Quantitative measurements of enlarged perivascular spaces in the brain are associated with retinal microvascular parameters in older community-dwelling subjects

Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain

Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.

Association of optic disc pallor and RNFL thickness with cerebral small vessel disease in the PREVENT-Dementia study

INTRODUCTION

We tested associations between two retinal measures (optic disc pallor, peripapillary retinal nerve fiber layer [pRNFL] thickness) and four magnetic resonance imaging markers of cerebral small vessel disease (SVD; lacunes, microbleeds, white matter hyperintensities, and enlarged perivascular spaces [ePVSs]).

METHODS

We used PallorMetrics to quantify optic disc pallor from fundus photographs, and pRNFL thickness from optical coherence tomography scans. Linear and logistic regression assessed relationships between retinal measures and SVD markers. Participants (N = 108, mean age 51.6) were from the PREVENT Dementia study.

RESULTS

Global optic disc pallor was linked to ePVSs in the basal ganglia in both left (β = 0.12, standard error [SE] = 0.05, P < 0.05) and right eyes (β = 0.13, SE = 0.05, P < 0.05). Associations were also noted in different disc sectors. No pRNFL associations with SVD markers were found.

DISCUSSION

Optic disc pallor correlated with ePVSs in the basal ganglia, suggesting retinal examination may be a useful method to study brain health changes related to SVD.

Highlights

Optic disc pallor is linked to enlarged perivascular spaces in basal ganglia.There is no association between peripapillary retinal nerve fiber layer thickness and cerebral small vessel disease markers.Optic disc examination could provide insights into brain health.The sample included 108 midlife adults from the PREVENT Dementia study.

A narrative review of retinal vascular parameters and the applications (Part II): Diagnosis in stroke

The retina, as an external extension of the diencephalon, can be directly, noninvasively observed by ocular fundus photography. Therefore, it offers a convenient and feasible mode to study nervous system diseases. Caliber, tortuosity, and fractal dimension, as three commonly used retinal vascular parameters, are not only the reflection of structural changes in the retinal microcirculation but also capture the branching pattern or density changes of the retinal microvascular network. Therefore, it contributes to better reflecting the subclinical pathological changes (e.g., lacunar stroke and small cerebral vascular disease) and predicting the risk of incident stroke and recurrent stroke.

A critical guide to the automated quantification of perivascular spaces in magnetic resonance imaging

The glymphatic system is responsible for waste clearance in the brain. It is comprised of perivascular spaces (PVS) that surround penetrating blood vessels. These spaces are filled with cerebrospinal fluid and interstitial fluid, and can be seen with magnetic resonance imaging. Various algorithms have been developed to automatically label these spaces in MRI. This has enabled volumetric and morphological analyses of PVS in healthy and disease cohorts. However, there remain inconsistencies between PVS measures reported by different methods of automated segmentation. The present review emphasizes that importance of voxel-wise evaluation of model performance, mainly with the Sørensen Dice similarity coefficient. Conventional count correlations for model validation are inadequate if the goal is to assess volumetric or morphological measures of PVS. The downside of voxel-wise evaluation is that it requires manual segmentations that require large amounts of time to produce. One possible solution is to derive these semi-automatically. Additionally, recommendations are made to facilitate rigorous development and validation of automated PVS segmentation models. In the application of automated PVS segmentation tools, publication of image quality metrics, such as the contrast-to-noise ratio, alongside descriptive statistics of PVS volumes and counts will facilitate comparability between studies. Lastly, a head-to-head comparison between two algorithms, applied to two cohorts of astronauts reveals how results can differ substantially between techniques.

Characterization of perivascular space pathology in a rat model of cerebral small vessel disease by in vivo magnetic resonance imaging

One of the most common causes of dementia is cerebral small vessel disease (SVD), which is associated with enlarged perivascular spaces (PVS). Clinically, PVS are visible as hyperintensities on T2-weighted (T2w) magnetic resonance images (MRI). While rodent SVD models exhibit arteriolosclerosis, PVS have not been robustly documented by MRI casting doubts on their clinical relevance. Here we established that the severity of SVD in spontaneously hypertensive stroke prone (SHRSP) rats correlated to 'moderate' SVD in human post-mortem tissue. We then developed two approaches for detecting PVS in SHRSP rats: 1) T2w imaging and 2) T1-weighted imaging with administration of gadoteric acid into cerebrospinal fluid. We applied the two protocols to six Wistar-Kyoto (WKY) control rats and thirteen SHRSP rats at ∼12 month of age. The primary endpoint was the number of hyperintense lesions. We found more hyperintensities on T2w MRI in the SHRSP compared to WKY rats (p-value = 0.023). CSF enhancement with gadoteric acid increased the visibility of PVS-like lesions in SHRSP rats. In some of the SHRSP rats, the MRI hyperintensities corresponded to enlarged PVS on histopathology. The finding of PVS-like hyperintensities on T2w MRI support the SHRSP rat's clinical relevance for studying the underlying pathophysiology of SVD.

Retinal microvasculature and imaging markers of brain frailty in normal aging adults

Background

The retina and brain share a similar embryologic origin, blood barriers, and microvasculature features. Thus, retinal imaging has been of interest in the aging population to help in the early detection of brain disorders. Imaging evaluation of brain frailty, including brain atrophy and markers of cerebral small vessel disease (CSVD), could reflect brain health in normal aging, but is costly and time-consuming. In this study, we aimed to evaluate the retinal microvasculature and its association with radiological indicators of brain frailty in normal aging adults.

Methods

Swept-source optical coherence tomography angiography (SS-OCTA) and 3T-MRI brain scanning were performed on normal aging adults (aged ≥ 50 years). Using a deep learning algorithm, microvascular tortuosity (VT) and fractal dimension parameter (Dbox) were used to evaluate the superficial vascular complex (SVC) and deep vascular complex (DVC) of the retina. MRI markers of brain frailty include brain volumetric measures and CSVD markers that were assessed.

Results

Of the 139 normal aging individuals included, the mean age was 59.43 ± 7.31 years, and 64.0% (n = 89) of the participants were females. After adjustment of age, sex, and vascular risk factors, Dbox in the DVC showed a significant association with the presence of lacunes (β = 0.58, p = 0.007), while VT in the SVC significantly correlated with the score of cerebral deep white matter hyperintensity (β = 0.31, p = 0.027). No correlations were found between brain volumes and retinal microvasculature changes (P &gt; 0.05).

Conclusion

Our report suggests that imaging of the retinal microvasculature may give clues to brain frailty in the aging population.