Impaired glymphatic system for upper limb motor dysfunction in patients with acute ischemic stroke

Introduction

As a prevalent neurological condition worldwide, stroke is a leading cause of profound disabilities and mortality (1,2). It is generally categorized into two main types: ischemic stroke and hemorrhagic stroke, with the former accounting for approximately 85% of all strokes (3). Acute ischemic stroke (AIS) is a prevalent cerebrovascular disorder characterized by insufficient cerebral perfusion and subsequent accumulation of metabolic waste products. Motor dysfunction, particularly upper limb motor dysfunction, is a prevalent consequence experienced by the majority of post-stroke survivors, significantly impairing their activities of daily living. However, despite its high prevalence, the neurobiological mechanisms underlying post-stroke upper limb motor dysfunction remain poorly understood.

The glymphatic system, proposed by Iliff et al. (4), has recently been recognized for its crucial role in waste clearance and fluid balance maintenance, facilitating the exchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) (5-7). The glymphatic system consists of three key components: a periarterial channel facilitating the inflow of CSF, a perivenous pathway responsible for the outflow of ISF, and an astrocytic aquaporin-4 (AQP4)-dependent exchange pathway within the parenchyma (8-10). The perivascular spaces (PVS) are essential in influencing the effectiveness of the glymphatic system, as they are enveloped by blood vessels and lined with astrocytic endfeet. These PVS can be further classified into periarterial spaces, which facilitate CSF influx into the brain, and perivenous spaces, which serve as conduits for CSF efflux from the brain. The glymphatic system plays a crucial role in the CSF transportation and the efficient clearance of detrimental proteins and metabolites generated within the brain parenchyma. The discovery of the changes occurring within the glymphatic system has proven immensely helpful in enhancing our understanding of the complex pathophysiological processes associated with ischemic stroke. In cases of ischemic stroke, the depletion of essential nutrients such as glucose and oxygen can result in irreversible neuronal damage, a devastating consequence that is often accompanied by the generation of harmful metabolic byproducts that further exacerbate the condition. Recent research has elucidated that glymphatic flow plays a significant role in the intricate pathophysiology of ischemic stroke, highlighting its importance in the clearance of these metabolic waste products and the maintenance of neuronal health during such critical events (11). Present studies have demonstrated that ischemic stroke impaired not only paravascular CSF influx but also glymphatic clearance activity and the polarization of AQP4 (12,13). Defining the alteration in glymphatic function is of great importance, as compromised glymphatic clearance may impede the elimination of metabolic wastes from brain tissue, resulting in the accumulation of proteins and toxic substances (14,15). However, there is no consensus regarding the changes in glymphatic function and its role in AIS.

In recent years, there have been advancements in imaging techniques for investigating glymphatic system activity (16-18). Some studies have reported the use of contrast-enhanced magnetic resonance imaging (MRI) with intrathecal or intravenous gadolinium contrast agent to assess glymphatic function (19,20). However, this method is considered invasive, requiring multiple scans and posing a risk of neurotoxicity. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) is an emerging non-invasive technique that provides an attractive new approach to evaluate glymphatic system function with good stability and intraobserver consistency (21,22). The utilization of the DTI-ALPS technique has revealed a discernible impairment in glymphatic function associated with Alzheimer’s disease (23), cerebral small vessel disease (24), sleep disorders (25), Parkinson’s disease (26,27), and end-stage kidney disease (28), thereby establishing its correlation with more pronounced clinical symptoms. Zhang et al. (14) compared the ALPS index to the classical detection of glymphatic clearance function, which was calculated on glymphatic MRI following intrathecal administration of gadolinium. Their results demonstrated a significant correlation between these two methods. In recent years, numerous studies have investigated the role of the lymphatic drainage system in the modulation mechanism of AQP4 changes, activation of neuroinflammation, and formation of cerebral edema (6,13,29,30). However, a consensus regarding the relationship between changes in glymphatic function and AIS has not yet been reached. We speculate that the glymphatic function of patients with AIS may be impaired, and this impairment may be related to the clinical symptoms and prognosis of the patients. The objective of this study was to investigate alterations in the ALPS index, a marker of glymphatic function, in AIS patients with upper limb motor dysfunction, as well as identify clinical factors associated with these changes. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1170/rc).

Methods

Participants

This prospective study included consecutive patients diagnosed with AIS, and age- and sex-matched control cases between May 2023 and September 2024. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All participants provided written informed consent prior to enrollment, and the study protocols were approved by the Institutional Review Board of Hospital of Chengdu University of Traditional Chinese Medicine (No. 2023KL-023). Stroke patients underwent clinical examinations, and their medical histories were reviewed. Patients were considered eligible if they met the following criteria: (I) diagnosis of first-ever AIS within 14 days of the onset of stroke; (II) age between 18 and 80 years; (III) subcortical ischemic stroke in one hemisphere of the brain in anterior circulation; (IV) presented with a unilateral upper limb motor dysfunction in the upper limb or hand. The exclusion criteria were as follows: (I) intracranial hemorrhage, brain tumor, cranium trauma, previous brain surgery; (II) previous nonlacunar infarct; (III) the quality of diffusion tensor imaging (DTI) imaging was poor or standard imaging was not performed; (IV) lesion areas overlapping the regions used to calculate the DTI-ALPS index; (V) missing or incomplete clinical data. In addition to sociodemographic data, we documented a range of parameters and clinical information, including male sex, hypertension, diabetes mellitus, hyperlipidemia, atrial fibrillation, coronary heart disease, and smoking history. Furthermore, the duration from the onset of the stroke (the interval between the MRI assessment and the time of stroke occurrence), the volume of the infarct, and the location of the infarct (whether in the right or left cerebral hemisphere) were also documented. The Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) score was utilized to evaluate motor function and reflex activity of affected upper extremity joints at baseline and follow-up (31). This assessment employs a three-point ordinal scale (0, 1, 2) for scoring purposes, encompassing a total of 33 items. Furthermore, we employed the National Institutes of Health Stroke Scale (NIHSS) to evaluate the degree of stroke severity (32). All evaluations were conducted on the day prior to the MRI assessment. In addition, 29 healthy controls (HCs) who were matched in terms of age and sex during the same time period were included. These individuals underwent identical MRI examinations to those of the stroke patients. The screening process for participants is shown in Figure 1.

Figure 1 Study flow chart based on the inclusion and exclusion criteria. AIS, acute ischemic stroke; DTI, diffusion tensor imaging; MRI, magnetic resonance imaging.

MRI protocol

All participants underwent MRI using a 3.0 T MRI scanner (MR750, GE Healthcare, Waukesha, WI, USA) with an 8-channel phased-array head coil. All examinations included T1-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI), and DTI. DTI was conducted utilizing a spin-echo single-shot echo-planar pulse sequence, which was configured with the subsequent parameters: b-value =0, 1,000 s/mm², repetition time/echo time (TR/TE) =6,800/76 ms, diffusion gradient encoding directions =64, field of view (FOV) =240 mm × 240 mm, matrix =120×120, and slice thickness =2 mm. A total of 70 axial slices without inter-slice gap covering the cerebral hemispheres were collected.

Image processing

The MRI raw data underwent initial format conversion using dcm2niix (Version 2016, https://www.nitrc.org): transforming Digital Imaging and Communications in Medicine (DICOM) into Neuroimaging Informatics Technology Initiative (NIFIT). DTI preprocessing was conducted using FMRIB Software Library (FSL, https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/), including: (I) quality assessment conducted to evaluate artifacts present in all DWI images; (II) compensation for eddy current-induced and movement-related distortions using the eddy function; (III) calculation of diffusion tensor maps and fractional anisotropy (FA) maps using the ‘DTIFIT’ command; (IV) generation of a binary brain mask with a fractional intensity threshold set to 0.2; (V) manual placement of 5-mm-diameter regions of interest (ROI) within the region of bilateral projection and association fibers on color-coded FA maps. It is important to note that although the target fibers are clearly visualized, they are not encompassed within the infarct tissue. The infarct volume was quantified based on DWI. A manually delineated polygonal ROI encompassing the entire infarct was drawn on each DW image. Subsequently, the ROIs from all images were merged to create a comprehensive volume of interest for accurate assessment of the infarct size.

Assessment of glymphatic system by the DTI-ALPS index

The activity of the glymphatic system was assessed using the DTI-ALPS method, which enables evaluation of diffusivity located within the PVS on a cross-sectional image at the level of the body of the lateral ventricle (22). The corticofugal corona radiata projection fibers at this level exhibit a craniocaudal orientation (z-axis in the coordinate system). The superior longitudinal fascicle, representing association fibers, demonstrates an anterior–posterior trajectory (y-axis in the coordinate system), whereas subcortical fibers traverse along the x-axis. To quantify glymphatic activity, the ALPS index is defined as follows:

DTI-ALPSindex=mean(Dxxproj,Dxxassoc)mean(Dyyproj,Dzzassoc)[1]

where D_xxproj and D_xxassoc are the x-axis diffusivity in the area of projection fibers and association fibers, respectively. D_yyproj and D_zzassoc are the z-axis diffusivity in the area of projection fibers and association fibers, respectively. The fixed spherical ROI with diameters of 5 mm were precisely positioned on the ventricular levels, specifically targeting the projection and association fibers. The differentiation between these areas was determined based on the automatically generated color-mapped anisotropy using FSL software. Figure 2 illustrates an exemplary placement of ROIs for ALPS index measurement. Two neuroradiologists (with 14 and 6 years of respective experience) independently performed all measurements blind to the clinical information of the given participants. To evaluate the reliability and reproducibility of the DTI-ALPS index, a random sample of 30 participants was selected from the total cohort. The same radiologist (Lichuan Zeng) independently delineated the ROIs for these participants two weeks after the initial segmentation, allowing for the assessment of intrarater reliability. The intraclass correlation coefficient (ICC) was found to be 0.823, indicating substantial agreement.

Figure 2 The assessment of glymphatic system by calculating the DTI-ALPS index. Four 5-mm-diameter ROI were placed in the area of bilateral projection and association fibers on color-coded FA maps (A). The schematic diagram (B) indicates the relationship among the perivascular space, projection fibers, and association fibers. DTI-ALPS, diffusion tensor imaging analysis along the perivascular space; FA, fractional anisotropy; ROI, regions of interest.

Statistical analysis

Statistical analyses were performed using SPSS (version 16.0; IBM Corp., Armonk, NY, USA) and P values <0.05 were considered indicative of a statistical significance. The interobserver variability in the measurements of ALPS index and infarct volume was assessed by ICCs with 95% confidence intervals (CIs). The ultimate values for all measurements were derived by calculating the average from the independent assessments conducted by two different observers. Continuous variables were presented as mean with standard deviation (SD) analyzed by t-test. Categorical variables were presented as frequencies with percentages and analyzed using Chi-squared tests. A paired t-test was used to evaluate the interhemispheric differences in ALPS index (infarct side vs. contralateral normal side). A mixed-design analysis of variance (ANOVA) was used to detect any significant differences between bilateral DTI-ALPS index in AIS patients and HCs. Spearman correlation or Pearson’s correlation analyses were performed as appropriate to analyze the relationships of the DTI-ALPS index of the infarct hemisphere with infarct volume, time since stroke onset, FMA-UE scores, and NIHSS scores in the AIS group.

Results

Demographics and clinical characteristics

We finally included 59 patients (40 men; age range, 33–81 years; mean age: 62.4±10.8 years) with AIS, and 29 HCs (17 men; age range, 36–75; mean age: 58.7±10.6 years). The two groups were matched in terms of gender and age (P>0.05). Of these 59 ischemic stroke patients, 18 underwent a second MRI scan after two months. Among 59 patients, 27 (45.8%) had left hemispheric infarct. The mean admission NIHSS score was 10.8±6.3 points (range, 2–24 points), and the FMA-UE score was 36.2±10.1 points (range, 13–59 points). The mean time since stroke onset was 5.9±3.6 days (range, 0.5–14 days). The measurements of infarct volumes (ICC =0.813, 95% CI: 0.795–0.824, P<0.001), and bilateral ALPS indices (ICC =0.817, 95% CI: 0.812–0.834, P<0.001) exhibited high inter-observer consistency. The median infarct volume (mm³) of 59 patients was 726 (range, 104–44,686). The demographic and clinical characteristics of the participants are presented in Table 1.

Comparison of the DTI-ALPS index within the AIS patients and HCs

In the HC group, the mean ALPS index was 1.450±0.211 (left side) and 1.450±0.155 (right side), without a significant difference observed between them (P>0.05). In patients with left cerebral infarct, the mean ALPS index of left side was 1.233±0.078, significantly (P<0.001) lower than that of the contralateral side (1.362±0.107). In patients with right cerebral infarct, the mean ALPS index of the right side was 1.217±0.165, significantly (P<0.001) lower than that of the contralateral side (1.317±0.158). The mean ALPS index ipsilateral to infarct side of the 59 patients was 1.225±0.132, significantly (P<0.001) lower than the contralateral side (1.337±0.138). The ALPS index in the infarct side was significantly lower than that on the same side in the HC group (P<0.001). It is noteworthy that the mean ALPS index of the side contralateral to infarct was significantly lower than that of the same side in the HC group (P<0.001). The interhemispheric differences in the ALPS index of the AIS patients and HCs are illustrated in Figure 3.

Figure 3 Box plots showed the difference in ALPS index between patients with ischemic stroke and normal subjects. The graph showed a significantly lower DTI-ALPS index in the stroke side compared to contralateral side in ischemic stroke patients and the same side in the HCs. AIS, acute ischemic stroke; ALPS, along the perivascular space; DTI-ALPS, diffusion tensor imaging analysis along the perivascular space; HC, healthy control.

Association with ALPS index and clinics

The DTI-ALPS index demonstrated a significant positive correlation (ρ=0.404, P=0.001) with FMA-UE and a notable negative correlation (ρ=−0.484, P<0.001) with the NIHSS score. Associations between the DTI-ALPS index and FMA-UE scores and NIHSS score are shown in Figure 4. The ALPS index exhibited no significant rank correlation with time since stroke onset and infarct volume (P>0.05). However, subsequent MRI follow-up (mean follow-up interval was 62 days) of the 18 patients revealed a statistically significant elevation in the ALPS index compared to baseline (1.296±0.141 vs. 1.174±0.109, P=0.001) (Figure 5). The FMA-UE score and NIHSS score at follow-up showed significant differences compared to the baseline (51.8±6.2 vs. 34.1±12.3, 5.3±3.5 vs. 12.1±5.7, P<0.001).

Figure 4 Scatterplots with regression lines showed the correlations of the ALPS index with FMA-UE scores (A) and NIHSS scores (B). ALPS, along the perivascular space; FMA-UE, Fugl-Meyer Assessment of the Upper Extremity; NIHSS, National Institutes of Health Stroke Scale.

Figure 5 Comparison of DTI-ALPS index of the 18 patients in baseline and follow-up. **, P=0.001. ALPS, along the perivascular space; DTI-ALPS, diffusion tensor imaging analysis along the perivascular space.

Discussion

This prospective study draws three primary conclusions. First, we observed a significant reduction in brain glymphatic activity in AIS patients. Specifically, the ALPS index in the ipsilateral hemisphere to the infarct side was markedly lower than that in the contralateral normal cerebral hemisphere (1.225 vs. 1.337; P<0.001) and also significantly lower than that in HCs (P<0.001). Second, the DTI-ALPS index was found to be correlated with the severity of AIS. Third, changes in the DTI-ALPS index were associated with the progression of AIS. These findings suggest that alterations in the glymphatic system provide a novel perspective on the pathogenesis of ischemic stroke.

The glymphatic system is crucial for waste clearance in the central nervous system and maintaining cerebral homeostasis. Ascertaining the role of the glymphatic system, which facilitates the clearance of neurotoxic waste from the brain, is crucial in elucidating the complex interactions contributing to AIS and its sequelae. The observed reduction in the ALPS index among stroke patients in this study indicates a potential impairment in glymphatic function, which may hinder the clearance of neurotoxic metabolites and thereby exacerbate motor dysfunction. Glymphatic dysfunction can be caused by cerebral ischemic infarction, which in turn may contribute to the development of related complications, such as edema. Reversible neuronal injury can occur due to glucose and oxygen depletion following ischemic stroke, which is accompanied by the generation of metabolic byproducts, such as pro-inflammatory cytokines and chemokines (15). Impaired glymphatic clearance subsequently results in the accumulation of toxic solutes and proteins within the infarcted region. Meanwhile, dysfunction of the glymphatic system plays an important role cerebral edema after stroke. Typically, CSF that is derived from the subarachnoid space permeates into the brain tissue through the periarterial spaces that envelop penetrating arteries. In this process, it collaborates with AQP4 water channels, allowing for the mixing of CSF with the ISF found within the parenchyma. Following this, the ISF, along with its dissolved substances, is transported into the perivenous and perineuronal spaces prior to leaving the brain tissue (5). The initiation of poststroke brain edema involves ischemic spreading depolarizations, followed by subsequent vasoconstriction, which subsequently leads to the enlargement of PVS and a twofold increase in glymphatic inflow speeds (11). Consequently, there is an increased influx of fluid into the brain parenchyma, resulting in enhanced tissue swelling. Dysfunction in the circulation of CSF is observed during an AIS, which may act as one of the fundamental pathological factors that lead to tissue swelling and cerebral edema (13). AQP4 channels are thought to be essential components of the glymphatic system, which are predominantly observed in astrocyte endfeet surrounding blood vessels, with less common occurrence in cell bodies (5). The polarity of AQP4 is essential for promoting the interchange between CSF and ISF, thereby ensuring the efficiency of the glymphatic system. However, abnormal expression of AQP4 may occur in ischemic stroke patients. Ribeiro et al. reported a rapid up-regulation of AQP4 expression in astrocyte endfeet within 1 hour after stroke onset, followed by a second peak at 48 hours (33). Additionally, the distribution of AQP4 shifts towards the astrocyte soma membrane. Another recent study revealed that the polarization of AQP4 around the microvascular structures exhibited a significant decrease on day 2 after middle cerebral artery occlusion (MCAO), yet showed a notable increase on day 7 (13). The upregulation and change of distribution of AQP4 following stroke may contribute to an augmented occurrence of cerebral edema decline of waste clearance post-stroke. Zhu et al. reported a severe impairment of paravascular CSF influx and glymphatic clearance following MCAO in mice with stroke models. Additionally, they observed a significant decrease in AQP4 polarization around the microvascular structures on day 2 after MCAO across both the infarcted core and peri-infarct regions (13). In the present study, we also observed a reduction in glymphatic function in the cerebral hemisphere affected by AIS, consistent with findings from other studies (13,34-36).

Wang et al. have demonstrated that cerebrovascular activity is a major factor in the CSF flow dynamics (37). The neurovascular unit (NVU) plays a crucial role in regulating cerebral blood flow (CBF) to sustain adequate metabolic activity of the brain. Neurovascular coupling (NVC) refers to the process in which increased neural activity leads to an augmentation of local CBF. This dynamic is crucial as it not only ensures the delivery of essential metabolites but also aids in the clearance of metabolic byproducts from the region (38,39). NVC is impaired early after stroke due to the reduction in neural activity, which normally drives increases in CBF via feed-forward mechanisms. In the acute phase following the onset of ischemia, the brain’s ability to maintain cerebral autoregulation may be compromised, which is closely associated with the impairment of NVC. NVU dysfunction directly contributes to the disruption of the blood-brain barrier (BBB), thereby increasing the susceptibility to vasogenic cerebral edema. Moreover, pericytes exacerbate the progression of cerebral edema by adopting a proinflammatory phenotype. Chao et al. demonstrated a significant decrease in NVC and ALPS index among stroke patients. Furthermore, the ALPS index exhibited positive correlations with both global and local NVC, suggesting that abnormal regional NVC may contribute to post-stroke depression by impairing glymphatic function. These findings imply that NVC abnormalities could potentially lead to compromised glymphatic system functionality (36).

Another noteworthy finding in this study is that the mean ALPS index of the contralateral side to the infarct was significantly lower than that of the corresponding side in the HC group, which differs from the findings reported in other studies. Qin et al. (34) reported that the DTI-ALPS index of the unaffected side in ischemic stroke patients was slightly lower compared to the HC group (1.381±0.172 vs. 1.454±0.107), although this difference did not reach statistical significance (t=−1.87, P=0.067). It appears that acute stroke patients may demonstrate a reduction in glymphatic function not only in the affected hemisphere but also in the unaffected hemisphere, albeit to a lesser extent compared to the affected hemisphere. We speculate that ischemic stroke may cause damage to the glymphatic system function not only on the affected side, but also lead to issues such as sleep disturbances, respiratory dysfunction, and emotional problems after the stroke. These factors may affect the entire cerebral hemisphere rather than being limited to the glial lymphatic function of the infarcted hemisphere alone. Considering the limited sample sizes in this study, it is imperative to exercise caution when interpreting these findings, as their accuracy may not be as robust as anticipated. Consequently, further investigation is warranted to elucidate the presence of the brain lymphatic system in patients with ischemic infarction. A recent study (34) reported a significant lateralization effect of DTI-ALPS in healthy participants, with a higher left-side DTI-ALPS index compared to the right-side. However, our study did not observe this effect; many other studies have failed to demonstrate the lateralization of DTI-ALPS.

In the present study, the ALPS index of the ipsilateral hemisphere to the infarct were linearly negatively correlated with baseline NIHSS scores (ρ=−0.484, P<0.001) and positively correlated with FMA-UE scores (ρ=0.404, P=0.001). This finding is consistent with Qin et al. (34), indicating that a higher left DTI-ALPS index is associated with better simple Fugl-Meyer motor function scores. A recent study (13) also reported a significant decrease in the ALPS index on both the infarcted and contralateral sides among patients with poor outcomes (modified Rankin Scale score >2) as compared to those with favorable outcomes. These results indicate that patients with lower ALPS index may experience more extensive damage during the onset of AIS. We also attempted to investigate the relationship between changes in the ALPS index and improvements in NIHSS and FMA-UE scores among the 18 patients who completed the follow-up. Although a trend toward a positive correlation was observed between changes in the ALPS index and improvements in both NIHSS and FMA-UE scores, no statistically significant correlation was found between these variables. We believe that this may be associated with several potential factors. First, the relatively small sample size of completed follow-up cases may have introduced certain biases. Additionally, the duration of follow-up could have played a role. In this study, the follow-up period was set at 2 months; however, a longer follow-up period of 90 days or more might reveal more pronounced clinical improvements. Therefore, further studies are warranted to validate these findings. In addition, there was no rank correlation between infarct volume and ALPS index in our study. It is important to acknowledge that the infarct volume included in this study was relatively small and exhibited a skewed distribution, which may have influenced the exploration of the relationship between ALPS index and infarct volume. Further studies are required to determine the relationship between the ALPS index and the volume of infarction.

The function of the glymphatic system in patients with acute stroke is significantly associated with symptom severity. As stroke recovery progresses, glymphatic system function also gradually improves, indicating a bidirectional interaction between the two. By assessing the DTI-ALPS index in a cohort of AIS patients and correlating these findings with clinical measures of motor function, we aimed to elucidate the potential role of impaired glymphatic clearance in post-stroke recovery. The results indicate significant correlations between the DTI-ALPS index and clinical outcomes, providing insights into the implications of glymphatic dysfunction in AIS and highlighting its potential as a biomarker for predicting recovery and therapeutic response in stroke patients. Toh and Siow (35) indicated that the ALPS index rises as the duration since the onset of stroke increases, implying a restoration of glymphatic function after its initial disruption. However, there was no rank correlation between time since stroke onset and ALPS index in our study. The mean duration from stroke onset was 17.1±14.8 days (range, 1–60 days) in Toh et al.’s study, whereas ours reported a mean duration of 5.9±3.6 days (range, 0.5–14 days). We believe it may be related to the limited functional recovery of patients in a relatively short period of time. However, in this study, we observed a significant increase in the ALPS index 2 months post-ischemic stroke, potentially indicating recovery of glymphatic function subsequent to initial impairment. Consequently, this study presents the longitudinal alterations in glymphatic function following ischemic stroke. In terms of clinical implications, our findings suggest that monitoring the DTI-ALPS index may be beneficial for predicting recovery and guiding rehabilitation strategies in AIS patients. For instance, a lower ALPS index correlates with poorer outcomes, indicating that interventions aimed at enhancing glymphatic function could be crucial in improving patient prognosis. Furthermore, integrating DTI-ALPS assessments into routine clinical practice could facilitate early detection of glymphatic dysfunction, allowing for timely interventions that may mitigate long-term disability associated with AIS. This approach aligns with the growing emphasis on personalized medicine, where understanding individual patient profiles, including glymphatic function, can lead to more effective treatment plans.

It is widely acknowledged that ISF clearance is diminished following ischemic stroke in both animal and human studies. The arterial pulsation plays a crucial role in facilitating the perivascular exchange of CSF and ISF, and an increased pulsation can potentially expedite this process. Following treatment, patients with ischemic stroke experience enhanced blood flow and augmented vascular pulsation, thereby promoting the restoration of glymphatic drainage towards normalcy. The results of animal experiments demonstrated a significant impairment in AQP4 polarization on day 2 after MCAO, followed by partial recovery on day 7 (13). These findings are consistent with the glymphatic clearance process, providing support for the temporal recovery of impaired glymphatic system function. In addition, sleep plays a crucial role in facilitating glymphatic clearance of toxic proteins and waste products, as evidenced by Xie et al., who reported a 90% increase in glymphatic activity during sleep compared to significantly suppressed function in the awake state (40). Patients who have experienced a stroke display an irregular pattern of melatonin secretion, accompanied by an early and ineffective release of cortisol. This phenomenon is believed to contribute to the disturbances observed in their circadian rhythm (41). Disruptions in sleep among individuals who have experienced a stroke contribute to the dysfunction of the glymphatic system, resulting in the build-up of neurotoxic metabolites. The mechanism underlying the recovery of glymphatic function in patients with ischemic stroke remains elusive. It is speculated that this phenomenon may be attributed to remodeling of the glymphatic pathway, facilitating the elimination of fluids and byproducts linked to tissue damage in the context of an ischemic infarction. The dynamic alterations in glymphatic function during ischemic stroke may contribute to the modulation of the ALPS index.

Several limitations should be considered when interpreting our findings. First, the sample size was relatively small, with only 18 out of the 59 participants with AIS undergoing follow-up MRI scans. Second, our study primarily focused on patients with mild stroke, which may not fully represent all stroke populations. Therefore, it is crucial to conduct larger-scale studies to establish a robust correlation between the ALPS index and AIS. Third, it is important to note that the DTI-ALPS method might offer limited insights into the overall functionality of the glymphatic system (22,42). Hence, caution must be exercised when interpreting the relationship between the ALPS index and glymphatic function.

Conclusions

This research not only adds to the understanding of the glymphatic system’s role in acute stroke but also opens avenues for future studies aimed at exploring therapeutic interventions that target this pathway to improve recovery outcomes in AIS patients. The ALPS index demonstrated a decrease in ischemic stroke, indicating impaired glymphatic function. Moreover, significant correlations were observed between the ALPS index and severity of stroke as well as symptoms of upper limb motor dysfunction. Notably, during follow-up, the ALPS index exhibited an increase suggestive of recovery in glymphatic function. Therefore, the ALPS index holds potential as a novel neuroimaging biomarker for evaluating glymphatic function in patients with ischemic stroke.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1170/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1170/dss

Funding: This study was funded by the Sichuan Natural Science Foundation (No. 2024NSFSC0056), National Natural Science Foundation of China (No. 82505760) and Hospital of Chengdu University of Traditional Chinese Medicine (No. Y2023007).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1170/coif). The authors report that this study was funded by the Sichuan Natural Science Foundation (No. 2024NSFSC0056), National Natural Science Foundation of China (No. 82505760) and Hospital of Chengdu University of Traditional Chinese Medicine (No. Y2023007). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All study participants provided written informed consent prior to enrollment, and the study protocols have been approved by the Institutional Review Board of Hospital of Chengdu University of Traditional Chinese Medicine (No. 2023KL-023).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Campbell BCV, De Silva DA, Macleod MR, Coutts SB, Schwamm LH, Davis SM, Donnan GA. Ischaemic stroke. Nat Rev Dis Primers 2019;5:70. [Crossref] [PubMed]
2. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol 2019;18:459-80. [Crossref] [PubMed]
3. Campbell BCV, Khatri P. Stroke. Lancet 2020;396:129-42. [Crossref] [PubMed]
4. Iliff JJ, Wang M, Zeppenfeld DM, Venkataraman A, Plog BA, Liao Y, Deane R, Nedergaard M. Cerebral arterial pulsation drives paravascular CSF-interstitial fluid exchange in the murine brain. J Neurosci 2013;33:18190-9. [Crossref] [PubMed]
5. Al Masri M, Corell A, Michaëlsson I, Jakola AS, Skoglund T. The glymphatic system for neurosurgeons: a scoping review. Neurosurg Rev 2024;47:61. [Crossref] [PubMed]
6. Zou K, Deng Q, Zhang H, Huang C. Glymphatic system: a gateway for neuroinflammation. Neural Regen Res 2024;19:2661-72. [Crossref] [PubMed]
7. Zhu HH, Li SS, Wang YC, Song B, Gao Y, Xu YM, Li YS. Clearance dysfunction of trans-barrier transport and lymphatic drainage in cerebral small vessel disease: Review and prospect. Neurobiol Dis 2023;189:106347. [Crossref] [PubMed]
8. Klostranec JM, Vucevic D, Bhatia KD, Kortman HGJ, Krings T, Murphy KP, terBrugge KG, Mikulis DJ. Current Concepts in Intracranial Interstitial Fluid Transport and the Glymphatic System: Part I-Anatomy and Physiology. Radiology 2021;301:502-14. [Crossref] [PubMed]
9. Gao Y, Liu K, Zhu J. Glymphatic system: an emerging therapeutic approach for neurological disorders. Front Mol Neurosci 2023;16:1138769. [Crossref] [PubMed]
10. Yao D, Zhang R, Xie M, Ding F, Wang M, Wang W. Updated Understanding of the Glial-Vascular Unit in Central Nervous System Disorders. Neurosci Bull 2023;39:503-18. [Crossref] [PubMed]
11. Mestre H, Du T, Sweeney AM, Liu G, Samson AJ, Peng W, et al. Cerebrospinal fluid influx drives acute ischemic tissue swelling. Science 2020;367:eaax7171. [Crossref] [PubMed]
12. Gaberel T, Gakuba C, Goulay R, Martinez De Lizarrondo S, Hanouz JL, Emery E, Touze E, Vivien D, Gauberti M. Impaired glymphatic perfusion after strokes revealed by contrast-enhanced MRI: a new target for fibrinolysis? Stroke 2014;45:3092-6. [Crossref] [PubMed]
13. Zhu J, Mo J, Liu K, Chen Q, Li Z, He Y, Chang Y, Lin C, Yu M, Xu Y, Tan X, Huang K, Pan S. Glymphatic System Impairment Contributes to the Formation of Brain Edema After Ischemic Stroke. Stroke 2024;55:1393-404. [Crossref] [PubMed]
14. Zhang W, Zhou Y, Wang J, Gong X, Chen Z, Zhang X, Cai J, Chen S, Fang L, Sun J, Lou M. Glymphatic clearance function in patients with cerebral small vessel disease. Neuroimage 2021;238:118257. [Crossref] [PubMed]
15. Zbesko JC, Nguyen TV, Yang T, Frye JB, Hussain O, Hayes M, Chung A, Day WA, Stepanovic K, Krumberger M, Mona J, Longo FM, Doyle KP. Glial scars are permeable to the neurotoxic environment of chronic stroke infarcts. Neurobiol Dis 2018;112:63-78. [Crossref] [PubMed]
16. Sun B, Fang D, Li W, Li M, Zhu S. NIR-II nanoprobes for investigating the glymphatic system function under anesthesia and stroke injury. J Nanobiotechnology 2024;22:200. [Crossref] [PubMed]
17. Yu Q, Wang H, Zhang W, Zhang X, Zhao J, Gong L, Liu X. MRI-visible enlarged perivascular spaces in basal ganglia rather than centrum semiovale was associated with aneurysmal subarachnoid hemorrhage. Front Neurol 2024;15:1341499. [Crossref] [PubMed]
18. Keil SA, Braun M, O'Boyle R, Sevao M, Pedersen T, Agarwal S, Jansson D, Iliff JJ. Dynamic infrared imaging of cerebrospinal fluid tracer influx into the brain. Neurophotonics 2022;9:031915. [Crossref] [PubMed]
19. Edeklev CS, Halvorsen M, Løvland G, Vatnehol SAS, Gjertsen Ø, Nedregaard B, Sletteberg R, Ringstad G, Eide PK. Intrathecal Use of Gadobutrol for Glymphatic MR Imaging: Prospective Safety Study of 100 Patients. AJNR Am J Neuroradiol 2019;40:1257-64. [Crossref] [PubMed]
20. Watts R, Steinklein JM, Waldman L, Zhou X, Filippi CG. Measuring Glymphatic Flow in Man Using Quantitative Contrast-Enhanced MRI. AJNR Am J Neuroradiol 2019;40:648-51. [Crossref] [PubMed]
21. Si X, Guo T, Wang Z, Fang Y, Gu L, Cao L, Yang W, Gao T, Song Z, Tian J, Yin X, Guan X, Zhou C, Wu J, Bai X, Liu X, Zhao G, Zhang M, Pu J, Zhang B. Neuroimaging evidence of glymphatic system dysfunction in possible REM sleep behavior disorder and Parkinson's disease. NPJ Parkinsons Dis 2022;8:54. [Crossref] [PubMed]
22. Taoka T, Ito R, Nakamichi R, Nakane T, Kawai H, Naganawa S. Diffusion Tensor Image Analysis ALong the Perivascular Space (DTI-ALPS): Revisiting the Meaning and Significance of the Method. Magn Reson Med Sci 2024;23:268-90. [Crossref] [PubMed]
23. Hong H, Hong L, Luo X, Zeng Q, Li K, Wang S, Jiaerken Y, Zhang R, Yu X, Zhang Y, Lei C, Liu Z, Chen Y, Huang P, Zhang M. The relationship between amyloid pathology, cerebral small vessel disease, glymphatic dysfunction, and cognition: a study based on Alzheimer's disease continuum participants. Alzheimers Res Ther 2024;16:43. [Crossref] [PubMed]
24. Li H, Jacob MA, Cai M, Kessels RPC, Norris DG, Duering M, De Leeuw FE, Tuladhar AM. Perivascular Spaces, Diffusivity Along Perivascular Spaces, and Free Water in Cerebral Small Vessel Disease. Neurology 2024;102:e209306. [Crossref] [PubMed]
25. Bae YJ, Kim JM, Choi BS, Ryoo N, Song YS, Nam Y, Yoon IY, Cho SJ, Kim JH. Altered Brain Glymphatic Flow at Diffusion-Tensor MRI in Rapid Eye Movement Sleep Behavior Disorder. Radiology 2023;307:e221848. [Crossref] [PubMed]
26. Tian S, Hong H, Luo X, Zeng Q, Huang P, Zhang M. Association between body mass index and glymphatic function using diffusion tensor image-along the perivascular space (DTI-ALPS) in patients with Parkinson's disease. Quant Imaging Med Surg 2024;14:2296-308. [Crossref] [PubMed]
27. Cai X, Chen Z, He C, Zhang P, Nie K, Qiu Y, Wang L, Wang L, Jing P, Zhang Y. Diffusion along perivascular spaces provides evidence interlinking compromised glymphatic function with aging in Parkinson's disease. CNS Neurosci Ther 2023;29:111-21. [Crossref] [PubMed]
28. Lee YJ, Park KM, Heo CM, Park S, Kim YW, Lee D, Kim Y, Oh JS, Shin HS, Park BS. Changes in the glymphatic system before and after dialysis initiation in patients with end-stage kidney disease. Ren Fail 2023;45:2265665. [Crossref] [PubMed]
29. Sun C, Lin L, Yin L, Hao X, Tian J, Zhang X, Ren Y, Li C, Yang Y. Acutely Inhibiting AQP4 With TGN-020 Improves Functional Outcome by Attenuating Edema and Peri-Infarct Astrogliosis After Cerebral Ischemia. Front Immunol 2022;13:870029. [Crossref] [PubMed]
30. Szczygielski J, Kopańska M, Wysocka A, Oertel J. Cerebral Microcirculation, Perivascular Unit, and Glymphatic System: Role of Aquaporin-4 as the Gatekeeper for Water Homeostasis. Front Neurol 2021;12:767470. [Crossref] [PubMed]
31. Sullivan KJ, Tilson JK, Cen SY, Rose DK, Hershberg J, Correa A, Gallichio J, McLeod M, Moore C, Wu SS, Duncan PW. Fugl-Meyer assessment of sensorimotor function after stroke: standardized training procedure for clinical practice and clinical trials. Stroke 2011;42:427-32. [Crossref] [PubMed]
32. Kwah LK, Diong J. National Institutes of Health Stroke Scale (NIHSS). J Physiother 2014;60:61. [Crossref] [PubMed]
33. Ribeiro Mde C, Hirt L, Bogousslavsky J, Regli L, Badaut J. Time course of aquaporin expression after transient focal cerebral ischemia in mice. J Neurosci Res 2006;83:1231-40. [Crossref] [PubMed]
34. Qin Y, Li X, Qiao Y, Zou H, Qian Y, Li X, Zhu Y, Huo W, Wang L, Zhang M. DTI-ALPS: An MR biomarker for motor dysfunction in patients with subacute ischemic stroke. Front Neurosci 2023;17:1132393. [Crossref] [PubMed]
35. Toh CH, Siow TY. Glymphatic Dysfunction in Patients With Ischemic Stroke. Front Aging Neurosci 2021;13:756249. [Crossref] [PubMed]
36. Chao X, Fang Y, Lu Z, Wang J, Yin D, Shi R, Wang P, Liu X, Sun W. Impairments of neurovascular coupling after stroke lower glymphatic system function and lead to depressive symptom: A longitudinal cohort study. J Affect Disord 2024;367:255-62. [Crossref] [PubMed]
37. Wang Y, van Gelderen P, de Zwart JA, Özbay PS, Mandelkow H, Picchioni D, Duyn JH. Cerebrovascular activity is a major factor in the cerebrospinal fluid flow dynamics. Neuroimage 2022;258:119362. [Crossref] [PubMed]
38. Holstein-Rønsbo S, Gan Y, Giannetto MJ, Rasmussen MK, Sigurdsson B, Beinlich FRM, Rose L, Untiet V, Hablitz LM, Kelley DH, Nedergaard M. Glymphatic influx and clearance are accelerated by neurovascular coupling. Nat Neurosci 2023;26:1042-53. [Crossref] [PubMed]
39. Wang L, Xiong X, Zhang L, Shen J. Neurovascular Unit: A critical role in ischemic stroke. CNS Neurosci Ther 2021;27:7-16. [Crossref] [PubMed]
40. Xie L, Kang H, Xu Q, Chen MJ, Liao Y, Thiyagarajan M, O'Donnell J, Christensen DJ, Nicholson C, Iliff JJ, Takano T, Deane R, Nedergaard M. Sleep drives metabolite clearance from the adult brain. Science 2013;342:373-7. [Crossref] [PubMed]
41. Adamczak-Ratajczak A, Kupsz J, Owecki M, Zielonka D, Sowinska A, Checinska-Maciejewska Z, Krauss H, Michalak S, Gibas-Dorna M. Circadian rhythms of melatonin and cortisol in manifest Huntington's disease and in acute cortical ischemic stroke. J Physiol Pharmacol 2017;68:539-46.
42. Ringstad G. Glymphatic imaging: a critical look at the DTI-ALPS index. Neuroradiology 2024;66:157-60. [Crossref] [PubMed]