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The mechanism of cognitive impairment in patients with cerebral small vessel disease (CSVD) remains unknown. The glymphatic system dysfunction, which has been demonstrated to influence cognitive impairment, can be evaluated by diffusion tensor image analysis along the perivascular space (ALPS index). We explored whether cognitive impairment in CSVD is associated with glymphatic clearance dysfunction. In this study, 133 patients with CSVD were enrolled and underwent neuropsychological test batteries as well as magnetic resonance imaging (MRI). They were then categorized into a CSVD with cognitive impairment (CSVD-CI) group and a cognitively normal CSVD (CSVD-CN) group. The ALPS index and four CSVD markers [white matter lesions (WMLs), cerebral microbleeds (CMBs), lacunes, and perivascular spaces (PVSs)] were also assessed. Univariate analysis showed that the ALPS index was significantly different between the CSVD-CN (n = 50) and CSVD-CI groups (n = 83) (p < 0.001). This difference remained significant (95% CI < 0.001–0.133) after adjusting for six common risk factors (age, education, hypertension, diabetes, smoking, and alcohol abuse) as well as CSVD markers. The ALPS index was independently linearly correlated with global cognitive function, executive function, attention function, and memory after adjusting for the aforementioned six risk factors or CSVD markers. Our results suggest that glymphatic system impairment is independently related to cognitive impairment in patients with CSVD. [ABSTRACT FROM AUTHOR]

The mechanism of cognitive impairment in patients with cerebral small vessel disease (CSVD) remains unknown. The glymphatic system dysfunction, which has been demonstrated to influence cognitive impairment, can be evaluated by diffusion tensor image analysis along the perivascular space (ALPS index). We explored whether cognitive impairment in CSVD is associated with glymphatic clearance dysfunction. In this study, 133 patients with CSVD were enrolled and underwent neuropsychological test batteries as well as magnetic resonance imaging (MRI). They were then categorized into a CSVD with cognitive impairment (CSVD-CI) group and a cognitively normal CSVD (CSVD-CN) group. The ALPS index and four CSVD markers [white matter lesions (WMLs), cerebral microbleeds (CMBs), lacunes, and perivascular spaces (PVSs)] were also assessed. Univariate analysis showed that the ALPS index was significantly different between the CSVD-CN (n = 50) and CSVD-CI groups (n = 83) (p < 0.001). This difference remained significant (95% CI < 0.001–0.133) after adjusting for six common risk factors (age, education, hypertension, diabetes, smoking, and alcohol abuse) as well as CSVD markers. The ALPS index was independently linearly correlated with global cognitive function, executive function, attention function, and memory after adjusting for the aforementioned six risk factors or CSVD markers. Our results suggest that glymphatic system impairment is independently related to cognitive impairment in patients with CSVD.

Objectives: To evaluate the microstructural damage in the heterogeneity of different white matter areas in relapsing-remitting multiple sclerosis (RRMS) patients by using diffusion kurtosis imaging (DKI) and its correlation with clinical and cognitive status. Materials and Methods: Kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD) in T1-hypointense lesions (T1Ls), pure T2-hyperintense lesions (pure-T2Ls), normal-appearing white matter (NAWM), and white matter in healthy controls (WM in HCs) were measured in 48 RRMS patients and 26 sex- and age-matched HCs. All the participants were assessed with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Symbol Digit Modalities Test (SDMT) scores as the cognitive status. The Kurtzke Expanded Disability Status Scale (EDSS) scores were used to evaluate the clinical status in RRMS patients. Results: The lowest KFA, FA, and MK values and the highest MD values were found in T1Ls, followed by pure-T2Ls, NAWM, and WM in HCs. The T1Ls and pure-T2Ls were significantly different in FA (p = 0.002) and MK (p = 0.013), while the NAWM and WM in HCs were significantly different in KFA, FA, and MK (p < 0.001; p < 0.001; p = 0.001). The KFA, FA, MK, and MD values in NAWM (r = 0.360, p = 0.014; r = 0.415, p = 0.004; r = 0.369, p = 0.012; r = −0.531, p < 0.001) were correlated with the MMSE scores and the FA, MK, and MD values in NAWM (r = 0.423, p = 0.003; r = 0.427, p = 0.003; r = −0.359, p = 0.014) were correlated with the SDMT scores. Conclusion: Applying DKI to the imaging-based white matter classification has the potential to reflect the white matter damage and is correlated with cognitive impairment. [ABSTRACT FROM AUTHOR]

Purpose: Primary aldosteronism (PA) is the most frequent form of secondary hypertension. Hypertension is a risk factor for cognitive decline and dementia. White matter lesions (WMLs) are linked to vascular risk factors, which increase the risk of dementia. We aimed to analyze the association of PA-related parameters and WMLs in patients with PA. Methods: We conducted a retrospective analysis of all patients with PA in the Hypertension Center of the People's Hospital of Xinjiang Uygur Autonomous Region from January 1, 2011 to April 1, 2021. We analyzed the relationship between plasma aldosterone concentration (PAC), plasma renin activity (PRA), aldosterone–renin ratio (ARR), serum potassium, and WMLs. Results: We enrolled 138 patients with WMLs and matched these to controls without WMLs at a 1:4 ratio. Among the analytic sample (N = 711) with ages ranging from 30 to 64 years, 69% were male. In the logistic regression analysis, PAC, PRA and serum potassium were treated as continuous variables. The results showed that PAC (OR 1.04, 95% CI 1.01, 1.06, P = 0.008) was positively associated with the risk of WMLs, and serum potassium (OR 0.26, 95% CI 0.16, 0.44, P < 0.001) was inversely associated with the risk of WMLs. PRA (OR 0.86, 95% CI 0.68, 1.08, P = 0.384) was not associated with the risk of WMLs after adjusting for confounders. The results of restricted cubic splines showed the dose-response association between increasing PAC, ARR, decreasing serum potassium, and the risk of WMLs. We also divided PAC, ARR and serum potassium into two groups according to the result of restricted cubic splines. After adjusting for confounders, patients who were in Q2 (≥23.12 ng/dl) of PAC (OR 2.07, 95% CI 1.36, 3.15), Q2 (≥56.81 (ng/dl per ng/ml*h) of ARR (OR 1.82, 95% CI 1.22, 2.72) and Q2 (≤3.58 mmol/l) of serum potassium (OR 2.99, 95% CI 1.95, 4.50) had a significantly higher risk of WMLs than their counterparts. In stratified analyses, there was no evidence of subgroup heterogeneity regarding the change in the risk of WMLs (P > 0.05 for interaction for all). Conclusion: Our results suggested that the PAC and serum potassium were related to the risk of WMLs in patients with PA. In particular, PAC ≥23.12 ng/dl significantly increased the risk of WMLs in patients with PA. [ABSTRACT FROM AUTHOR]

ObjectivesTo evaluate the microstructural damage in the heterogeneity of different white matter areas in relapsing-remitting multiple sclerosis (RRMS) patients by using diffusion kurtosis imaging (DKI) and its correlation with clinical and cognitive status.Materials and MethodsKurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD) in T1-hypointense lesions (T1Ls), pure T2-hyperintense lesions (pure-T2Ls), normal-appearing white matter (NAWM), and white matter in healthy controls (WM in HCs) were measured in 48 RRMS patients and 26 sex- and age-matched HCs. All the participants were assessed with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Symbol Digit Modalities Test (SDMT) scores as the cognitive status. The Kurtzke Expanded Disability Status Scale (EDSS) scores were used to evaluate the clinical status in RRMS patients.ResultsThe lowest KFA, FA, and MK values and the highest MD values were found in T1Ls, followed by pure-T2Ls, NAWM, and WM in HCs. The T1Ls and pure-T2Ls were significantly different in FA (p = 0.002) and MK (p = 0.013), while the NAWM and WM in HCs were significantly different in KFA, FA, and MK (p < 0.001; p < 0.001; p = 0.001). The KFA, FA, MK, and MD values in NAWM (r = 0.360, p = 0.014; r = 0.415, p = 0.004; r = 0.369, p = 0.012; r = −0.531, p < 0.001) were correlated with the MMSE scores and the FA, MK, and MD values in NAWM (r = 0.423, p = 0.003; r = 0.427, p = 0.003; r = −0.359, p = 0.014) were correlated with the SDMT scores.ConclusionApplying DKI to the imaging-based white matter classification has the potential to reflect the white matter damage and is correlated with cognitive impairment.

Background: Few studies have quantitatively analyzed the imaging disparities between multiple sclerosis (MS) and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We aimed to compare the imaging characteristics of MS and CADASIL in middle-aged patients., Materials and Methods: This retrospective study used a single-center database and included patients aged 40-60 years with MS and CADASIL who underwent the designated imaging protocol including 3D T1-weighted imaging and fluid attenuated inversion recovery (FLAIR), diffusion tensor imaging and susceptibility-weighted imaging between January 2018 and March 2023. Patients with MRI-detected macrobleeds were excluded., Results: A total of 27 patients with MS (mean age, 46.7 years ± 4.4, 8 men) and 30 patients with CADASIL (mean age, 51.6 years ± 5.8, 14 men) were included. No significant differences were observed in the Fazekas grades of white matter lesions (WMLs). Patients with CADASIL exhibited greater external capsule involvement (56.7% vs.18.5 %; p = 0.006), whereas the MS group had more lesions in the corpus callosum (81.5% vs. 53.3 %, p = 0.02) and brainstem (74.1% vs. 46.7 %, p = 0.04). The CADASIL group exhibited a higher incidence of microbleeds (12.07 vs. 0.11, p = 0.001). The WMLs in the MS group exhibited a lower T1 lesion/cerebrospinal fluid signal index (2.206 vs. 2.882, p < 0.001). A value of ≤2.57 demonstrated a sensitivity of 92.6 % and a specificity of 90.0 % in differentiating MS. Patients with MS had a thinner corpus callosum (7.18 mm vs 7.86 mm, p = 0.04), while patients with CADASIL showed significantly higher mean diffusivity (0.8776 × 10 -3 vs. 0.7637 × 10 -3 mm2/s, p = 0.03) and lower fractional anisotropy (0.7581 vs. 0.8389, p = 0.04) in the splenium of the corpus callosum., Conclusion: Middle-aged patients with MS and CADASIL showed comparable Fazekas grades for WMLs. However, lesion distribution, T1 signal characteristics, and splenic diffusivity changes can help differentiate between MS and CADASIL., Competing Interests: Declaration of competing interest The authors have nothing to disclose. The authors declare no conflicts of interest associated with this manuscript., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and ObjectiveWhite matter lesions (WMLs) are imaging changes in MRI of cerebral small vessel disease associated with vascular risk factors, increasing the risk of dementia, depression, and stroke. Aldosterone (ALD) or activation of mineralocorticoid receptor (MR) causes cerebrovascular injury in a mouse model. We aimed to analyze the relationship between ALD and WMLs in a population with hypertension.MethodsWe conducted a retrospective review of all patients screened for causes of secondary hypertension. We enrolled 547 patients with WMLs and matched these to controls without WMLs at a 1:1 ratio. White matter lesion load was assessed by using a modified Scheltens’ scale.ResultsAmong the analytic sample (N = 1,094) with ages ranging from 30 to 64 years, 62.2% were male. We divided plasma ALD concentration (PAC), plasma renin activity (PRA), and ALD–renin ratio (ARR) into the third tertile (Q3), second tertile (Q2), and first tertile (Q1). We also analyzed them simultaneously as continuous variables. Multivariate logistic regression analysis showed that participants in Q3 (>17.26 ng/dl) of PAC (OR 1.59, 95% CI 1.15, 2.19), Q3 (18.59 ng/dl per ng/ml*h) of ARR (OR 2.90, 95% CI 2.10, 4.01) had a significantly higher risk of WMLs than those in Q1 (2.19) of PRA, and Q1 ( 0.05 for interaction for all).ConclusionHigher PAC, especially in PAC >17.26 ng/dl, increased the risk of WMLs. PAC was positively associated with white matter lesion load independent of SBP or DBP.

Background and Objective: White matter lesions (WMLs) are imaging changes in MRI of cerebral small vessel disease associated with vascular risk factors, increasing the risk of dementia, depression, and stroke. Aldosterone (ALD) or activation of mineralocorticoid receptor (MR) causes cerebrovascular injury in a mouse model. We aimed to analyze the relationship between ALD and WMLs in a population with hypertension. Methods: We conducted a retrospective review of all patients screened for causes of secondary hypertension. We enrolled 547 patients with WMLs and matched these to controls without WMLs at a 1:1 ratio. White matter lesion load was assessed by using a modified Scheltens' scale. Results: Among the analytic sample (N = 1,094) with ages ranging from 30 to 64 years, 62.2% were male. We divided plasma ALD concentration (PAC), plasma renin activity (PRA), and ALD–renin ratio (ARR) into the third tertile (Q3), second tertile (Q2), and first tertile (Q1). We also analyzed them simultaneously as continuous variables. Multivariate logistic regression analysis showed that participants in Q3 (>17.26 ng/dl) of PAC (OR 1.59, 95% CI 1.15, 2.19), Q3 (<0.80 ng/dl) of PRA (OR 2.50, 95% CI 1.81, 3.44), and Q3 (>18.59 ng/dl per ng/ml*h) of ARR (OR 2.90, 95% CI 2.10, 4.01) had a significantly higher risk of WMLs than those in Q1 (<12.48) of PAC, Q1 (>2.19) of PRA, and Q1 (<6.96) of ARR. In linear regression analysis, we separately analyzed the correlation between the modified Scheltens' scale score and log(PAC) (β = 2.36; 95% CI 1.30, 3.41; p < 0.001), log(PRA) (β = −1.76; 95% CI −2.09, −1.43; p < 0.001), and log(ARR) (β = 1.86; 95% CI 1.55, 2.17; p < 0.001), which were all significantly correlated with white matter lesion load, after adjusting for confounding factors. Simple mediation analyses showed that systolic blood pressure (SBP) or diastolic blood pressure (DBP) mediated −3.83% or −2.66% of the association between PAC and white matter lesion load, respectively. In stratified analyses, there was no evidence of subgroup heterogeneity concerning the change in the risk of WMLs (p > 0.05 for interaction for all). Conclusion: Higher PAC, especially in PAC >17.26 ng/dl, increased the risk of WMLs. PAC was positively associated with white matter lesion load independent of SBP or DBP. [ABSTRACT FROM AUTHOR]

• CP volume was 30% larger in patients with RRMS than HCs and was 20% larger in patients with IRLs than those without IRLs. • The enlargement of CP in RRMS had close correlations with inflammatory lesions load, especially IRLs, and deep gray matter atrophy. • There were no statistical correlations between CP volume and cortical lesions load and cortex volume. • The larger CP volume was associated with higher disability and lower cognitive scores. Choroid plexus (CP) is considered to be linked to inflammation of multiple sclerosis (MS), but its connection with markers of inflammation in vivo in MS is unclear, the markers such as lesions load and brain atrophy, particularly the white matter lesions (WMLs) edge surrounded by an iron rim, termed as iron rim lesions (IRLs). To investigate the association between CP volume and brain lesions load, especially IRLs load and atrophy in MS, and its relationship with clinical characteristics. 3.0 T brain MRI images were acquired from 99 relapsing-remitting MS (RRMS) and 60 healthy controls (HCs) to obtain the volumes of CP, whole brain and lesions. Volumes were expressed as a ratio of intracranial volume. Expanded Disability Status Scale (EDSS), Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were used to assess the severity of disability and cognitive function. Student's t -test and Multivariable regression analyses were performed to evaluate the difference of CP volumes between RRMS and HC and the association between CP volume and lesions load, brain volumes and clinical scale scores in RRMS. CP volume was 30% larger in patients with RRMS than HCs (p < 0.001) and was 20% larger in patients with IRLs than those without IRLs (p = 0.007). Moreover, the larger CP volume was related to greater WMLs volume in the whole RRMS (r = 0.46, p < 0.001). Further analysis in patients with IRLs showed a positive correlation between CP volume and WMLs volume (r = 0.45, p = 0.003), and IRLs volume (r = 0.51, p < 0.001). Meanwhile, enlarged CP was related to lower volumes in the whole brain (r = -0.30, p = 0.006), deep gray matter (r = -0.51, p < 0.001) and most regional deep gray matter nuclei (except amygdala), but no correlation with cortical lesions or cortex volume (both p > 0.05). In addition, CP volume was significantly higher in patients with cognitive impairment than those with cognitive preservation by MoCA scores (p = 0.011); the larger CP volume was associated with higher EDSS scores (r = 0.25, p = 0.014) and lower SDMT Z scores in RRMS (r = -0.26, p = 0.014). The enlargement of CP in RRMS had close correlations with inflammatory lesions, especially IRLs and deep gray matter atrophy, but not the cortex. Meanwhile, the larger CP volume was associated with higher disability and lower cognitive scores. CP volume may be a surrogate imaging marker for MS disease activity. [ABSTRACT FROM AUTHOR]

White matter lesions (WMLs) are small groups of dead cells that clump together in the white matter of brain. In this paper, we propose a reliable method to automatically segment WMLs. Our method uses a novel filter to enhance the intensity of WMLs. Then a feature set containing enhanced intensity, anatomical and spatial information is used to train a random forest classifier for the initial segmentation of WMLs. Following that a reliable and robust edge potential function based Markov Random Field (MRF) is proposed to obtain the final segmentation by removing false positive WMLs. Quantitative evaluation of the proposed method is performed on 24 subjects of ENVISion study. The segmentation results are validated against the manual segmentation, performed under the supervision of an expert neuroradiologist. The results show a dice similarity index of 0.76 for severe lesion load, 0.73 for moderate lesion load and 0.61 for mild lesion load. In addition to that we have compared our method with three state of the art methods on 20 subjects of Medical Image Computing and Computer Aided Intervention Society's (MICCAI's) MS lesion challenge dataset, where our method shows better segmentation accuracy compare to the state of the art methods. These results indicate that the proposed method can assist the neuroradiologists in assessing the WMLs in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Alcohol dependence has become a major problem that poses a serious threat to public health. Long-term heavy alcohol consumption can lead to brain functional disorders. This study aimed to investigate the relationship of the severity of cerebral white matter lesions (WMLs), serum neurofilament light (NfL) and inflammatory factors, tumour necrosis factor alpha (TNF-α) and Interleukin-1β (IL-1β), with the cognitive function of patients with alcohol dependence., Methods: A total of 118 patients were enrolled in this prospective study, and divided into alcohol-dependent and non-alcohol-dependent groups. The severity of WMLs was assessed using the Fazekas scale based on magnetic resonance imaging analysis. The expression levels of NfL, TNF-α and IL-1β in the serum of the subjects were measured by enzyme-linked immunosorbent assay. The cognitive function and psychological status of the patients were assessed using the Minimum Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA). The severity of WMLs and the expression levels of serum NfL, TNF-α and IL-1β in alcohol-dependent patients were analysed for their influence on cognitive function. This clinical trial was approved by China Clinical Trials Registry, and the trial number is ChiCTR2200066057 (http://www.chictr.org.cn/searchproj.aspx)., Results: The score of Fazekas scale was higher, and the MMSE score and MoCA score were lower in the alcohol-dependent group than those in the non-alcohol-dependent group. Moreover, the Fazekas score of the alcohol-dependent group was negatively correlated with the MMSE and MoCA scores. The serum NfL, TNF-α and IL-1β levels were higher in the alcohol-dependent group than in the non-alcohol-dependent group, and the serum NfL, TNF-α and IL-1β levels in the alcohol-dependent group were negatively correlated with the MMSE and MoCA scores., Conclusion: Alcohol-dependent patients have more severe cerebral WMLs and significant cognitive impairment, particularly in visuospatial and executive functions, attention, calculation, abstraction, delayed recall and orientation. Serum NfL, TNF-α and IL-1β may be used as biomarkers to assess alcohol related cognitive decline., Competing Interests: None., (AJTR Copyright © 2023.)

Many current methods for multiple sclerosis (MS) lesion segmentation require radiologist seed points as input, but do not necessarily allow the expert to work in an intuitive or efficient way. Ironically, most methods also assume that the points are placed optimally. This paper examines how seed points can be processed with intuitive heuristics, which provide improved segmentation accuracy while facilitating quick and natural point placement. Using a large set of MRIs from an MS clinical trial, two radiologists are asked to seed the lesions while unaware that the points would be fed into a classifier, based on Parzen windows, that automatically delineates each marked lesion. To evaluate the impact of the new heuristics, an interactive region-growing method is used to provide ground truth and the Dice coefficient (DC) and Spearman’s rank correlation are used as the primary measures of agreement. A stratified analysis is performed to determine the effect on scans with low-, medium-, and high lesion loads. Compared to the unenhanced classifier, the heuristics dramatically improve the DC (+32.91 pt.) and correlation (+0.50) for the scans with low lesion loads, and also improve the DC (+14.55 pt.) and correlation (+0.15) for the scans with medium lesion loads, while having a minimal effect for the scans with high lesion loads, which are already segmented accurately by Parzen windows. With the heuristics, the DC is close to 80% and the correlation is above 0.9 for all three load categories. [ABSTRACT FROM PUBLISHER]

The purposes of this study were to explore the association between cognitive performance and white matter lesions (WMLs), and to investigate whether it is possible to predict cognitive impairment using spatial maps of WMLs. These WML maps were produced for 263 elders from the OASIS-3 dataset, and a relevance vector regression (RVR) model was applied to predict neuropsychological performance based on the maps. The association between the spatial distribution of WMLs and cognitive function was examined using diffusion tensor imaging data. WML burden significantly associated with increasing age (r=0.318, p<0.001) and cognitive decline. Eight of 15 neuropsychological measures could be accurately predicted, and the mini-mental state examination (MMSE) test achieved the highest predictive accuracy (CORR=0.28, p<0.003). WMLs located in bilateral tapetum, posterior corona radiata, and thalamic radiation contributed the most prediction power. Diffusion indexes in these regions associated significantly with cognitive performance (axial diffusivity>radial diffusivity>mean diffusivity>fractional anisotropy). These results show that the combination of the extent and location of WMLs exhibit great potential to serve as a generalizable marker of multidomain neurocognitive decline in the aging population. The results may also shed light on the mechanism underlying white matter changes during the progression of cognitive decline and aging.

Large arteries are the upstream vessels of cerebral small vessels, through which blood flow is transported. Since structurally and functionally connected, large arteries and cerebral small vessels are physiologically correlated. However, large vessel diseases and small vessel diseases are investigated separately in old era. More and more evidence suggested they are inter-mingled and should be considered together. When a deep brain lacunar infarct occurs, it is of necessity to perform high-resolution magnetic resonance imaging to screen intracranial large artery atherosclerosis, which requires more intensified treatment. It may be the appropriate strategy to keep longitudinal monitoring of the trend of large artery stiffness and give intervention such as aggressive blood pressure control to prevent cerebral white matter lesions (WMLs) occurrence or progression. More data from cohort studies are required, especially the biomarkers of "diseased" artery stiffness. In the future, when randomized clinical trials are performed, the end points should take both large artery and small vessel damages into consideration. The two diseases are in the same "boat", i.e., the pan-vessel diseases. In order to save one, we have to save both.