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Introduction: White matter hyperintensities (WMH) and MRI-visible perivascular spaces (PVS) are neuroimaging features of cerebral small vessel disease (CSVD). PVS are believed to play a role in cerebral metabolic waste clearance, particularly during sleep, and emerging evidence suggests that sleep disturbances are among the earliest symptoms of dementia. However, PVS quantification remains challenging and not accessible, particularly in complex patients with neurovascular and neurodegenerative disease. We developed and validated an automated deep learning-based PVS quantification method using multi-site patient MRI with varying degrees of CSVD burden. Additionally, we examined the correlation between PVS volumes and age in patients undergoing treatment for sleep apnea. Methods: MRI (training/validation data=141; testing=15) were obtained from various multi-site studies (ONDRI, CAHHM, Leducq SVD-PVS, CAIN). We developed a deep learning convolutional neural net (CNN) model with a U-net architecture for PVS segmentation using T1-weighted images. Ground truth data used for model training were generated by first applying the RORPO filter to extract small tubular structures, then refinement of the RORPO output around WMH, followed by removal of probable non-PVS objects from the RORPO-based output using Freesurfer regions of interest, and finally manually correcting the remaining errors. After ground truth generation and model training, the final CNN output was used to examine the association between PVS volumes and age in patients with sleep apnea (n=42). Results: After CNN training, our PVS tool completes full segmentation in under 3 minutes (NVIDIA RTX3090). It achieved excellent performance on the test data, with a mean Dice score of 0.95, indicating outstanding agreement with ground truth. When applied to the patients undergoing interventional sleep apnea treatment, a strong positive relationship was found between total PVS volume and age (r=0.57 [0.38 0.72]). Discussion: Our findings suggest that our automated PVS segmentation method can quickly and accurately quantify PVS in neurodegenerative and neurovascular patients with varying degrees of CSVD burden. The strong association between age and PVS in patients with sleep apnea further demonstrates the utility of our method and underscores the importance of further investigating the role of PVS in the context of sleep, aging, and neurodegenerative processes.

The pathogenesis of cerebral small vessel disease (CSVD) is largely unknown. Endothelial disfunction has been suggested as the turning point in CSVD development. In this study, we tested the effect of plasma from CSVD patients on human cerebral microvascular endothelial cells with the aim of describing the pattern of endothelial activation. Plasma samples from three groups of young subjects have been tested: PTs (subjects affected by early stage CSVD); CTRLs (control subjects without abnormalities at MRI scanning); BDs (blood donors). Human Brain Endothelial Cells 5i (HBEC5i) were treated with plasma and total RNA was extracted. RNAs were pooled to reduce gene expression-based variability and NGS analysis was performed. Differentially expressed genes were highlighted comparing PTs, CTRLs and BDs with HBEC5i untreated cells. No significantly altered pathway was evaluated in BD-related treatment. Regulation of p38 MAPK cascade (GO:1900744) was the only pathway altered in CTRL-related treatment. Indeed, 36 different biological processes turned out to be deregulated after PT treatment of HBEC5i, i.e., the cytokine-mediated signaling pathway (GO:0019221). Endothelial cells activate inflammatory pathways in response to stimuli from CSVD patients’ plasma, suggesting the pathogenetic role of neuroinflammation from the early asymptomatic phases of cerebrovascular disease.

Cerebral small vessel disease (CSVD) refers to a spectrum of clinical and imaging findings resulting from pathological processes of various etiologies affecting cerebral arterioles, perforating arteries, capillaries, and venules. Unlike large vessels, it is a challenge to visualize small vessels in vivo, hence the difficulty to directly monitor the natural progression of the disease. CSVD might progress for many years during the early stage of the disease as it remains asymptomatic. Prevalent among elderly individuals, CSVD has been alarmingly reported as an important precursor of full-blown stroke and vascular dementia. Growing evidence has also shown a significant association between CSVD’s radiological manifestation with dementia and Alzheimer’s disease (AD) pathology. Although it remains contentious as to whether CSVD is a cause or sequelae of AD, it is not far-fetched to posit that effective therapeutic measures of CSVD would mitigate the overall burden of dementia. Nevertheless, the unifying theory on the pathomechanism of the disease remains elusive, hence the lack of effective therapeutic approaches. Thus, this chapter consolidates the contemporary insights from numerous experimental animal models of CSVD, to date: from the available experimental animal models of CSVD and its translational research value; the pathomechanical aspects of the disease; relevant aspects on systems biology; opportunities for early disease biomarkers; and finally, converging approaches for future therapeutic directions of CSVD.

Abstract Background Sleep fragmentation was shown to be positively associated with cognitive impairment in patients with cerebral small vessel disease (CSVD); however, the underlying mechanisms are not well characterized. In this study, we sought to clarify this issue by investigating the relationship between non breathing-related sleep fragmentation and brain imaging markers in patients with CSVD. Methods Eighty-four CSVD patients and 24 age- and sex-matched healthy controls were prospectively recruited. All subjects underwent 3.0 T superconducting magnetic resonance imaging and overnight polysomnography. Polysomnography parameters including sleep onset latency (SOL), total sleep time (TST); sleep efficiency (SE), wake after sleep onset (WASO), percentage of each sleep stage (N1, N2, N3 and rapid eye movement [REM]), arousal index (ArI), periodic limb movement in sleep index (PLSMI), and periodic limb movement related arousal index (PLMAI) were compared between CSVD patients and healthy controls. The relationship between arousal index and CSVD markers was explored in the CSVD group. Results On polysomnography, CSVD patients showed significantly higher ArI, WASO, PLSMI, and PLMAI, and lower sleep efficiency and N− 3 ratio compared to healthy controls (p

Abstract Background Conventional brain MRI cannot always distinguish between different white matter lesions. Susceptibility weighted imaging (SWI) can detect a sign called central vein sign which is suggested to discriminate between multiple sclerosis and other white matter lesions thus increasing the accuracy of MRI in MS diagnosis. This study aimed to evaluate the role of MR susceptibility weighted imaging in differentiating MS from CSVD lesions. Results The central vein sign (CVS) was found to have a premium diagnostic performance in diagnosis of MS with sensitivity 83.3%, specificity 70%, positive predictive value 80.6%, and negative predictive value 73.7%. When CVS positive lesions load was ≥ 44.24%, the specificity of CVS in diagnosing MS raised to 100%. Conclusion Detection of the CVS on SWI can reliably discriminate between MS and CSVD.

Competing Interests: Competing interests: None declared.

Background: Conventional brain MRI cannot always distinguish between different white matter lesions. Susceptibility weighted imaging (SWI) can detect a sign called central vein sign which is suggested to discriminate between multiple sclerosis and other white matter lesions thus increasing the accuracy of MRI in MS diagnosis. This study aimed to evaluate the role of MR susceptibility weighted imaging in differentiating MS from CSVD lesions. Results: The central vein sign (CVS) was found to have a premium diagnostic performance in diagnosis of MS with sensitivity 83.3%, specificity 70%, positive predictive value 80.6%, and negative predictive value 73.7%. When CVS positive lesions load was ≥ 44.24%, the specificity of CVS in diagnosing MS raised to 100%. Conclusion: Detection of the CVS on SWI can reliably discriminate between MS and CSVD. [ABSTRACT FROM AUTHOR]

Background: Depressive symptoms are one of the main clinical features of the cerebral small-vessel disease (CSVD). However, the pathogenesis of depressive symptoms of CSVD has not been fully studied, and a lack of effective diagnostic methodseffective diagnostic methods exists. Recently, the emerging body of evidence regarding exosomes has rendered them potentially key players in the neuropsychiatric disease theragnostic. This study's aim was to investigate serumexosome proteomic expression in CSVD patients with depressive symptoms and to screen and analyze potential biomarkers for clinical diagnosis., Methods: Serum samples were collected from 36 CSVD patients, including 18 cerebral small-vessel disease (CSVD+D) patients with depressive clinical manifestations and 18 cerebral small-vessel disease patients that did not present depression-related clinical manifestations (CSVD-D). This investigation employed tandem mass tag (TMT) combined with mass spectrometry for sample detection and quantitative analysis of proteins. The differential proteins with significant dysregulated expression levels in patient plasma exosomes were screened and analyzed through bioinformatics techniques., Results: This investigation focused on a global collection of 659 quantifiable proteins. Compared to the CSVD-D group, 7 up-regulated and 30 down-regulated proteins were identified in the CSVD+D group (P < 0.05). Gene ontology (GO) enrichment analyses revealed proteomic expression profile dysregulations within serum exosomes in patients with depression, such as desmosomes and keratins, rendering them as potential biomarkers. Kyoto encyclopedia of genes and genomes (KEGG) database investigations revealed the differentially expressed proteins to be highly aggregated within the estrogen signaling pathway., Conclusion: This investigation pioneered TMT proteomic evaluation of serum exosomes within CSVD patients suffering from depression and reveals the shifts in proteomic expression profiles by serum exosomes within such patients. This study identified several important molecular / signal pathway abnormalities related to depression. These results provide a possible means to further clarify the pathogenesis of depressive symptoms of cerebrovascular disease and its diagnosis and treatment in the future., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

BackgroundCerebral Microbleeds (CMBs) serve as critical indicators of cerebral small vessel disease and are strongly associated with severe neurological disorders, including cognitive impairments, stroke, and dementia. Despite the importance of diagnosing and preventing CMBs, there is a significant lack of effective predictive tools in clinical settings, hindering comprehensive assessment and timely intervention.ObjectiveThis study aims to develop a robust predictive model for CMBs by integrating a broad range of clinical and laboratory parameters, enhancing early diagnosis and risk stratification.MethodsWe analyzed extensive data from 587 neurology inpatients using advanced statistical techniques, including Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression. Key predictive factors such as Albumin/Globulin ratio, gender, hypertension, homocysteine levels, Neutrophil to HDL Ratio (NHR), and history of stroke were evaluated. Model validation was performed through Receiver Operating Characteristic (ROC) curves and Decision Curve Analysis (DCA).ResultsThe model demonstrated strong predictive performance with significant clinical applicability. Key predictors identified include the Albumin/Globulin ratio, homocysteine levels, and NHR, among others. Validation metrics such as the area under the ROC curve (AUC) and decision curve analysis confirmed the model’s utility in predicting CMBs, highlighting its potential for clinical implementation.ConclusionThe comprehensive predictive model developed in this study offers a significant advancement in the personalized management of patients at risk for CMBs. By addressing the gap in effective predictive tools, this model facilitates early diagnosis and targeted intervention, potentially reducing the incidence of stroke and cognitive impairments associated with cerebral microbleeds. Our findings advocate for a more nuanced approach to cerebrovascular disease management, emphasizing the importance of multi-factorial risk profiling.

BackgroundLacunes, a characteristic feature of cerebral small vessel disease (CSVD), are critical public health concerns, especially in the aging population. Traditional neuroimaging techniques often fall short in early lacune detection, prompting the need for more precise predictive models.MethodsIn this retrospective study, 587 patients from the Neurology Department of the Affiliated Hospital of Hebei University who underwent cranial MRI were assessed. A nomogram for predicting lacune incidence was developed using LASSO regression and binary logistic regression analysis for variable selection. The nomogram’s performance was quantitatively assessed using AUC-ROC, calibration plots, and decision curve analysis (DCA) in both training (n = 412) and testing (n = 175) cohorts.ResultsIndependent predictors identified included age, gender, history of stroke, carotid atherosclerosis, hypertension, creatinine, and homocysteine levels. The nomogram showed an AUC-ROC of 0.814 (95% CI: 0.791–0.870) for the training set and 0.805 (95% CI: 0.782–0.843) for the testing set. Calibration and DCA corroborated the model’s clinical value.ConclusionThis study introduces a clinically useful nomogram, derived from binary logistic regression, that significantly enhances the prediction of lacunes in patients undergoing brain MRI for various indications, potentially advancing early diagnosis and intervention. While promising, its retrospective design and single-center context are limitations that warrant further research, including multi-center validation.

Abstract Vascular risk factors such as chronic hypertension are well-established major modifiable factors for the development of cerebral small vessel disease (cSVD). In the present study, our focus was the investigation of cSVD-related phenotypic changes in microglia in human disease and in the spontaneously hypertensive stroke-prone rat (SHRSP) model of cSVD. Our examination of cortical microglia in human post-mortem cSVD cortical tissue revealed distinct morphological microglial features specific to cSVD. We identified enlarged somata, an increase in the territory occupied by thickened microglial processes, and an expansion in the number of vascular-associated microglia. In parallel, we characterized microglia in a rodent model of hypertensive cSVD along different durations of arterial hypertension, i.e., early chronic and late chronic hypertension. Microglial somata were already enlarged in early hypertension. In contrast, at late-stage chronic hypertension, they further exhibited elongated branches, thickened processes, and a reduced ramification index, mirroring the findings in human cSVD. An unbiased multidimensional flow cytometric analysis revealed phenotypic heterogeneity among microglia cells within the hippocampus and cortex. At early-stage hypertension, hippocampal microglia exhibited upregulated CD11b/c, P2Y12R, CD200R, and CD86 surface expression. Detailed analysis of cell subpopulations revealed a unique microglial subset expressing CD11b/c, CD163, and CD86 exclusively in early hypertension. Notably, even at early-stage hypertension, microglia displayed a higher association with cerebral blood vessels. We identified several profound clusters of microglia expressing distinct marker profiles at late chronic hypertensive states. In summary, our findings demonstrate a higher vulnerability of the hippocampus, stage-specific microglial signatures based on morphological features, and cell surface protein expression in response to chronic arterial hypertension. These results indicate the diversity within microglia sub-populations and implicate the subtle involvement of microglia in cSVD pathogenesis.

BackgroundCerebral small vessel disease (CSVD) is a significant contributor to stroke, intracerebral hemorrhages, and vascular dementia, particularly in the elderly. Early diagnosis remains challenging. This study aimed to develop and validate a novel nomogram for the early diagnosis of cerebral small vessel disease (CSVD). We focused on integrating cerebrovascular risk factors and blood biochemical markers to identify individuals at high risk of CSVD, thus enabling early intervention.MethodsIn a retrospective study conducted at the neurology department of the Affiliated Hospital of Hebei University from January 2020 to June 2022, 587 patients were enrolled. The patients were randomly divided into a training set (70%, n = 412) and a validation set (30%, n = 175). The nomogram was developed using multivariable logistic regression analysis, with variables selected through the Least Absolute Shrinkage and Selection Operator (LASSO) technique. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).ResultsOut of 88 analyzed biomarkers, 32 showed significant differences between the CSVD and non-CSVD groups. The LASSO regression identified 12 significant indicators, with nine being independent clinical predictors of CSVD. The AUC-ROC values of the nomogram were 0.849 (95% CI: 0.821–0.894) in the training set and 0.863 (95% CI: 0.810–0.917) in the validation set, indicating excellent discriminative ability. Calibration plots demonstrated good agreement between predicted and observed probabilities in both sets. DCA showed that the nomogram had significant clinical utility.ConclusionsThe study successfully developed a nomogram predictive model for CSVD, incorporating nine clinical predictive factors. This model offers a valuable tool for early identification and risk assessment of CSVD, potentially enhancing clinical decision-making and patient outcomes.

Background and purposeThe angiotensin-converting enzyme (ACE) insertion (I)/deletion (D) polymorphism has been studied as a genetic candidate for cerebral small vessel disease (CSVD). However, no previous study has evaluated the relationship between the ACE I/D polymorphism and cerebral microbleed (CMB), an important CSVD marker. We evaluated the association between ACE I/D polymorphisms and 2-year changes in CMBs.MethodsThe CHALLENGE (Comparison Study of Cilostazol and Aspirin on Changes in Volume of Cerebral Small Vessel Disease White Matter Changes) database was analyzed. Of 256 subjects, 186 participants who underwent a 2-year follow-up brain scan and ACE genotyping were included. Our analysis was conducted by dividing the ACE genotype into two groups (DD vs. ID/II) under the assumption of the recessive effects of the D allele. A linear mixed-effect model was used to compare the 2-year changes in the number of CMBs between the DD and combined ID/II genotypes.ResultsAmong 186 patients included in this study, 24 (12.9%) had the DD genotype, 91 (48.9%) had the ID genotype, and 71 (38.2%) had the II genotype. Baseline clinical characteristics and cerebral small vessel disease markers were not different between the two groups (DD vs. ID/II) except for the prevalence of hypertension (DD 66.7% vs. ID/II 84.6%; p = 0.04). A multivariate linear mixed-effects model showed that the DD carriers had a greater increase in total CMB counts than the ID/II carriers after adjusting for the baseline number of CMBs, age, sex, and hypertension (estimated mean of difference [standard error (SE)] = 1.33 [0.61]; p = 0.03). When we performed an analysis of cases divided into deep and lobar CMBs, only lobar CMBs were significantly different between the two groups (estimated mean of difference [SE] = 0.94 [0.42]; p = 0.02).ConclusionThe progression of CMBs over 2 years was greater in the ACE DD carriers compared with the combined II/ID carriers. The results of our study indicate a possible association between the ACE I/D polymorphism and CMB. A study with a larger sample size is needed to confirm this association.

Although a portion of patients with cerebral small vessel disease (CSVD) present mental disorders, there is currently a lack of appropriate technologies to evaluate brain functions that are relevant to neurovascular coupling. Furthermore, there are no established objective criteria for diagnosing and distinguishing CSVD-induced mental disorders and psychiatric diseases. In this study, we report the first comprehensive investigation of the cerebral hemodynamics of CSVD patients who also presented with mental disorders. Two CSVD patients with similar magnetic resonance imaging (MRI) outcomes but with non-identical mental symptoms participated in this study. The patients were instructed to perform the verbal fluency task (VFT), high-level cognition task (HCT), as well as voluntary breath holding (VBH). A functional near-infrared spectroscopy (fNIRS) was used to measure the cerebral oxygenation responses. Additionally, a diffuse correlation spectroscopy (DCS) was used to measure the cerebral blood flow (CBF) responses. Both technologies were also applied to a healthy subject for comparison. The fNIRS results showed that both CSVD patients presented abnormal cerebral oxygenation responses during the VFT, HCT, and VBH tasks. Moreover, the patient with cognition impairment showed fluctuations in CBF during these tasks. In contrast, the patient without cognition impairment mostly presented typical CBF responses during the tasks, which was consistent with the healthy subject. The cognitive impairment in CSVD patients may be due to the decoupling of the neurons from the cerebrovascular, subsequently affecting the autoregulation capacity. The results of the fNIRS and DCS combined provide a comprehensive evaluation of the neurovascular coupling and, hence, offer great potential in diagnosing cerebrovascular or psychiatric diseases.

BackgroundCerebral small vessel disease (CSVD) attaches people’s attention in recent years. In this study, we aim to explore retinal structure and vessel density changes in CSVD patients.MethodsWe collected information on retinal metrics assessed by optical coherence tomography (OCT) and OCT angiography and CSVD characters. Logistic and liner regression was used to analyze the relationship between retinal metrics and CSVD.ResultsVessel density of superficial retinal capillary plexus (SRCP), foveal density- 300 length (FD-300), radial peripapillary capillary (RPC) and thickness of retina were significantly lower in CSVD patients, the difference only existed in the thickness of retina after adjusted relevant risk factors (OR (95% CI): 0.954 (0.912, 0.997), p = 0.037). SRCP vessel density showed a significant downward trend with the increase of CSVD scores (β: −0.087, 95%CI: −0.166, −0.008, p = 0.031). SRCP and FD-300 were significantly lower in patients with lacunar infarctions and white matter hypertensions separately [OR (95% CI): 0.857 (0.736, 0.998), p = 0.047 and OR (95% CI): 0.636 (0.434, 0.932), p = 0.020, separately].ConclusionSRCP, FD-300 and thickness of retina were associated with the occurrence and severity of total CSVD scores and its different radiological manifestations. Exploring CSVD by observing alterations in retinal metrics has become an optional research direction in future.

Multiple sclerosis (MS) is a condition that affects the veins and small blood vessels. Previous research suggests that individuals with MS have an increased risk of vascular events and higher mortality rates. However, the relationship between MS and cerebral small vessel disease (CSVD) remains uncertain. This study aims to investigate the association between MS and lacunes. A prospective observational study was conducted, including a total of 112 participants, of which 46 had MS and 66 had CSVD. All participants underwent an MRI scan and a battery of neurological functional assessments. The presence of definite lacunes and black holes was determined through the analysis of T2-weighted, T1-weighted, and FLAIR images. The occurrence of lacunes in MS patients was found to be 19.6%. Notably, the duration of MS was identified as the sole risk factor for the development of lacune lesions in MS patients [odds ratio (OR) = 1.3, 95% confidence interval (CI) = 1.1–1.6, p = 0.008]. Comparatively, MS patients with lacunes exhibited a higher frequency of attacks and larger volumes of T2 lesions compared to MS patients without lacunes. Further analysis using receiver operating characteristic (ROC) curves showed that lacune lesions had limited ability to discriminate between MS and CSVD when disease duration exceeded 6 years. The presence of small arterial lesions in the brain of individuals with MS, along with the duration of the disease, contributes to the development of lacunes in MS patients.

BackgroundCerebral microbleeds (MBs) are a hallmark of cerebral small vessel disease (CSVD) and can be found on T2*-weighted sequences on MRI. Quantitative susceptibility mapping (QSM) is a postprocessing method that also enables MBs identification and furthermore allows to differentiate them from calcifications.AimsWe explored the implications of using QSM at submillimeter resolution for MBs detection in CSVD.MethodsBoth 3 and 7 Tesla (T) MRI were performed in elderly participants without MBs and patients with CSVD. MBs were quantified on T2*-weighted imaging and QSM. Differences in the number of MBs were assessed, and subjects were classified in CSVD subgroups or controls both on 3T T2*-weighted imaging and 7T QSM.Results48 participants [mean age (SD) 70.9 (8.8) years, 48% females] were included: 31 were healthy controls, 6 probable cerebral amyloid angiopathy (CAA), 9 mixed CSVD, and 2 were hypertensive arteriopathy [HA] patients. After accounting for the higher number of MBs detected at 7T QSM (Median = Mdn; Mdn7T−QSM = 2.5; Mdn3T−T2 = 0; z = 4.90; p < 0.001) and false positive MBs (6.1% calcifications), most healthy controls (80.6%) demonstrated at least one MB and more MBs were discovered in the CSVD group.ConclusionsOur observations suggest that QSM at submillimeter resolution improves the detection of MBs in the elderly human brain. A higher prevalence of MBs than so far known in healthy elderly was revealed.

BackgroundWhite matter hyperintensities (WMH) are a key imaging feature of cerebral small-vessel disease (CSVD). However, there is a lack of standardized methods for determining WMH volume, and the value of total white matter (WM) volume in the assessment of cognitive impairment in patients with CSVD remains unknown.ObjectiveWe aimed to explore the correlations of WMH volume and WM volume with cognitive dysfunction and its components in patients with CSVD. We also aimed to compare the value of the Fazekas score, WMH volume, and ratio of WMH volume to total WM volume in the assessment of cognitive dysfunction.MethodsThe study included 99 patients with CSVD. Patients were categorized into following groups based on MoCA scores: patients with mild cognitive impairment and those without. Brain magnetic resonance images were processed to investigate differences in WMH and WM volumes between the groups. Logistic regression analysis was used to determine whether these two factors were independent risk factors for cognitive dysfunction. Correlation analysis was used to examine the relationships of WMH and WM volume with different types of cognitive impairment. Receiver operating characteristic curves were used to compare the effectiveness of the WMH score, WMH volume, and WMH to WM ratio for evaluating cognitive dysfunction.ResultsThere were significant differences in age, education level, WMH volume, and WM volume between the groups (P < 0.05). After adjusting for age and education, the multivariate logistic analysis indicated that both WMH volume and WM volume were independent risk factors for cognitive dysfunction. Correlation analysis indicated that WMH volume was mainly related to cognition involving the visual space and delayed recall. WM volume was not strongly associated with different types of cognitive dysfunction. The WMH to WM ratio was the strongest predictor, with an area under the curve value of 0.800 and a 95% confidence interval of 0.710–0.891.ConclusionIncreases in WMH volume may aggravate cognitive dysfunction in patients with CSVD, and a higher WM volume may reduce the effect of WMH volume on cognitive function to a certain extent. The ratio of WMH to total WM volume may reduce the impact of brain atrophy, allowing for more accurate evaluation of cognitive dysfunction in older adults with CSVD.

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Copyright of Chinese Journal of Stroke is the property of Chinese Journal of Stroke Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background and objectiveThe blood neutrophil/lymphocyte ratio (NLR) is an objective and convenient parameter of systemic inflammation. Elevated NLR is associated with an increased risk of mild cognitive impairment (CI) in the elderly. However, few data are available on the impact of the NLR on CI in patients with cerebral small vessel disease (CSVD).MethodsA total of 66 CSVD subjects with CI and 81 CSVD subjects without CI were evaluated in this study. Clinical, laboratory, radiological, and cognitive parameters were collected. The NLR was obtained with the absolute neutrophil count being divided by the absolute lymphocyte count in fasting blood samples. Logistic regression analysis was performed to evaluate the factors associated with CI. Receiver operating characteristic curves were illustrated to predict factors associated with CI in patients with CSVD.ResultsThe NLR of the CI group was significantly higher than that of subjects without CI (2.59 vs. 2.21, P = 0.003). In multivariate analysis, NLR was positively correlated to the CI (OR: 1.43, 95% CI: 1.05–1.96, P = 0.024). It was suggested that the optimum NLR cutoff point for CI was 1.89 with 69.7% sensitivity and 59.3% specificity. Subjects with NLR ≥ 1.89 showed higher possibilities of CI compared to those with NLR < 1.89 (OR: 3.38, 95% CI: 1.62–7.07).ConclusionsCorrelations were found between NLR and CI. Patients with CSVD who have higher NLR might have an increased risk of CI.