Perivascular space enlargement accelerates in ageing and Alzheimer's disease pathology: evidence from a three-year longitudinal multicentre study

Imaging brain fluid dynamics and waste clearance involving perivascular spaces in cerebral small vessel disease

Cerebral small vessel disease (SVD) is recognized as a major vascular contributor to cognitive decline, ultimately leading to dementia and stroke. While the pathogenesis of SVD remains unclear, emerging evidence suggests that waste clearance involving perivascular space (PVS) - also known as the glymphatic system - dysfunction may play a role. Among SVD radiological markers, the increased presence of dilated PVS is recognized as a marker of waste clearance disruption. Recently developed neuroimaging methods have been proposed as indirect measures of brain fluid dynamics, but they currently lack formal validation. Here, we provide a comprehensive overview of the latest neuroimaging advancements for assessing brain fluid dynamics, including waste clearance involving PVS function in SVD. We review the mechanisms by which clearance dysfunction might contribute to SVD. Finally, we argue that robust, multimodal, and longitudinal studies are essential for understanding the waste clearance (involving PVS) function and for establishing a diagnostic gold standard. HIGHLIGHTS: The majority of PVS are not visible on MRI, making it crucial to understand how and why they become dilated. The origin of waste clearance involving PVS disruption in SVD may be multifactorial. The BBB and waste clearance (involving PVS) dysfunction likely affect each other, forming a vicious cycle, promoting further amyloid beta accumulation. Yet their direct association in humans over time remains to be studied. Comparative studies can aid in the standardization of methods for assessing waste clearance involving PVS function.

Cerebral Small Vessel Disease Outperforms Brain Atrophy as an Imaging Biomarker in Diabetic Retinopathy

AIM

This study aimed to examine microvascular lesions and neurodegenerative changes in diabetic retinopathy (DR) compared to type 2 diabetes mellitus (T2DM) without DR (NDR) using structural MRI and to explore their associations with DR.

METHODS

243 patients with NDR and 122 patients with DR were included. Participants underwent conventional brain MRI scans, clinical measurements, and fundus examinations. Cerebral small vessel disease (CSVD) imaging parameters were obtained using AI-based software, manually verified, and corrected for accuracy. Volumes of major cortical and subcortical regions representing neurodegeneration were assessed using automated brain segmentation and quantitative techniques. Statistical analysis included T-test, chi-square test, Mann-Whitney U test, multivariate analysis of variance (MANCOVA), multivariate logistic regression, area under the receiver operating characteristic curve (AUC), and Delong test.

RESULTS

DR group exhibited significant differences in 11 CSVD features. Meanwhile, DR showed an atrophy trend in the frontal cortex, occipital cortex, and subcortical gray matter (GM) compared to NDR. After adjustment, DR patients exhibited greater perivascular spaces (PVS) numbers in the parietal lobe (OR = 1.394) and deep brain regions (OR = 1.066), greater dilated perivascular spaces (DPVS) numbers in the left basal ganglia (OR = 2.006), greater small subcortical infarcts (SSI) numbers in the right hemisphere (OR = 3.104), and decreased left frontal PVS (OR = 0.824), total left DPVS (OR = 0.714), and frontal cortex volume (OR = 0.959) compared to NDR. Further, the CSVD model showed a larger AUC (0.823, 95% CI: 0.781-0.866) than the brain atrophy model (AUC = 0.757, 95% CI: 0.706-0.808).

CONCLUSION

Microvascular and neurodegeneration are significantly associated with DR. CSVD is a better imaging biomarker for DR than brain atrophy.