factors, including relational, adversity, stress, lifestyle, spiritual, health, and self-perceived health variables with high and low MWB, controlling for sociodemographic and university-related variables. RESULTS: Data from 2082 students (18.6 ± 1.2 years; 56.6 % females) were analysed. Being male, being born in a foreign country, "high" self-perceived support, and "high" self-perceived mental health increased the odds of high MWB. Growing up in the suburbs, stressful experiences, and anxiety disorders reduced the odds of high MWB. Mood and anxiety disorders increased the odds of low MWB. "Middle" self-perceived support, sleeping ≥8 h per day, and "high" self-perceived mental health reduced the odds of low MWB. LIMITATIONS: The cross-sectional design precludes establishing causal relationships. Data were collected in the 2014-15 academic year using self-reported online surveys. CONCLUSION: The factors associated with high and low MWB do not always mirror each other, so specific plans are needed to successfully address each of the two poles. Interventions and policies targeting these factors for health promotion and disease prevention would improve the MWB of university students.


Subject(s)
Mental Health , Students , Humans , Male , Female , Students/psychology , Students/statistics & numerical data , Spain/epidemiology , Universities , Adolescent , Young Adult , Stress, Psychological/psychology , Stress, Psychological/epidemiology , Cross-Sectional Studies , Social Support , Life Style , Anxiety Disorders/epidemiology , Anxiety Disorders/psychology
10.
Alzheimers Dement ; 20(4): 2680-2697, 2024 04.
Article in English | MEDLINE | ID: mdl-38380882

ABSTRACT

INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. HIGHLIGHTS: Mutation position influences Aß burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aß burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.


Subject(s)
Alzheimer Disease , Amyloidosis , Cerebral Small Vessel Diseases , Humans , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/genetics , Alzheimer Disease/pathology , Cerebral Small Vessel Diseases/diagnostic imaging , Cerebral Small Vessel Diseases/genetics , Cerebral Small Vessel Diseases/complications , Diffusion Tensor Imaging , Magnetic Resonance Imaging , Mutation/genetics , Presenilin-1/genetics
11.
Quant Imaging Med Surg ; 14(2): 1417-1428, 2024 Feb 01.
Article in English | MEDLINE | ID: mdl-38415162

ABSTRACT

Background: Deep medullary vein (DMV) hypo-visibility is correlated with white matter hyperintensity (WMH), but the underlying causes remain unclear. This study aimed to explore the relationship between deep vein diameters and perivascular space (PVS) scores, and DMV hypo-visibility in the presence of WMH. Methods: This cross-sectional study prospectively analyzed the clinical and imaging data of 190 cerebral small vessel disease patients with WMH and 40 healthy controls from the Lishui Hospital of Traditional Chinese Medicine affiliated with Zhejiang Chinese Medical University. PVS scores ranging from 0 to 4 were determined according to the PVS counts in the basal ganglia area on T2-weighted magnetic resonance images; high-grade PVS was defined as a PVS score >1. The diameters of the deep cerebral veins, including the bilateral septal veins (SVs), thalamostriate veins (TSVs), lateral ventricular veins (LVVs), and internal cerebral veins, were measured using susceptibility weighted imaging (SWI). Left and right DMV scores, ranging from 0 to 9, were calculated based on the visibility of the DMV on SWI in the ipsilateral frontal, parietal, and occipital lobes. Results: The deep cerebral vein diameters, left and right DMV scores, and high-grade PVS differed between the healthy controls and WMH patients (P<0.05). Left DMV scores were independently associated with age {ß [95% confidence interval (CI)]: 0.050 (0.018, 0.082)}, high-grade PVS [ß (95% CI): 0.998 (0.262, 1.737)], and the diameters of the ipsilateral SVs [ß (95% CI): -1.114 (-1.754, -0.475)], SVs [ß (95% CI): -0.734 (-1.191, -0.277)], and LVVs [ß (95% CI): -0.921 (-1.567, -0.275)] [all false discovery rate (FDR)-corrected P<0.05]. Right DMV scores were independently associated with age [ß (95% CI): 0.071 (0.037, 0.105)], high-grade PVS [ß (95% CI): 0.873 (0.111, 1.635)], and the diameters of the ipsilateral SVs [ß (95% CI): -0.837 (-1.386, -0.289)], TSVs [ß (95% CI): -0.875 (-1.331, -0.419)], and LVVs [ß (95% CI): -1.813 (-2.484, -1.142)] (all FDR-corrected P<0.05). Conclusions: Decreased hypo-visibility of DMVs on SWI was associated with a higher age, the presence of high-grade PVS, and smaller diameters of the ipsilateral deep cerebral veins in individuals with WMH. Our findings provide novel insights into the probable mechanisms leading to high DMV scores.

12.
13.
Neurobiol Aging ; 135: 79-90, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38262221

ABSTRACT

We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance.


Subject(s)
Alzheimer Disease , Connectome , White Matter , Humans , Alzheimer Disease/pathology , White Matter/pathology , Cognition , Neuroimaging , Magnetic Resonance Imaging/methods
14.
Neuroimage Clin ; 41: 103549, 2024.
Article in English | MEDLINE | ID: mdl-38071889

ABSTRACT

BACKGROUND: The influence of white matter hyperintensity (WMH) on clinical outcomes in acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT) remains controversial. We performed a systematic review and meta-analysis to examine whether WMH burden is associated with clinical outcomes in AIS patients after MT. METHODS: PubMed, Embase, and Web of Science were searched from inception to Sep 03, 2023. The registration number for PROSPERO is CRD42022340568. Studies reporting an association between the burden of WMH in AIS patients and clinical outcomes after MT were included in the meta-analysis. A random-effects model was used for meta-analysis. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Additionally, the presence of imprecise-study effects was evaluated using Egger's test and funnel plot. RESULTS: Fifteen studies with 3,456 patients were enrolled in this meta-analysis. Among AIS patients who underwent MT, moderate/severe WMH had higher odds of 90-day unfavorable functional outcomes (odds ratio [OR] 2.72, 95% confidence interval [CI] 2.14-3.44; I2 = 0.0%; 95% CI 0.0%-42.7%), 90-day mortality (OR 1.94, 95% CI 1.45-2.60; I2 = 19.5%; 95% CI 0.0%-65.2%) and futile recanalization (OR 2.99, 95% CI 1.42-6.28; I2 = 69.7%; 95% CI 0.0%-91.0%) compared with none/mild WMH. However, the two groups had no significant difference in successful recanalization, symptomatic hemorrhagic transformation, and hemorrhagic transformation. A subset analysis of patients from 3 articles showed that WMH volume was not significantly associated with these outcomes. A notable limitation is that this meta-analysis lacks direct adjustment for imbalances in important baseline covariates. CONCLUSIONS: Patients with moderate/severe WMH on baseline imaging are associated with substantially increased odds of 90-day unfavorable outcomes, futile recanalization, and 90-day mortality after MT. This association suggests that moderate/severe WMH may contribute to the prediction of clinical outcomes in AIS patients after MT.


Subject(s)
Brain Ischemia , Ischemic Stroke , Leukoaraiosis , Stroke , White Matter , Humans , Stroke/diagnostic imaging , Stroke/surgery , Stroke/complications , Ischemic Stroke/diagnostic imaging , Ischemic Stroke/surgery , Brain Ischemia/diagnostic imaging , Brain Ischemia/surgery , Brain Ischemia/complications , White Matter/diagnostic imaging , Treatment Outcome , Thrombectomy/adverse effects , Thrombectomy/methods
15.
Neuroimage ; 285: 120494, 2024 Jan.
Article in English | MEDLINE | ID: mdl-38086495

ABSTRACT

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets.


Subject(s)
Leukoaraiosis , White Matter , Humans , White Matter/diagnostic imaging , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Algorithms , Aging
16.
medRxiv ; 2023 Oct 26.
Article in English | MEDLINE | ID: mdl-37961444

ABSTRACT

Individuals with Down syndrome (DS) are less likely to have hypertension than neurotypical adults. However, whether blood pressure measures are associated with brain health and clinical outcomes in this population has not been studied in detail. Here, we assessed whether pulse pressure is associated with markers of cerebrovascular disease, entorhinal cortical atrophy, and diagnosis of dementia in adults with DS. Participants with DS from the Biomarkers of Alzheimer's Disease in Adults with Down Syndrome study (ADDS; n=195, age=50.6±7.2 years, 44% women, 18% diagnosed with dementia) were included. Higher pulse pressure was associated with greater global, parietal, and occipital WMH volume. Pulse pressure was not related to enlarged PVS, microbleeds, infarcts, entorhinal cortical thickness, or dementia diagnosis. However, in a serial mediation model, we found that pulse pressure was indirectly related to dementia diagnosis through parieto-occipital WMH and, subsequently through entorhinal cortical thickness. Higher pulse pressure may be a risk factor for dementia in people with DS by promoting cerebrovascular disease, which in turn affects neurodegeneration. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with Down syndrome despite the low likelihood of frank hypertension.

17.
Quant Imaging Med Surg ; 13(11): 7596-7606, 2023 Nov 01.
Article in English | MEDLINE | ID: mdl-37969631

ABSTRACT

Background: This systematic review summarizes available evidence on the relationship between white matter hyperintensities (WMH) volumetric quantification on brain MRI scans and chronic kidney disease (CKD). Methods: The literature search was performed in March 2022 using MEDLINE PubMed Central, Scopus and Web of Science - Publons as search engines. Relevant articles investigating, with a quantitative volumetric approach, the link between WMH and CKD patients were selected. Results: The database search strategy found 987 articles, after excluding duplicates, the titles and abstracts of the remaining 320 articles were examined. Subsequently 276 articles were excluded as they were not relevant to the topic. Of the 44 articles evaluated for eligibility, 36 were excluded because the quantitative analysis of WMH was not volumetric. Finally, 8 articles were included in this systematic review. Conclusions: Literature on this topic is extremely heterogeneous in terms of methodology and samples. However, evidence shows that there is a relationship between CKD and WMH volume of the brain. We recommend that quantifiable biomarkers such as estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (UACR) should be included in studies dealing with cerebrovascular disease. The biological and molecular mechanisms underlying cerebrovascular damage in patients with chronic renal failure deserve to be further explored.

18.
Alzheimers Res Ther ; 15(1): 197, 2023 11 10.
Article in English | MEDLINE | ID: mdl-37950256

ABSTRACT

BACKGROUND: Cholesterol plays important roles in ß-amyloid (Aß) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aß and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aß and CSVD burdens in a large, non-demented Korean cohort. METHODS: We enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aß PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aß uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders. RESULTS: Increased LDL-c levels (ß = 0.014 to 0.115, p = 0.013) were associated with greater Aß uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (ß = - 0.133 to - 0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect ß = - 0.053, p = 0.040), which was partially mediated by Aß uptake (indirect effect ß = - 0.018, p = 0.006). CONCLUSIONS: Our findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aß and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.


Subject(s)
Cerebral Small Vessel Diseases , Cognitive Dysfunction , Humans , Cholesterol, LDL , Cognitive Dysfunction/diagnostic imaging , Cognition , Cholesterol , Amyloid beta-Peptides/metabolism , Amyloid
19.
Atherosclerosis ; 381: 117247, 2023 09.
Article in English | MEDLINE | ID: mdl-37634296

ABSTRACT

BACKGROUND AND AIMS: Despite reported correlations between intracranial arterial calcification (IAC) and white matter hyperintensities (WMH), little is known about the relationship between IAC pattern and WMH. By differentiating intimal and medial IAC, we aimed to investigate the relationship between IAC pattern and WMH. METHODS: Consecutive acute stroke patients were included. IAC pattern was categorized as intimal or medial on plain brain CT. The number of cerebral arteries involved by IAC for each patient was recorded. IAC severity was defined as focal or diffuse. On brain MRI, the burden of WMH was visually graded and classified as absent mild, moderate and severe. Multiple logistic regression was performed to examine the relationship between IAC and WMH. RESULTS: Among 265 patients, intimal IAC was detected in 54.7% patients and medial IAC in 48.5% patients. Diffuse IAC was present in 27.9% patients, all of which were medial. WMH was found in 75.5% patients, including 39.6% patients with mild WMH, 26.0% with moderate WMH, and 9.8% with severe WMH. The severity of medial IAC was correlated with WMH occurrence (p < 0.001). Chi-square linear trend suggested the number of arteries involved by medial IAC (p < 0.001) and the severity of medial IAC (p < 0.001) were correlated with WMH burden. Multiple ordinal logistic regression demonstrated a positive correlation of WMH burden with the number of arteries involved by medial IAC (p < 0.001) and the severity of medial IAC (p < 0.001). CONCLUSIONS: Medial IAC was correlated with WMH. The dose-effect relationship between medial IAC and WMH suggests underlying shared mechanisms of intracranial large artery disease and small vessel disease.


Subject(s)
Arteriosclerosis , Intracranial Arterial Diseases , Leukoaraiosis , Stroke , White Matter , Humans , White Matter/diagnostic imaging , Arteries
20.
Front Neuroimaging ; 2: 1099301, 2023.
Article in English | MEDLINE | ID: mdl-37554631

ABSTRACT

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.

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