Quantity and Morphology of Perivascular Spaces: Associations With Vascular Risk Factors and Cerebral Small Vessel Disease

Effects of prospective motion correction on perivascular spaces at 7T MRI evaluated using motion artifact simulation

PURPOSE

The effectiveness of prospective motion correction (PMC) is often evaluated by comparing artifacts in images acquired with and without PMC (NoPMC). However, such an approach is not applicable in clinical setting due to unavailability of NoPMC images. We aim to develop a simulation approach for demonstrating the ability of fat-navigator-based PMC in improving perivascular space (PVS) visibility in T2-weighted MRI.

METHODS

MRI datasets from two earlier studies were used for motion artifact simulation and evaluating PMC, including T2-weighted NoPMC and PMC images. To simulate motion artifacts, k-space data at motion-perturbed positions were calculated from artifact-free images using nonuniform Fourier transform and misplaced onto the Cartesian grid before inverse Fourier transform. The simulation's ability to reproduce motion-induced blurring, ringing, and ghosting artifacts was evaluated using sharpness at lateral ventricle/white matter boundary, ringing artifact magnitude in the Fourier spectrum, and background noise, respectively. PVS volume fraction in white matter was employed to reflect its visibility.

RESULTS

In simulation, sharpness, PVS volume fraction, and background noise exhibited significant negative correlations with motion score. Significant correlations were found in sharpness, ringing artifact magnitude, and PVS volume fraction between simulated and real NoPMC images (p ≤ 0.006). In contrast, such correlations were reduced and nonsignificant between simulated and real PMC images (p ≥ 0.48), suggesting reduction of motion effects with PMC.

CONCLUSIONS

The proposed simulation approach is an effective tool to study the effects of motion and PMC on PVS visibility. PMC may reduce the systematic bias of PVS volume fraction caused by motion artifacts.

Dynamic functional network connectivity in patients with a mismatch between white matter hyperintensity and cognitive function

Objective

White matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective.

Methods

The resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system.

Results

The 149 CSVD patients included 20 cases of "Type I mismatch," 51 cases of Type I match, 38 cases of "Type II mismatch," and 40 cases of "Type II match." Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between "Type I match" and "Type I mismatch"; the FT of States 1 and 4 differed significantly between "Type II match" and "Type II mismatch." Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between "Type I match" and "Type I mismatch," while the left MTA score differed between "Type II match" and "Type II mismatch."

Conclusion

Different mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.

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.

Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Relationship of Perivascular Space Markers With Incident Dementia in Cerebral Small Vessel Disease

BACKGROUND

Recent studies, using diffusion tensor image analysis along the perivascular space (DTI-ALPS), suggest impaired perivascular space (PVS) function in cerebral small vessel disease, but they were cross-sectional, making inferences on causality difficult. We determined associations between impaired PVS, measured using DTI-ALPS and PVS volume, and cognition and incident dementia.

METHODS

In patients with lacunar stroke and confluent white matter hyperintensities, without dementia at baseline, recruited prospectively in a single center, magnetic resonance imaging was performed annually for 3 years, and cognitive assessments, including global, memory, executive function, and processing speed, were performed annually for 5 years. We determined associations between DTI-ALPS and PVS volume with cerebral small vessel disease imaging markers (white matter hyperintensity volume, lacunes, and microbleeds) at baseline and with changes in imaging markers. We determined whether DTI-ALPS and PVS volume at baseline and change over 3 years predicted incident dementia. Analyses were controlled for conventional diffusion tensor image metrics using 2 markers (median mean diffusivity [MD] and peak width of skeletonized MD) and adjusted for age, sex, and vascular risk factors.

RESULTS

A total of 120 patients, mean age 70.0 years and 65.0% male, were included. DTI-ALPS declined over 3 years, while no change in PVS volume was found. Neither DTI-ALPS nor PVS volume was associated with cerebral small vessel disease imaging marker progression. Baseline DTI-ALPS was associated with changes in global cognition (β=0.142, P=0.032), executive function (β=0.287, P=0.027), and long-term memory (β=0.228, P=0.027). Higher DTI-ALPS at baseline predicted a lower risk of dementia (hazard ratio, 0.328 [0.183-0.588]; P<0.001), and this remained significant after including median MD as a covariate (hazard ratio, 0.290 [0.139-0.602]; P<0.001). Change in DTI-ALPS predicted dementia conversion (hazard ratio, 0.630 [0.428-0.964]; P=0.048), but when peak width of skeletonized MD and median MD were entered as covariates, the association was not significant. There was no association between baseline PVS volume, or PVS change over 3 years, and conversion to dementia.

CONCLUSIONS

DTI-ALPS predicts future dementia risk in patients with lacunar strokes and confluent white matter hyperintensities. However, the weakening of the association between change in DTI-ALPS and incident dementia after controlling for peak width of skeletonized MD and median MD suggests part of the signal may represent conventional diffusion tensor image metrics. PVS volume is not a predictor of future dementia risk.

Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces

BACKGROUND

Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified.

NEW METHOD

We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T.

RESULTS

The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter.

COMPARISON WITH EXISTING METHODS

Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given.

CONCLUSIONS

Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.

Correlation analysis between cerebral microangiopathy and autonomic nervous dysfunction

OBJECTIVE

Our study was conducted aimed at investigating the potential correlation between cerebral microangiopathy and autonomic nervous dysfunction.

METHODS

We initially included 164 hospitalized patients with cerebral microangiopathy at our hospital from November 2019 to January 2021. Based on the inclusion and exclusion criteria, a final total of 162 patients with cerebral microangiopathy were selected. According to the patient's Autonomic Symptom Profile (ASP) score, patients with a score greater than 22 were categorized into a group with concomitant autonomic dysfunction (71 cases, combined group), while those with a score below 22 were categorized into a group of isolated cerebral microangiopathy (83 cases, cerebral microangiopathy group). The general data and laboratory examination results of the two groups were analyzed, and Pearson correlation analysis was performed to evaluate the correlation between cerebral microangiopathy and autonomic dysfunction, as well as the influencing factors of cerebral microangiopathy patients combined with autonomic dysfunction.

RESULTS

There were no significant differences between the two groups in terms of sex, BMI, smoking, drinking, family dementia history, diabetes, hypothyroidism, carotid atherosclerosis, obstructive sleep apnea hypopnea syndrome, hyperuricemia, hyperlipidemia, chronic obstructive pulmonary disease, Hamilton Anxiety Scale score, Hamilton Depression Scale score, 24-h mean systolic blood pressure (SBP), 24-h mean diastolic blood pressure DBP, daytime mean systolic blood pressure (dSBP), daytime mean diastolic blood pressure, nighttime mean systolic blood pressure (nSBP), nighttime mean diastolic blood pressure, 24-h systolic blood pressure standard deviation (SBPSD), 24-h diastolic blood pressure standard deviation, daytime diastolic blood pressure standard deviation, nighttime diastolic blood pressure standard deviation (nDBPSD), nDBPSD (p > .05). However, significant differences were observed between the two groups regarding age, history of coronary heart disease, hypertension, leukoaraiosis, cognitive function, ASP score, SSR, 24-h SBPSD, daytime systolic blood pressure standard deviation (dSBPSD), nighttime systolic blood pressure standard deviation (nSBPSD), standard deviation of RR interval (SDNN), root mean square value of successive RR interval difference (RMSSD), high-frequency component (HF), and low-frequency component (LF) (p < .05). Moreover, the levels of TG, TC, HDL-C, and LDL-C did not show significant differences between the two groups (p > .05), but there were significant differences in blood uric acid and homocysteine (Hcy) levels (p < .05). Age, history of leukoaraiosis, cognitive function assessment, blood uric acid, Hcy levels, 24-h SBPSD, dSBPSD, and nSBPSD showed positive correlations with ASP scores and SSR in patients with cerebral microangiopathy (p < .001). In contrast, hypertension, SDNN, RMSSD, HF, and LF showed negative correlations with ASP scores and SSR (p < .001). Moreover, coronary heart disease was negatively correlated with ASP scores but positively correlated with SSR (p < .001). The independent variables included age, history of leukoaraiosis, cognitive function assessment, ASP score, SSR, blood uric acid, Hcy, bradykinin, coronary heart disease, hypertension, 24-h SBPSD, dSBPSD, nSBPSD, SDNN, RMSSD, HF, and LF, which were indicators with differences in general data and laboratory indicators. The dependent variable was patients with cerebral microangiopathy combined with autonomic nervous dysfunction. The analysis results showed that age, history of leukoaraiosis, ASP score, SSR, 24-h SBPSD, dSBPSD, nSBPSD, SDNN, RMSSD, HF, and LF were the influencing factors of patients with cerebral microangiopathy complicated with autonomic nervous dysfunction.

CONCLUSION

We demonstrates that age, history of leukoaraiosis, cognitive function assessment, blood uric acid, Hcy level, 24-h SBPSD, dSBPSD, nSBPSD, blood pressure, SDNN, RMSSD, HF, LF, and coronary heart disease were highly associated with cerebral microangiopathy with autonomic dysfunction. Furthermore, the influencing factors of cerebral microangiopathy with autonomic dysfunction are age, history of leukoaraiosis, ASP score, SSR, blood pressure variability, and HRV.

Imaging the neurovascular unit in health and neurodegeneration: a scoping review of interdependencies between MRI measures

The neurovascular unit (NVU) is a complex structure that facilitates nutrient delivery and metabolic waste clearance, forms the blood-brain barrier (BBB), and supports fluid homeostasis in the brain. The integrity of NVU subcomponents can be measured in vivo using magnetic resonance imaging (MRI), including quantification of enlarged perivascular spaces (ePVS), BBB permeability, cerebral perfusion and extracellular free water. The breakdown of NVU subparts is individually associated with aging, pathology, and cognition. However, how these subcomponents interact as a system, and how interdependencies are impacted by pathology remains unclear. This systematic scoping review identified 26 studies that investigated the inter-relationships between multiple subcomponents of the NVU in nonclinical and neurodegenerative populations using MRI. A further 112 studies investigated associations between the NVU and white matter hyperintensities (WMH). We identify two putative clusters of NVU interdependencies: a 'vascular' cluster comprising BBB permeability, perfusion and basal ganglia ePVS; and a 'fluid' cluster comprising ePVS, free water and WMH. Emerging evidence suggests that subcomponent coupling within these clusters may be differentially related to aging, neurovascular injury or neurodegenerative pathology.

Past antihypertensive medication use is associated with lower levels of small vessel disease and lower Aβ plaque stage in the brains of older individuals

AIMS

This study assesses the association of antihypertensive medication use on the severities of neuropathological cerebrovascular disease (CVD excluding lobar infarction) in older individuals.

METHODS

Clinical and neuropathological data were retrieved for 149 autopsy cases >75 years old with or without CVD or Alzheimer's disease and no other neuropathological diagnoses. Clinical data included hypertension status, hypertension diagnosis, antihypertensive medication use, antihypertensive medication dose (where available) and clinical dementia rating (CDR). Neuropathological CVD severity was evaluated for differences with anti-hypertensive medication usage.

RESULTS

Antihypertensive medication use was associated with less severe white matter small vessel disease (SVD, mainly perivascular dilatation and rarefaction), with a 5.6-14.4 times greater likelihood of less severe SVD if medicated. No significant relationship was detected between infarction (presence, type, number and size), lacunes or cerebral amyloid angiopathy and antihypertensive medication use. Only increased white matter rarefaction/oedema and not perivascular dilation was associated with Alzheimer's pathology, with a 4.3 times greater likelihood of reduced Aβ progression through the brain if white matter rarefaction severity was none or mild. Antihypertensive medication use was associated with reduced Aβ progression but only in those with moderate to severe white matter SVD.

CONCLUSIONS

This histopathological study provides further evidence that antihypertensive medication use in older individuals is associated with white matter SVD and not with other CVD pathologies. This is mainly due to a reduction in white matter perivascular dilation and rarefaction/oedema. Even in those with moderate to severe white matter SVD, antihypertensive medication use reduced rarefaction and Aβ propagation through the brain.

Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research

Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.

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.

Associations of MRI-visible perivascular spaces with longitudinal cognitive decline across the Alzheimer's disease spectrum

OBJECTIVE

To investigate the characteristics and associations of MRI-visible perivascular spaces (PVS) with clinical progression and longitudinal cognitive decline across the Alzheimer's disease spectrum.

METHODS

We included 1429 participants (641 [44.86%] female) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. PVS number and grade in the centrum semiovale (CSO-PVS), basal ganglia (BG-PVS), and hippocampus (HP-PVS) were compared among the control (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) groups. PVS were tested as predictors of diagnostic progression (i.e., CN to MCI/AD or MCI to AD) and longitudinal changes in the 13-item Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog 13), Mini-Mental State Examination (MMSE), memory (ADNI-MEM), and executive function (ADNI-EF) using multiple linear regression, linear mixed-effects, and Cox proportional hazards modeling.

RESULTS

Compared with CN subjects, MCI and AD subjects had more CSO-PVS, both in number (p < 0.001) and grade (p < 0.001). However, there was no significant difference in BG-PVS and HP-PVS across the AD spectrum (p > 0.05). Individuals with moderate and frequent/severe CSO-PVS had a higher diagnostic conversion risk than individuals with no/mild CSO-PVS (log-rank p < 0.001 for all) in the combined CN and MCI group. Further Cox regression analyses revealed that moderate and frequent/severe CSO-PVS were associated with a higher risk of diagnostic conversion (HR = 2.007, 95% CI = 1.382-2.914, p < 0.001; HR = 2.676, 95% CI = 1.830-3.911, p < 0.001, respectively). A higher CSO-PVS number was associated with baseline cognitive performance and longitudinal cognitive decline in all cognitive tests (p < 0.05 for all).

CONCLUSIONS

CSO-PVS were more common in MCI and AD and were associated with cognitive decline across the AD spectrum.

The association of enlarged perivascular space with microglia-related inflammation and Alzheimer's pathology in cognitively normal elderly

BACKGROUND

Glymphatic dysfunction may contribute to the accumulation of Alzheimer's disease (AD) pathologies. Conversely, AD pathologic change might also cause neuroinflammation and aggravate glymphatic dysfunction, forming a loop that accelerates AD progression. In vivo validations are needed to confirm their relationships.

METHODS

In this study, we included 144 cognitively normal participants with AD pathological biomarker data (baseline CSF Aβ_1-42, T-Tau, P-Tau₁₈₁; plasma P-Tau₁₈₁ at baseline and at least one follow-up) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Each subject had completed structural MRI scans. Among them, 117 subjects have available neuroinflammatory biomarker (soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and 123 subjects have completed two times [18F]-florbetapir PET. The enlarged PVS (EPVS) visual rating scores in basal ganglia (BG) and centrum semiovale (CS) were assessed on T1-weighted images to reflect glymphatic dysfunction. Intracranial volume and white matter hyperintensities (WMH) volume were also calculated for further analysis. We performed stepwise linear regression models and mediation analyses to estimate the association between EPVS severity, sTREM2, and AD biomarkers.

RESULTS

CS-EPVS degree was associated with CSF sTREM2, annual change of plasma P-tau₁₈₁ and total WMH volume, whereas BG-EPVS severity was associated with age, gender and intracranial volume. The sTREM2 mediated the association between CSF P-tau₁₈₁ and CS-EPVS.

CONCLUSION

Impaired glymphatic dysfunction could contribute to the accumulation of pathological tau protein. The association between tauopathy and glymphatic dysfunction was mediated by the microglia inflammatory process. These findings may provide evidence for novel treatment strategies of anti-neuroinflammation therapy in the early stage.

Perivascular Spaces, Glymphatic System and MR

The importance of the perivascular space (PVS) as one of the imaging markers of cerebral small vessel disease (CSVD) has been widely appreciated by the neuroradiologists. The PVS surrounds the small blood vessels in the brain and has a signal consistent with the cerebrospinal fluid (CSF) on MR. In a variety of physio-pathological statuses, the PVS may expand. The discovery of the cerebral glymphatic system has provided a revolutionary perspective to elucidate its pathophysiological mechanisms. Research on the function and pathogenesis of this system has become a prevalent topic among neuroradiologists. It is now believed that this system carries out the similar functions as the lymphatic system in other parts of the body and plays an important role in the removal of metabolic waste and the maintenance of homeostatic fluid circulation in the brain. In this article, we will briefly describe the composition of the cerebral glymphatic system, the influencing factors, the MR manifestations of the PVS and the related imaging technological advances. The aim of this research is to provide a reference for future clinical studies of the PVS and glymphatic system.