Neuroimaging and neuropathology indices of cerebrovascular disease burden

A novel perspective for exploring the relationship between cerebral small vessel disease and deep medullary veins with automatic segmentation

BACKGROUND

This study aimed to establish an intelligent segmentation algorithm to count the number of deep medullary veins (DMVs) and analyze the relationship between DMVs and imaging markers of cerebral small vessel disease (CSVD).

METHODS

DMVs on magnetic resonance imaging (MRI) of patients with CSVD were counted by intelligent segmentation and manual counting. The dice coefficient and intraclass correlation coefficient (ICC) were used to evaluate their consistency and correlation. Structural MR images were used to assess imaging markers and total burden of CSVD. A multivariate linear regression model was used to evaluate the correlation between the number of DMVs counted by intelligent segmentation and imaging markers of CSVD, including white matter hyperintensities of the presumed vascular origin, lacune, perivascular spaces, cerebral microbleeds, and total CSVD burden.

RESULTS

A total of 305 patients with CSVD were enrolled. An intelligent segmentation algorithm was established to calculate the number of DMVs, and it was validated and tested. The number of DMVs counted intelligently significantly correlated with the manual counting method (r = 0.761, P< 0.001). The number of smart-counted DMVs negatively correlated with the imaging markers and total burden of CSVD (P< 0.001), and the correlation remained after adjusting for age and hypertension (P< 0.05).

CONCLUSIONS

The proposed intelligent segmentation algorithm, which was established to count DMVs, can provide objective and quantitative imaging information for the follow-up of patients with CSVD. DMVs are involved in CSVD pathogenesis and a likely new imaging marker for CSVD.

Cerebral small vessel disease and stroke: Linked by stroke aetiology, but not stroke lesion location or size

BACKGROUND

Cerebral small vessel disease (SVD) has previously been associated with worse stroke outcome, vascular dementia, and specific post-stroke cognitive deficits. The underlying causal mechanisms of these associations are not yet fully understood. We investigated whether a relationship between SVD and certain stroke aetiologies or a specific stroke lesion anatomy provides a potential explanation.

METHODS

In a retrospective observational study, we examined 859 patients with first-ever, non-SVD anterior circulation ischemic stroke (age = 69.0±15.2). We evaluated MRI imaging markers to assess an SVD burden score and mapped stroke lesions on diffusion-weighted MRI. We investigated the association of SVD burden with i) stroke aetiology, and ii) lesion anatomy using topographical statistical mapping.

RESULTS

With increasing SVD burden, stroke of cardioembolic aetiology was more frequent (ρ = 0.175; 95 %-CI = 0.103;0.244), whereas cervical artery dissection (ρ = -0.143; 95 %-CI = -0.198;-0.087) and a patent foramen ovale (ρ = -0.165; 95 %-CI = -0.220;-0.104) were less frequent stroke etiologies. However, no significant associations between SVD burden and stroke aetiology remained after additionally controlling for age (all p>0.125). Lesion-symptom-mapping and Bayesian statistics showed that SVD burden was not associated with a specific stroke lesion anatomy or size.

CONCLUSIONS

In patients with a high burden of SVD, non-SVD stroke is more likely to be caused by cardioembolic aetiology. The common risk factor of advanced age may link both pathologies and explain some of the existing associations between SVD and stroke. The SVD burden is not related to a specific stroke lesion location.

A typology of cerebral small vessel disease based on imaging markers

BACKGROUND

Lacunes, microbleeds, enlarged perivascular spaces (EPVS), and white matter hyperintensities (WMH) are brain imaging features of cerebral small vessel disease (SVD). Based on these imaging markers, we aimed to identify subtypes of SVD and to evaluate the validity of these markers as part of clinical ratings and as biomarkers for stroke outcome.

METHODS

In a cross-sectional study, we examined 1207 first-ever anterior circulation ischemic stroke patients (mean age 69.1 ± 15.4 years; mean NIHSS 5.3 ± 6.8). On acute stroke MRI, we assessed the numbers of lacunes and microbleeds and rated EPVS and deep and periventricular WMH. We used unsupervised learning to cluster patients based on these variables.

RESULTS

We identified five clusters, of which the last three appeared to represent distinct late stages of SVD. The two largest clusters had no to only mild or moderate WMH and EPVS, respectively, and favorable stroke outcome. The third cluster was characterized by the largest number of lacunes and a likewise favorable outcome. The fourth cluster had the highest age, most pronounced WMH, and poor outcome. Showing the worst outcome, the fifth cluster presented pronounced microbleeds and the most severe SVD burden.

CONCLUSION

The study confirmed the existence of different SVD types with different relationships to stroke outcome. EPVS and WMH were identified as imaging features of presumably early progression. The number of microbleeds and WMH severity appear to be promising biomarkers for distinguishing clinical subgroups. Further understanding of SVD progression might require consideration of refined SVD features, e.g., for EPVS and type of lacunes.

Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning

Background

Cerebrovascular disease (CeVD) is a prominent contributor to global mortality and profound disability. Extensive research has unveiled a connection between CeVD and retinal microvascular abnormalities. Nonetheless, manual analysis of fundus images remains a laborious and time-consuming task. Consequently, our objective is to develop a risk prediction model that utilizes retinal fundus photo to noninvasively and accurately assess cerebrovascular risks.

Materials and methods

To leverage retinal fundus photo for CeVD risk evaluation, we proposed a novel model called Efficient Attention which combines the convolutional neural network with attention mechanism. This combination aims to reinforce the salient features present in fundus photos, consequently improving the accuracy and effectiveness of cerebrovascular risk assessment.

Result

Our proposed model demonstrates notable advancements compared to the conventional ResNet and Efficient-Net architectures. The accuracy (ACC) of our model is 0.834 ± 0.03, surpassing Efficient-Net by a margin of 3.6%. Additionally, our model exhibits an improved area under the receiver operating characteristic curve (AUC) of 0.904 ± 0.02, surpassing other methods by a margin of 2.2%.

Conclusion

This paper provides compelling evidence that Efficient-Attention methods can serve as effective and accurate tool for cerebrovascular risk. The results of the study strongly support the notion that retinal fundus photo holds great potential as a reliable predictor of CeVD, which offers a noninvasive, convenient and low-cost solution for large scale screening of CeVD.

The essential role of neuroimaging in diagnosing and managing cerebrovascular disease in Africa: a review

BACKGROUND

Cerebrovascular disease is a significant cause of morbidity and mortality in Africa, and using neuroimaging techniques has improved the diagnosis and management of this disease. However, there is a lack of comprehensive reviews of the role and effectiveness of neuroimaging techniques in the African context.

METHODS

We reviewed the literature to evaluate the role of neuroimaging in diagnosing and managing cerebrovascular disease in Africa. Our search included electronic databases such as PubMed, Scopus, and Google Scholar from 2000 to April 2023. We included peer-reviewed studies written in English that reported on the use of neuroimaging in diagnosing and managing cerebrovascular disease in African populations. We excluded non-peer-reviewed articles, letters, editorials, and studies unrelated to cerebrovascular disease, neuroimaging, or Africa. A total of 102 potential articles were identified; after applying our exclusion criteria and removing duplicated articles, 51 articles were reviewed.

RESULTS

Our findings suggest that neuroimaging techniques such as CT, MRI, and Skull x-ray play a crucial role in diagnosing and managing cerebrovascular disease in Africa. CT and MRI were the most commonly used techniques, with CT being more widely available and less expensive than MRI. However, challenges to using neuroimaging in Africa include the high cost of equipment and maintenance, lack of trained personnel, and inadequate infrastructure. These challenges limit the widespread use of neuroimaging in diagnosing and managing cerebrovascular disease in Africa.

CONCLUSION

Neuroimaging techniques are essential for diagnosing and managing cerebrovascular disease in Africa, but challenges to their use must be addressed to improve healthcare outcomes. Our policy recommendations can help improve the availability and accessibility of neuroimaging services in Africa.

Brain and Cognition Signature Fingerprinting Vascular Health in Diabetic Individuals: An International Multi-Cohort Study

OBJECTIVE

To evaluate the correlation between cognitive signatures and the risk of diabetic vascular complications and mortality, based on a multicountry prospective study.

METHODS

The participants comprised 27,773 diabetics from the UK Biobank (UKB) and 1307 diabetics from the Guangzhou Diabetic Eye Study (GDES) cohort. The exposures were brain volume and cognitive screening tests for UKB participants, whilst the global cognitive score (GCS) measuring orientation to time and attention, episodic memory, and visuospatial abilities were determined for GDES participants. The outcomes for the UKB group were mortality, as well as macrovascular (myocardial infarction [MI] and stroke), microvascular (end-stage renal disease [ESRD], and diabetic retinopathy [DR]) events. The outcomes for the GDES group were retinal and renal microvascular damage.

RESULTS

In the UKB group, a 1-SD reduction in brain gray matter volume was associated with 34%-77% higher risks of incident MI, ESRD, and DR. The presence of impaired memory was associated with 18%-73% higher risk of mortality and ESRD; impaired reaction was associated with 1.2-1.7-fold higher risks of mortality, stroke, ESRD, and DR. In the GDES group, the lowest GCS tertile exhibited 1.4-2.2-fold higher risk of developing referable DR and a twofold faster decline in renal function and retinal capillary density compared with the highest tertile. Restricting data analysis to individuals aged less than 65 years produced consistent results.

CONCLUSION

Cognitive decline significantly elevates the risk of diabetic vascular complications and is correlated with retinal and renal microcirculation damage. Cognitive screening tests are strongly recommended as routine tools for management of diabetes.

Neuroimaging standards for research into small vessel disease-advances since 2013

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Correlation of CT perfusion with MRI brain in symptomatic carotid artery stenosis

Background

Cerebral white matter disease and large vessel cerebral steno-occlusive are both associated with high incidence of strokes and mortality. There is a lack of literature correlating the cerebral perfusion downstream of a stenotic lesion with white matter changes in the cerebral hemispheres. The aim of this study was to correlate the white matter changes in magnetic resonance imaging (MRI) with computed tomography (CT) perfusion parameters in patients with symptomatic carotid stenosis.

Methods

A total of 50 patients with symptomatic carotid stenosis underwent MRI brain and CT Perfusion. Percentage differences in cerebral blood flow (CBF) and mean transit time (MTT) were correlated with symmetric and asymmetric small vessel ischemic disease (SVID) on MRI. Receiver operating characteristic (ROC) curve analysis was performed to determine sensitivity and specificity for different values of percentage CBF and MTT difference.

Results

A total of 17 patients with symmetrical SVID had a mean CBF difference of 6.58 (SD of 3.17) and mean MTT difference of 11.61 (SD of 4.32). 33 patients with asymmetrical SVID had a mean CBF difference of 34.73 (SD of 6.87) and mean MTT difference of 44.63 (SD of 9.12). ROC curve analysis showed percentage CBF and MTT differences of 12.5% and 26.5% respectively to be associated with 100% specificity and sensitivity.

Conclusion

In patients with symptomatic carotid stenosis, CT perfusion parameters correlate with MRI features of SVID.

The contribution of white matter pathology, hypoperfusion, lesion load, and stroke recurrence to language deficits following acute subcortical left hemisphere stroke

Aphasia, the loss of language ability following damage to the brain, is among the most disabling and common consequences of stroke. Subcortical stroke, occurring in the basal ganglia, thalamus, and/or deep white matter can result in aphasia, often characterized by word fluency, motor speech output, or sentence generation impairments. The link between greater lesion volume and acute aphasia is well documented, but the independent contributions of lesion location, cortical hypoperfusion, prior stroke, and white matter degeneration (leukoaraiosis) remain unclear, particularly in subcortical aphasia. Thus, we aimed to disentangle the contributions of each factor on language impairments in left hemisphere acute subcortical stroke survivors. Eighty patients with acute ischemic left hemisphere subcortical stroke (less than 10 days post-onset) participated. We manually traced acute lesions on diffusion-weighted scans and prior lesions on T2-weighted scans. Leukoaraiosis was rated on T2-weighted scans using the Fazekas et al. (1987) scale. Fluid-attenuated inversion recovery (FLAIR) scans were evaluated for hyperintense vessels in each vascular territory, providing an indirect measure of hypoperfusion in lieu of perfusion-weighted imaging. We found that language performance was negatively correlated with acute/total lesion volumes and greater damage to substructures of the deep white matter and basal ganglia. We conducted a LASSO regression that included all variables for which we found significant univariate relationships to language performance, plus nuisance regressors. Only total lesion volume was a significant predictor of global language impairment severity. Further examination of three participants with severe language impairments suggests that their deficits result from impairment in domain-general, rather than linguistic, processes. Given the variability in language deficits and imaging markers associated with such deficits, it seems likely that subcortical aphasia is a heterogeneous clinical syndrome with distinct causes across individuals.

Comorbidity of Cerebrovascular and Alzheimer's Disease in Aging

BACKGROUND

Cerebrovascular disease often coexists with Alzheimer's disease (AD). While both diseases share common risk factors, their interrelationship remains unclear. Increasing the understanding of how cerebrovascular changes interact with AD is essential to develop therapeutic strategies and refine biomarkers for early diagnosis.

OBJECTIVE

We investigate the prevalence and risk factors for the comorbidity of amyloid-β (Aβ) and cerebrovascular disease in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing, and further examine their cross-sectional association.

METHODS

A total of 598 participants (422 cognitively normal, 89 with mild cognitive impairment, 87 with AD) underwent positron emission tomography and structural magnetic resonance imaging for assessment of Aβ deposition and cerebrovascular disease. Individuals were categorized based on the comorbidity status of Aβ and cerebrovascular disease (V) as Aβ-V-, Aβ-V+, Aβ+V-, or Aβ+V+.

RESULTS

Advancing age was associated with greater likelihood of cerebrovascular disease, high Aβ load and their comorbidity. Apolipoprotein E ɛ4 carriage was only associated with Aβ positivity. Greater total and regional WMH burden were observed in participants with AD. However, no association were observed between Aβ and WMH measures after stratification by clinical classification, suggesting that the observed association between AD and cerebrovascular disease was driven by the common risk factor of age.

CONCLUSION

Our observations demonstrate common comorbid condition of Aβ and cerebrovascular disease in later life. While our study did not demonstrate a convincing cross-sectional association between Aβ and WMH burden, future longitudinal studies are required to further confirm this.

Classification differentiates clinical and neuroanatomic features of cerebral small vessel disease

Age-related cerebral small vessel disease involves heterogeneous pathogenesis, such as arteriosclerosis/lipohyalinosis and cerebral amyloid angiopathy. MRI can visualize the brain lesions attributable to small vessel disease pathologies, including white-matter hyperintensities, lacune and cerebral microbleeds. However, these MRI markers usually coexist in small vessel disease of different aetiologies. Currently, there is no available classification integrating these neuroimaging markers for differentiating clinical and neuroanatomic features of small vessel disease yet. In this study, we tested whether our proposed stratification scheme could characterize specific clinical, neuroanatomic and potentially pathogenesis/aetiologies in classified small vessel disease subtypes. Cross-sectional analyses from a community-based non-demented non-stroke cohort consisting of ≥50 years old individuals were conducted. All participants were scanned 3T brain MRI for small vessel disease detection and neuroanatomic measurements and underwent physical and cognitive assessments. Study population were classified into robust and four small vessel disease groups based on imaging markers indicating (i) bleeding or non-bleeding; (ii) specific location of cerebral microbleeds; and (iii) the severity and combination of white-matter hyperintensities and lacune. We used whole-brain voxel-based morphometry analyses and tract-based spatial statistics to evaluate the regional grey-matter volume and white-matter microstructure integrity for comparisons among groups. Among the 735 participants with eligible brain MRI images, quality screening qualified 670 for grey-matter volume analyses and 617 for white-matter microstructural analyses. Common and distinct patterns of the clinical and neuroimaging manifestations were found in the stratified four small vessel disease subgroups. Hierarchical clustering analysis revealed that small vessel disease type 4 had features distinct from the small vessel disease types 1, 2 and 3. Abnormal white-matter microstructures and cognitive function but preserved physical function and grey-matter volume were found in small vessel disease type 4. Among small vessel disease types 1, 2 and 3, there were similar characteristics but different severity; the clinical features showed both physical frail and cognitive impairment and the neuroanatomic features revealed frontal–subcortical white-matter microstructures and remote, diffuse cortical abnormalities. This novel stratification scheme highlights the distinct clinical and neuroanatomic features of small vessel disease and the possible underlying pathogenesis. It could have potential application in research and clinical settings.

Cognitive Impairment in Patients with Stroke

Despite substantial advances in stroke care, vascular cognitive impairment remains a prominent source of disability. Unlike sensorimotor impairments, cognition often continues to decline after stroke. An aging population will increase the prevalence of vascular cognitive impairment, with stroke playing an important role. Ten percent of patients presenting with stroke have pre-stroke dementia; an additional 10% will develop incident dementia with a first stroke, and 30% with a recurrent stroke. While stroke increases the risk of cognitive impairment, the presence of cognitive impairment also impacts acute stroke treatment and increases risk of poor outcome by nearly twofold. There is substantial overlap in the clinical and pathological aspects of vascular and degenerative dementias in many patients. How they relate to one another is controversial. The treatment of vascular cognitive impairment remains supportive, focusing on treating vascular risk factors. Cognitive rehabilitation after stroke is an area of active research, and existing pharmacologic treatments have limited benefit. Heightened awareness of cognitive impairment in the setting of stroke is imperative for prognostication and management, impetus for research and, ultimately, the discovery of efficacious treatments.

Positive effects of resilience and self-efficacy on World Health Organization Quality of Life Instrument score among caregivers of stroke inpatients in China

AIM

Stroke is one of the major health challenges affecting life expectancy and quality of life around the world. However, there is limited reporting on the status of some caregivers, including Chinese caregivers of stroke inpatients. Limited information is available on evaluations using the World Health Organization Quality of Life Instrument (WHOQOL) and the effects of resilience and self-efficacy on WHOQOL score. Therefore, we conducted research to assess the role of resilience on the WHOQOL and to investigate the role of self-efficacy as a mediator between resilience and WHOQOL score among Chinese caregivers of stroke inpatients.

METHODS

This cross-sectional study to gather data from north-east and south-east China was conducted from June 2019 to October 2019. Over 380 caregivers of stroke inpatients at two general public hospitals were interviewed face-to-face. About 305 caregivers (80.26%) completed the questionnaire, which included the Ego Resilience Scale, the General Self-Efficacy Scale, and the brief version of the WHOQOL and asked about demographic characteristics. This study also examined factors associated with WHOQOL score and used linear regression analysis and structure equation modelling to construct direct and indirect models, respectively.

RESULTS

After adjustment for demographic characteristics, both resilience and self-efficacy were positively associated with all WHOQOL domains. Structure equation modelling revealed that self-efficacy mediated the relationship between resilience and WHOQOL score among caregivers of stroke inpatients.

CONCLUSION

Chinese caregivers of stroke inpatients exhibited good social health but poor physical, psychological, and environmental health. It is necessary for promoting resilience and improving WHOQOL score through the mediating effect of self-efficacy. These results suggest that interventions in health care focused on both enhancing resilience and providing self-efficacy training could effectively improve WHOQOL score.

White Matter Hyperintensities Contribute to Language Deficits in Primary Progressive Aphasia

OBJECTIVE

To determine the contribution of white matter hyperintensities (WMH) to language deficits while accounting for cortical atrophy in individuals with primary progressive aphasia (PPA).

METHOD

Forty-three individuals with PPA completed neuropsychological assessments of nonverbal semantics, naming, and sentence repetition plus T2-weighted and fluid-attenuated inversion recovery scans. Using three visual scales, we rated WMH and cerebral ventricle size for both scan types. We used Spearman correlations to evaluate associations between the scales and scans. To test whether visual ratings-particularly of WMH-are associated with language, we compared a base model (including gray matter component scores obtained via principal component analysis, age, and days between assessment and MRI as independent variables) with full models (ie, the base model plus visual ratings) for each language variable.

RESULTS

Visual ratings were significantly associated within and between scans and were significantly correlated with age but not with other vascular risk factors. Only the T2 scan ratings were associated with language abilities. Specifically, controlling for other variables, poorer naming was significantly related to larger ventricles (P = 0.033) and greater global (P = 0.033) and periventricular (P = 0.049) WMH. High global WMH (P = 0.034) were also correlated with worse sentence repetition skills.

CONCLUSION

Visual ratings of global brain health were associated with language deficits in PPA independent of cortical atrophy and age. While WMH are not unique to PPA, measuring WMH in conjunction with cortical atrophy may elucidate more accurate brain structure-behavior relationships in PPA than cortical atrophy measures alone.

White-matter hyperintensities in patients with carotid artery stenosis: An exploratory connectometry study

BACKGROUND

White-matter lesions (WMLs) are frequently found in magnetic resonance imaging (MRi), and the WML load tends to be higher in patients affected by cervical internal carotid artery (cICA) stenosis.

PURPOSE

This study aimed to investigate whether and how WMLs influence cerebral networking in patients with asymptomatic cICA stenosis eligible for carotid endarterectomy (CEA) by exploiting the connectometry technique.

METHODS

The study was designed as a cross-sectional exploratory investigation, and 28 patients with cICA stenosis eligible for CEA were enrolled. All patients received an MRI scan, including a T1-weighted, a FLAIR and a diffusion-weighted (DW) sequence. The T1 and FLAIR sequences were analysed for quantification of WML burden (WMLB) and total number of WMLs (TNWMLs). The DW data were reconstructed in the MNI space using q-space diffeomorphic reconstruction, and were grouped to create a connectometry database. The connectometry analysis evaluated the influence of both the WMLB and TNWMLs to local connectivity in a multiple regression model that included age, WMLB and TNWMLs, adopting three different T-score thresholds (1, 2 and 3). A p-value corrected for false discovery rate of <0.05 was adopted as a threshold to identify statistically significant results.

RESULTS

The connectometry analysis identified several white-matter bundles negatively correlated with WMLB; no statistically significant correlation was found for TNWMLs.

CONCLUSION

Results of our study suggest that WMLs influence brain connectivity measured by the connectometry technique in patients with cICA stenosis eligible for CEA. Further studies are warranted to understand the role of WMLs better as a marker of disease in patients with cICA stenosis.

Aljaberi M. Correlation of Mortality Burdens of Cerebrovascular Disease and Diabetes Mellitus with Domestic Consumption of Soya and Palm Oils

BACKGROUND

Cerebrovascular diseases (CBVDs) and diabetes mellitus (DM) are interrelated and cumbersome global health burdens. However, the relationship between edible oils consumption and mortality burdens of CBVDs and DM has not yet been evaluated. This review aims to explore correlations between per capita mortality burdens of CBVDs and DM, as well as food consumption of palm or soya oils in 11 randomly selected countries in 2005, 2010, and 2016.

METHODS

After obtaining data on food consumption of palm and soya oils and mortality burdens of CBVDs and DM, correlations between the consumption of oils and mortality burdens of diseases were explored.

RESULTS

There was a positive correlation between the consumption of soya oil with the mortality burden of CBVDs in Australia, Switzerland, and Indonesia, as well as the mortality burden of DM in the USA. The consumption of palm oil had a positive correlation with the mortality burden of DM in Jordan only.

CONCLUSIONS

Food consumption of soya oil in several countries possibly contributes to the mortality burden of CBVDs or DM more than food consumption of palm oil, which could be a possible risk factor in the mortality burdens of CBVDs and DM.

Developing robust biomarkers for vascular cognitive disorders: adding 'V' to the AT(N) research framework

PURPOSE OF REVIEW

The AT(N) research framework was introduced in 2018 to define Alzheimer's disease as a biological entity. It is recognized that Alzheimer's disease lesions rarely occur in isolation in older brains, with cerebrovascular disease (CVD) being a common comorbidity. To fully characterize the disorder of dementia, the AT(N) framework needs to be extended with biomarkers for other disorders. The present review examines some of the requirements for adding a 'V' to the AT(N), and examines the currently available biomarkers as definitive markers of CVD.

RECENT FINDINGS

Neuroimaging biomarkers of CVD have received the greatest attention, with rapid advances in MRI techniques showing the greatest promise. Challenges remain in standardization of techniques, validation of some of the results and assessing total CVD burden from diverse lesion types. Retinal imaging shows promise as a window to cerebral vasculature. Biochemical markers are advancing rapidly, but their specificity for CVD is not established.

SUMMARY

Biomarkers of CVD have seen rapid advances but further validation and determination of their specificity are needed before they can be reliably used to delineate a V in the AT(N) framework as definitive indicators of significant CVD.

Optical Coherence Tomography Angiography Reveals Distinct Retinal Structural and Microvascular Abnormalities in Cerebrovascular Disease

Cerebrovascular disease (CeVD) is one of the leading global causes of death and severe disability. To date, retinal microangiopathy has become a reflection of cerebral microangiopathy, mirroring the vascular pathological modifications in vivo. To evaluate the retinal structure and microvasculature in patients with CeVD, we conducted a cross-sectional study in Zhongshan Ophthalmic Center and Department of Neurology of Third Affiliated Hospital, Sun Yat-sen University using optical coherence tomography angiography (OCTA). CeVD patients (n = 121; 238 eyes) and healthy controls (n = 44; 57 eyes) were included in the analysis. The CeVD group showed significant thinning of the peripapillary retinal nerve fiber layer (pRNFL) thickness in the temporal and nasal quadrants, and thinning of the macular ganglion cell-inner plexiform layer (GC-IPL) in the inferior quadrant, while macular microvasculature reduction was prominent in all nine quadrants. There were significant correlations between OCTA parameters, visual acuity, and transcranial doppler parameters in the CeVD group. The specific structural parameters combining microvasculature indices showed the best diagnostic accuracies (AUC = 0.918) to discriminate CeVD group from healthy controls. To conclude, we proved that OCTA reveals specific patterns of retinal structural changes and extensive macular microvascular changes in CeVD. Additionally, these retinal abnormalities could prove useful disease biomarkers in the management of individuals at high risk of debilitating complications from a cerebrovascular event.

Health related quality of life in stroke patients and risk factors associated with patients for return to work

To clarify dynamic change of quality of life (QOL) in patients with stroke after treatment, and to explore the predictors associated with return to work (RTW) within 48 weeks.Patients diagnosed with stroke were enrolled. All patients enrolled were asked to fill in the Short Form 36 Health Survey. For patients with stroke, SF-36 questionnaires were measured repeatedly 4 weeks after treatment. We used phone call to find out if the patient was RTW. The investigation time was 48 weeks.Patients with stroke had lower scores in terms of physiological dimensions, such as physical functional, role limitations due to physical problems, and general health (P < .001). While patients with strokes scored significantly lower in all mental dimensions including vitality, social functioning, role limitations due to emotional problems, and mental health (P < .001). After 4-weeks treatment, we found that, except for bodily pain, scores in dimensions like physical functioning, role limitations due to physical problems, and general health had increased significantly (P < .001). Multivariate logistic regression analysis was conducted, and the result showed that older age (P = .04) and singleness (P = .03) were risk factors associated with QOL improvement in stroke patients after treatment. Outcomes of stroke patients within 48 weeks were explored. The results showed that 108 out of 136 patients RTW within 48 weeks. Average days it took for patients with cerebral infarction to return to work were 77 ± 79, significantly less than patients with cerebral hemorrhage (206 ± 159 days) and patients with subarachnoid hemorrhage (117 ± 113 days, P < .001). Multivariate analysis indicated that only QOL improvement (P = .04) and subtype of stroke (P = .01) were independent factors associated with RTW within 48 weeks.QOL of stroke patients was significantly reduced. After treatments, the physiological quality of stroke patients increased, but the psychological quality remained low. In addition, patients with cerebral hemorrhage and patients with no significant improvement in QOL are independent risk factors for RTW. Therefore, for this subgroup of the population, early diagnosis, close follow-up and monitor of the psychological state should be provided to avoid the occurrence of adverse events.