Cerebral Small Vessel Disease Load Research Articles

Correlation analysis and predictive model construction of metabolic syndrome, complete blood count-derived inflammatory markers, and overall burden of cerebral small vessel disease

BackgroundThe high burden of cerebral small vessel disease (CSVD) on neuroimaging is a significant risk factor for stroke, cognitive dysfunction, and emotional disorders. Currently, there is a lack of studies investigating the correlation between metabolic syndrome (MetS), complete blood count-derived inflammatory markers, and total CSVD burden. This study aims to evaluate the total CSVD imaging load using machine learning (ML) algorithms and to explore further the relationship between MetS, complete blood count-derived inflammatory markers, and CSVD load. MethodsWe included CSVD patients from Xijing Hospital (2012–2022). Univariate and lasso regression analyses identified variables linked to CSVD neuroimaging burden. Six ML models predicted CSVD burden based on MetS and inflammatory markers. Model performance was evaluated using ROCauc, PRauc, DCA, and calibration curves. The SHAP method validated model interpretability. The best-performing model was selected to develop a web-based calculator using the Shiny package. ResultsThe Logistic regression model outperformed others in predicting CSVD burden. The model incorporated MetS, neutrophil-to-lymphocyte ratio (NLR), homocysteine (Hcy), age, smoking status, cystatin C (CysC), uric acid (UA), and prognostic nutritional index (PNI). ConclusionMetS, NLR, Hcy and CSVD high load were positively correlated, and the Logistic regression model could accurately predict the total CSVD load degree.

Quantitative Analysis of Multimodal MRI Markers and Clinical Risk Factors for Cerebral Small Vessel Disease Based on Deep Learning.

Cerebral small vessel disease lacks specific clinical manifestations, and extraction of valuable features from multimodal images is expected to improve its diagnostic accuracy. In this study, we used deep learning techniques to segment cerebral small vessel disease imaging markers in multimodal magnetic resonance images and analyze them with clinical risk factors. We recruited 211 lacunar stroke patients and 83 control patients. The patients' cerebral small vessel disease markers were automatically segmented using a V-shaped bottleneck network, and the number and volume were calculated after manual correction. The segmentation results of the V-shaped bottleneck network for white matter hyperintensity and recent small subcortical infarction were in high agreement with the ground truth (DSC>0.90). In small lesion segmentation, cerebral microbleed (average recall=0.778; average precision=0.758) and perivascular spaces (average recall=0.953; average precision=0.923) were superior to lacunar infarct (average recall=0.339; average precision=0.432) in recall and precision. Binary logistic regression analysis showed that age, systolic blood pressure, and total cerebral small vessel disease load score were independent risk factors for lacunar stroke (P<0.05). Ordered logistic regression analysis showed age was positively correlated with cerebral small vessel disease load score and total cholesterol was negatively correlated with cerebral small vessel disease score (P<0.05). Lacunar stroke patients exhibited higher cerebral small vessel disease imaging markers, and age, systolic blood pressure, and total cerebral small vessel disease score were independent risk factors for lacunar stroke patients. V-shaped bottleneck network segmentation network based on multimodal deep learning can segment and quantify various cerebral small vessel disease lesions to some extent.

Subclinical hypothyroidism is associated with basal ganglia enlarged perivascular spaces and overall cerebral small vessel disease load.

The association between subclinical hypothyroidism (SCH) and cerebral small vessel disease (CSVD) in the stroke-free population is currently unclear. A total of 354 individuals without a history of stroke were enrolled in this study. Demographic data, medical history, vascular risk factors, carotid arteriosclerosis, and the results of laboratory tests were collated. SCH is defined as an elevation in thyroid-stimulating hormone levels, but with normal free thyroxine levels. Magnetic resonance imaging (MRI) was used to assess 4 markers of CSVD, including white matter hyperintensities (WMHs), lacunes, deep microbleeds, and enlarged perivascular spaces (EPVSs). The overall CSVD load was then ranked using an ordinal scale ranging from 0 to 4. Brain atrophy was measured semi-quantitatively on MRI. A binary logistic regression model was used to explore the association of SCH with each CSVD marker after adjusting for confounding factors. The ordinal regression model was used to explore the association of SCH with CSVD burden and brain atrophy after adjusting for confounding factors. The mean age of the participants (66.9% males) was 69.4±12.8 years. SCH was observed in 44 (12.4%) participants. MRI findings revealed 13% of cases with lacunes, 6.2% with microbleeds, 50.3% with confluent WMH, and 49.2% with extensive basal ganglia EPVS. Assessment of total CSVD burden showed that 29.1% scored 1, 30.5% scored 2, 6.5% scored 3, and 2.3% scored ≥3. SCH was associated with extensive basal ganglia EPVS [odds ratio (OR) =2.175; 95% confidence interval (CI): 1.075 to 4.401] and total CSVD load (OR =1.879; 95% CI: 1.028 to 3.438). SCH was not associated with advanced brain atrophy. SCH is associated with the advanced total burden of CSVD and basal ganglia EPVS in the stroke-free population.

Cerebral Small Vessel Disease Load Predicts Functional Outcome and Stroke Recurrence After Intracerebral Hemorrhage: A Median Follow-Up of 5 Years.

Background: Uncertainty exists over the long-term prognostic significance of cerebral small vessel disease (CSVD) in primary intracerebral hemorrhage (ICH).Methods: We performed a longitudinal analysis of CSVD and clinical outcomes in consecutive patients with primary ICH who had MRI. Baseline CSVD load (including white matter hyperintensities [WMH], cerebral microbleeds [CMBs], lacunes, and enlarged perivascular spaces [EPVS]) was evaluated. The cumulative CSVD score was calculated by combining the presence of each CSVD marker (range 0–4). We followed participants for poor functional outcome [modified Rankin scale [mRS] ≥ 4], stroke recurrence, and time-varying survival during a median follow-up of 4.9 [interquartile range [IQR] 3.1–6.0] years. Parsimonious and fuller multivariable logistic regression analysis and Cox-regression analysis were performed to estimate the association of CSVD markers, individually and collectively, with each outcome.Results: A total of 153 patients were included in the analyses. CMBs ≥ 10 [adjusted OR [adOR] 3.252, 95% CI 1.181–8.956, p = 0.023] and periventricular WMH (PWMH) (adOR 2.053, 95% CI 1.220–3.456, p = 0.007) were significantly associated with poor functional outcome. PWMH (adOR 2.908, 95% CI 1.230–6.878, p = 0.015) and lobar CMB severity (adOR 1.811, 95% CI 1.039–3.157, p = 0.036) were associated with stroke recurrence. The cumulative CSVD score was associated with poor functional outcome (adOR 1.460, 95% CI 1.017–2.096) and stroke recurrence (adOR 2.258, 95% CI 1.080–4.723). Death occurred in 36.1% (13/36) of patients with CMBs ≥ 10 compared with 18.8% (22/117) in those with CMB < 10 (adjusted HR 2.669, 95% CI 1.248–5.707, p = 0.011). In addition, the cumulative CSVD score ≥ 2 was associated with a decreased survival rate (adjusted HR 3.140, 95% CI 1.066–9.250, p = 0.038).Conclusions: Severe PWMH, CMB, or cumulative CSVD burden exert important influences on the long-term outcome of ICH.

Association between Brachial-Ankle Arterial Stiffness and Cerebral Small Vessel Disease Load in Patients with Acute NonCardioembolic Ischemic Stroke

Association between Brachial-Ankle Arterial Stiffness and Cerebral Small Vessel Disease Load in Patients with Acute NonCardioembolic Ischemic Stroke

Relevance of cerebral small vessel disease load scores in first-ever lacunar infarction

AimTo reveal the correlation between total cerebrovascular disease load and primary lacunar infarction. BackgroundCerebral small vessel disease (CSVD) is the lack of specific clinical manifestations, whose clinical diagnoses are highly dependent on neuroimaging results. Total CSVD load scores may be more suitable for the assessment of overall brain function damage caused by CSVD. Little is known about whether the association between imaging markers of CSVD and CSVD total load scores at the time of first-ever lacunar infarction (LI). Methodsclinical data of 396 patients hospitalised from September 2016 to May 2018 due to a first-ever LI (case group), along with patients diagnosed with CSVD based on imaging alone and those with no abnormalities (control group) based on magnetic resonance imaging (MRI). Binary logistic regression and multiple ordered logistic regression were used to analyse the characteristics of imaging markers of CSVD in patients with first-ever LI, including different total score burden and distribution, and the relationship between different markers. ResultsIn 396 patients, smoking, cholesterol level and total small vessel disease (SVD) score were all significantly associated with the first-ever LI. There were more LI, cerebral microbleeds (CMB), white matter hyperintensities (WMH), and moderate to severe enlarged perivascular spaces (EPVS) in the first-ever LI group, relative to controls (p < 0.01). The Fazekas scores for periventricular WMH, deep WMH, and total Fazekas score were all significantly higher in patients with first-ever LI relative to those with no cerebral abnormalities (p < 0.01). An analysis of various imaging markers of CSVD revealed a significant correlation between the presence and degree of any marker and the severity of other markers, even after adjusting for the presence of other markers (p < 0.05). ConclusionsThe first-ever LI group exhibited higher total CSVD score loads, a greater number of lacunae, CMB, severe WMH and moderate to severe EPVS. Smoking is an independent risk factor in patients with first-ever LI.

Type 2 Diabetes, Change in Depressive Symptoms Over Time, and Cerebral Small Vessel Disease: Longitudinal Data of the AGES-Reykjavik Study.

Type 2 diabetes has been associated with depression. However, the underlying pathophysiological mechanisms remain unknown. Cerebral small vessel disease, a consequence of diabetes, may lead to depression. Therefore, we evaluated whether cerebral small vessel disease mediates the association between type 2 diabetes and higher depressive symptoms. We used longitudinal data from the population-based Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study, with examinations from 2002 to 2006 and 5 years later. Type 2 diabetes was defined as self-reported history of type 2 diabetes, use of blood glucose-lowering drugs, or fasting blood glucose level ≥7.0 mmol/L. Cerebral small vessel disease load was quantified in a composite score based on MRI-defined presence of high white matter hyperintensity volume, low total brain parenchyma volume, and subcortical infarcts, cerebral microbleeds, and large perivascular spaces. The 5-year change in the 15-item Geriatric Depression Scale score (GDS-15) was measured between baseline and follow-up. Included were 2,135 individuals without dementia and baseline depression (baseline age 74.5 [SD 4.6] years, 1,245 women [58.3%], and 197 [9.2%] with diabetes). The GDS-15 score increased 0.4 (SD 1.6) points over time. Baseline diabetes was associated with a greater increase in the GDS-15 score (β = 0.337; 95% CI 0.094; 0.579), adjusted for age, sex, education, and cardiovascular risk factors. Baseline cerebral small vessel disease and change of cerebral small vessel disease statistically significantly mediated a part of this association. Type 2 diabetes is associated with a greater increase in depressive symptoms score over 5 years, and cerebral small vessel disease partly explains this association.

Arterial Stiffness Is Associated With Basal Ganglia Enlarged Perivascular Spaces and Cerebral Small Vessel Disease Load.

We assessed whether the load of cerebral small vessel disease (cSVD) and its individual markers, including lacunes, white matter hyperintensities, microbleeds, and enlarged perivascular spaces (EPVS), are associated with arterial stiffness. We evaluated cSVD markers in a cohort of 782 hypertensive individuals without history of stroke or dementia. The load of the disease was calculated using an ordinal scale ranging from 0 to 4 (1 point was given for each of the 4 markers examined). The arterial stiffness was tested by measuring the carotid-femoral pulse wave velocity with an oscillometric automatic device. The mean age of the participants (49.6% women) was 62.7±5.4 years, and the mean systolic/diastolic blood pressure was 142.9/77.3 mm Hg (55.5% of the participants had poor blood pressure control). We found 7.2% cases with lacunes, 6.4% with microbleeds, 6.7% with extensive white matter hyperintensities, 24.5% with extensive basal ganglia EPVS, and 40.1% with extensive EPVS in the centrum semiovale. Regarding the cSVD load, 19.7% of the participants scored 1, 6.5% scored 2, and 1.4% scored ≥3. The median carotid-femoral pulse wave velocity was 10.5 m/s (interquartile range, 9.2-11.9) and was associated with lacunes (odds ratio per carotid-femoral pulse wave velocity SD increase, 1.51; 95% confidence interval, 1.13-2.03), extensive basal ganglia EPVS (odds ratio, 1.39; 95% confidence interval, 1.16-1.67), and cSVD load (common odds ratio, 1.42; 95% confidence interval, 1.19-1.68). We found that, in a cohort of hypertensive individuals, the arterial stiffness is associated with the total load of the cSVD, especially with lacunes and basal ganglia EPVS.