Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease

Optical coherence tomography angiography in patients with bipolar disorder and major depressive disorder

BACKGROUND

Cerebral microvascular dysfunction is a promising area for research into the pathogenesis of major depressive disorder (MDD) and bipolar disorder (BD). Despite the scientific and clinical potential of studying microvascular dysfunction, progress in this area has long been hampered by the lack of methods to study microvessels intravitally.

AIMS

The aim of the present study was to search for potential optical coherence tomography (OCT) and OCT-angiography (OCTA) biomarkers of BD and MDD.

METHODS

One hundred and five consecutive patients with a current depressive episode were enrolled in the study (39 - BD and 66 - MDD). In addition, forty-one generally healthy subjects were enrolled as a control group. Only the right eye was examined in all subjects. Structural OCT and OCTA scans with signal strength ≥7 were included.

RESULTS

Structural OCT measurements showed no significant differences between the groups. OCTA measurements of foveal avascular zone (FAZ), area and skeleton density showed a decrease in the retinal capillary bed in BD patients, whereas OCTA values in MDD patients did not differ from the control group. Several significant differences were found between the BD and control groups. In the BD group, the FAZ of the deep capillary plexus was increased, reflecting a reduction in capillary perfusion in the central subfield of this plexus.

CONCLUSIONS

OCTA measurements of FAZ, area and skeleton density showed a decrease in the retinal capillary bed in BD patients, whereas OCTA values in MDD patients did not differ from the control group.

Retina as a potential biomarker for the early stage of Alzheimer's disease spectrum

OBJECTIVE

To characterize the retinal microvasculature and structure in subjective cognitive decline (SCD) and identify the potential biomarker for the early stage of the Alzheimer's disease (AD) spectrum.

METHODS

In this study, 35 patients with SCD, 36 with cognitive impairment, and 29 with normal cognition (NC) were enrolled. Optical coherence tomography angiography was employed to assess retinal vascular density, fovea avascular zone area, and retinal thickness. The parameters reflecting retinal perfusion and structure were compared among the three groups. In addition, the association between retinal parameters, cerebral blood flow (CBF), and peripheral blood biomarkers in the SCD stage was analyzed.

RESULTS

The superficial vascular complex (SVC) vascular density in the macula and retinal nerve fiber layer thickness in the peripapillary were significantly reduced in individuals with SCD compared to NC. Furthermore, there was a positive correlation between macular ganglion cell complex thickness and CBF in SCD.

INTERPRETATION

The retinal microvasculature and structure exhibit alterations in individuals with SCD. Macular ganglion cell complex thickness demonstrates correlations with cerebral perfusion. The retina holds potential as a novel biomarker for early detection of AD.

Association of Retinal Biomarkers With the Subtypes of Ischemic Stroke and an Automated Classification Model

Purpose

Retinal microvascular changes are associated with ischemic stroke, and optical coherence tomography angiography (OCTA) is a potential tool to reveal the retinal microvasculature. We investigated the feasibility of using the OCTA image to automatically identify ischemic stroke and its subtypes (i.e. lacunar and non-lacunar stroke), and exploited the association of retinal biomarkers with the subtypes of ischemic stroke.

Methods

Two cohorts were included in this study and a total of 1730 eyes from 865 participants were studied. A deep learning model was developed to discriminate the subjects with ischemic stroke from healthy controls and to distinguish the subtypes of ischemic stroke. We also extracted geometric parameters of the retinal microvasculature at different retinal layers to investigate the correlations.

Results

Superficial vascular plexus (SVP) yielded the highest areas under the receiver operating characteristic curve (AUCs) of 0.922 and 0.871 for the ischemic stroke detection and stroke subtypes classification, respectively. For external data validation, our model achieved an AUC of 0.822 and 0.766 for the ischemic stroke detection and stroke subtypes classification, respectively. When parameterizing the OCTA images, we showed individuals with ischemic strokes had increased SVP tortuosity (B = 0.085, 95% confidence interval [CI] = 0.005-0.166, P = 0.038) and reduced FAZ circularity (B = -0.212, 95% CI = -0.42 to -0.005, P = 0.045); non-lacunar stroke had reduced SVP FAZ circularity (P = 0.027) compared to lacunar stroke.

Conclusions

Our study demonstrates the applicability of artificial intelligence (AI)-enhanced OCTA image analysis for ischemic stroke detection and its subtypes classification. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of ischemic stroke and its subtypes.

Macular vessel density in the superficial plexus is not a proxy of cerebrovascular damage in non-demented individuals: data from the NORFACE cohort

INTRODUCTION

Optical coherence tomography angiography (OCT-A) is a novel tool that allows the detection of retinal vascular changes. We investigated the association of macular vessel density (VD) in the superficial plexus assessed by OCT-A with measures of cerebrovascular pathology and atrophy quantified by brain magnetic resonance imaging (MRI) in non-demented individuals.

METHODS

Clinical, demographical, OCT-A, and brain MRI data from non-demented research participants were included. We analyzed the association of regional macular VD with brain vascular burden using the Fazekas scale assessed in a logistic regression analysis, and the volume of white matter hyperintensities (WMH) assessed in a multiple linear regression analysis. We also explored the associations of macular VD with hippocampal volume, ventricle volume and Alzheimer disease cortical signature (ADCS) thickness assessed in multiple linear regression analyses. All analyses were adjusted for age, sex, syndromic diagnosis and cardiovascular variables.

RESULTS

The study cohort comprised 188 participants: 89 with subjective cognitive decline and 99 with mild cognitive impairment. No significant association of regional macular VD with the Fazekas categories (all, p > 0.111) and WMH volume (all, p > 0.051) were detected. VD in the nasal quadrant was associated to hippocampal volume (p = 0.007), but no other associations of macular VD with brain atrophy measures were detected (all, p > 0.05).

DISCUSSION

Retinal vascular measures were not a proxy of cerebrovascular damage in non-demented individuals, while VD in the nasal quadrant was associated with hippocampal atrophy independently of the amyloid status.

Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review

Background

This study aimed to review the literature on the application of ImageJ in optical coherence tomography angiography (OCT-A) images.

Methods

A general search was performed in PubMed, Google Scholar, and Scopus databases. The authors evaluated each of the selected articles in order to assess the implementation of ImageJ in OCT-A images.

Results

ImageJ can aid in reducing artifacts, enhancing image quality to increase the accuracy of the process and analysis, processing and analyzing images, generating comparable parameters such as the parameters that assess perfusion of the layers (vessel density (VD), skeletonized density (SD), and vessel length density (VLD)) and the parameters that evaluate the structure of the layers (fractal dimension (FD), vessel density index (VDI), and lacunarity (LAC)), and the foveal avascular zone (FAZ) that are used widely in the retinal and choroidal studies), and establishing diagnostic criteria. It can help to save time when the dataset is huge with numerous plugins and options for image processing and analysis with reliable results. Diverse studies implemented distinct binarization and thresholding techniques, resulting in disparate outcomes and incomparable parameters. Uniformity in methodology is required to acquire comparable data from studies employing diverse processing and analysis techniques that yield varied outcomes.

Conclusion

Researchers and professionals might benefit from using ImageJ because of how quickly and correctly it processes and analyzes images. It is highly adaptable and potent software, allowing users to evaluate images in a variety of ways. There exists a diverse range of methodologies for analyzing OCTA images through the utilization of ImageJ. However, it is imperative to establish a standardized strategy to ensure the reliability and consistency of the method for research purposes.

A mini-review of the evidence for cerebrovascular changes following gender-affirming hormone replacement therapy and a call for increased focus on cerebrovascular transgender health

Gender-affirming hormone replacement therapy (gaHRT) is an important step for many in the gender diverse community, associated with increased quality-of-life and lower self-reported scores of depression and anxiety. However, considering the interactions that the involved sex hormones have on vasculature (with oestrogen and testosterone demonstrating vasodilatory and vasoconstricting properties, respectively), it is important for transgender healthcare research to examine how the manipulation of these hormones interact with cerebrovascular structure and functioning. There is a stark lack of research in this area. This mini-review outlines the research suggesting a vascular impact of these sex hormones using evidence from a range of cohorts (e.g., menopause, polycystic ovary syndrome) and discusses the work that has been done into cerebrovascular changes following gaHRT. Finally, recommendations for future research into cerebrovascular health in transgender cohorts following gaHRT are outlined.

Serum cystatin C for risk stratification of prediabetes and diabetes populations

BACKGROUND

The association between serum cystatin C level and vascular outcomes has not been fully elucidated in diabetes and is unclear in prediabetes. We aim to evaluate whether cystatin C level predicts future risk for mortality and vascular outcomes in prediabetes and diabetes.

METHODS

A total of 85,371 participants with prediabetes and diabetes, and available baseline cystatin C in the UK biobank were included with a 14-year follow-up. Cox hazards models were used to calculate the associations between cystatin C level, mortality (all-cause, cause-specfic mortality) and vascular outcomes (myocardial infarction [MI], stroke, end-stage renal disease [ESRD] and diabetic retinopathy [DR]). The 1136 diabetes subjects in Guangzhou Diabetic Eye Study (GDES) were included for examing the impact of cystatin C on in vivo retinal degeneration and microvascular changes by using SS-OCT and OCTA.

RESULTS

The highest cystatin C quartile had increased risks of all-cause (hazard ratio [HR], 2.02; 95% confidence interval [CI] 1.86-2.19), cardiovascular (HR, 2.29; 95% CI 1.97-2.67), cancer (HR, 1.86; 95% CI 1.65-2.10) and other-cause mortality (HR, 2.24; 95% CI 1.90-2.64), MI (HR, 1.40; 95% CI 1.26-1.55), stroke (HR, 1.88; 95% CI, 1.57-2.26), ESRD (HR, 7.33; 95% CI, 5.02-10.71), DR (HR, 1.17; 95% CI 1.03-1.32) than those in the lowest quartile. Adding cystatin C to the conventional model improved C-statistic for all-cause (0.699-0.724), cardiovascular (0.762-0.789), cancer (0.661-0.674) and other-cause mortality (0.675-0.715), MI (0.748-0.750), stroke (0.712-0.718), and ESRD (0.808-0.827). The GDES analysis identified a strong association between increased cystatin C levels and diminished retinal neural layers, as well as microvascular rarefaction in both macular and optic disc regions (all P < 0.05).

CONCLUSIONS

Serum cystatin C refines the risk stratification for mortality and vascular outcomes among patients with prediabetes or diabetes.

Relationships between quantitative retinal microvascular characteristics and cognitive function based on automated artificial intelligence measurements

Introduction: The purpose of this study is to assess the relationship between retinal vascular characteristics and cognitive function using artificial intelligence techniques to obtain fully automated quantitative measurements of retinal vascular morphological parameters. Methods: A deep learning-based semantic segmentation network ResNet101-UNet was used to construct a vascular segmentation model for fully automated quantitative measurement of retinal vascular parameters on fundus photographs. Retinal photographs centered on the optic disc of 3107 participants (aged 50-93 years) from the Beijing Eye Study 2011, a population-based cross-sectional study, were analyzed. The main parameters included the retinal vascular branching angle, vascular fractal dimension, vascular diameter, vascular tortuosity, and vascular density. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Results: The results showed that the mean MMSE score was 26.34 ± 3.64 (median: 27; range: 2-30). Among the participants, 414 (13.3%) were classified as having cognitive impairment (MMSE score < 24), 296 (9.5%) were classified as mild cognitive impairment (MMSE: 19-23), 98 (3.2%) were classified as moderate cognitive impairment (MMSE: 10-18), and 20 (0.6%) were classified as severe cognitive impairment (MMSE < 10). Compared with the normal cognitive function group, the retinal venular average diameter was significantly larger (p = 0.013), and the retinal vascular fractal dimension and vascular density were significantly smaller (both p < 0.001) in the mild cognitive impairment group. The retinal arteriole-to-venular ratio (p = 0.003) and vascular fractal dimension (p = 0.033) were significantly decreased in the severe cognitive impairment group compared to the mild cognitive impairment group. In the multivariate analysis, better cognition (i.e., higher MMSE score) was significantly associated with higher retinal vascular fractal dimension (b = 0.134, p = 0.043) and higher retinal vascular density (b = 0.152, p = 0.023) after adjustment for age, best corrected visual acuity (BCVA) (logMAR) and education level. Discussion: In conclusion, our findings derived from an artificial intelligence-based fully automated retinal vascular parameter measurement method showed that several retinal vascular morphological parameters were correlated with cognitive impairment. The decrease in retinal vascular fractal dimension and decreased vascular density may serve as candidate biomarkers for early identification of cognitive impairment. The observed reduction in the retinal arteriole-to-venular ratio occurs in the late stages of cognitive impairment.

Implication of heart rate variability on cerebral small vessel disease: A potential therapeutic target

OBJECTIVE

This study aimed to investigate the relationships of heart rate variability (HRV) with the presence, severity, and individual neuroimaging markers of cerebral small vessel disease (CSVD).

METHOD

A total of 4676 participants from the Third China National Stroke Registry (CNSR-III) study were included in this cross-sectional analysis. CSVD and its markers, including white matter hyperintensity (WMH), lacunes, enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and brain atrophy (BA), were evaluated. Two common HRV parameters, including the square root of the mean of the sum of the squares of differences between adjacent N-N intervals (RMSSD) and the standard deviation of all N-N intervals (SDNN), were used to evaluate the function of the autonomic nervous system (ANS). Binary or ordinal logistic regression analyses were performed to investigate the association between HRV and CSVD. In addition, two-sample mendelian randomization (MR) analyses were performed to investigate the causality of HRV with CSVD.

RESULTS

RMSSD was significantly associated with total burden of CSVD (Wardlaw's scale, common odds ratio [cOR] 0.80, 95% confidence interval [CI] 0.67-0.96, p = 0.02; Rothwell's scale, cOR 0.75, 95% CI 0.60-0.93, p = 0.008) and the presence of CSVD (Rothwell, OR 0.75, 95% CI 0.60-0.93, p = 0.008). However, no significant associations between SDNN and the presence or total burden of CSVD were observed. Moreover, RMSSD was related to WMH burden (OR 0.80, 95% CI 0.66-0.96, p = 0.02), modified WMH burden (cOR 0.82, 95% CI 0.69-0.97, p = 0.02), and Deep-WMH (OR 0.75, 95% CI 0.62-0.91, p = 0.003), while SDNN was related to Deep-WMH (OR 0.80, 95% CI 0.66-0.96, p = 0.02) and BA (cOR 0.80, 95% CI 0.68-0.95, p = 0.009). Furthermore, adding HRV to the conventional model based on vascualr risk factors enhanced the predictive performance for CSVD, as validated by the integrated discrimination index (p < 0.05). In addition, no causality between HRV and CSVD was observed in two-sample MR analyses.

CONCLUSION

Decreased HRV may be a potential risk factor of CSVD, implying the possible role of the ANS in the pathogenesis of CSVD.