Assessing interstitial fluid dynamics in type 2 diabetes mellitus and prediabetes cases through diffusion tensor imaging analysis along the perivascular space.

Background and purpose: Glymphatic system in type 2 diabetes mellitus (T2DM) but not in the prodrome, prediabetes (Pre-DM) was investigated using diffusion tensor image analysis along the perivascular space (DTI-ALPS). Association between glymphatic system and insulin resistance of prominent characteristic in T2DM and Pre-DM between is yet elucidated. Therefore, this study delves into the interstitial fluid dynamics using the DTI-ALPS in both Pre-DM and T2DM and association with insulin resistance. Materials and methods: In our cross-sectional study, we assessed 70 elderly individuals from the Bunkyo Health Study, which included 22 with Pre-DM, 18 with T2DM, and 33 healthy controls with normal glucose metabolism (NGM). We utilized the general linear model (GLM) to evaluate the ALPS index based on DTI-ALPS across these groups, considering variables like sex, age, intracranial volume, years of education, anamnesis of hypertension and hyperlipidemia, and the total Fazekas scale. Furthermore, we have explored the relationship between the ALPS index and insulin resistance, as measured by the homeostasis model assessment of insulin resistance (HOMA-IR) using GLM and the same set of covariates. Results: In the T2DM group, the ALPS index demonstrated a reduction compared with the NGM group [family-wise error (FWE)-corrected p < 0.001; Cohen's d = -1.32]. Similarly, the Pre-DM group had a lower ALPS index than the NGM group (FWE-corrected p < 0.001; Cohen's d = -1.04). However, there was no significant disparity between the T2DM and Pre-DM groups (FWE-corrected p = 1.00; Cohen's d = -0.63). A negative correlation was observed between the ALPS index and HOMA-IR in the combined T2DM and Pre-DM groups (partial correlation coefficient r = -0.35, p < 0.005). Conclusion: The ALPS index significantly decreased in both the pre-DM and T2DM groups and showed a correlated with insulin resistance. This indicated that changes in interstitial fluid dynamics are associated with insulin resistance.

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.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping.

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Glymphatic system impairment in corticobasal syndrome: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the along the perivascular space (ALPS) index based on the diffusion tensor image ALPS (DTI-ALPS) in corticobasal degeneration with corticobasal syndrome (CBD-CBS) and investigate its correlation with motor and cognitive functions. MATERIALS AND METHODS: The data of 21 patients with CBD-CBS and 17 healthy controls (HCs) were obtained from the 4-Repeat Tauopathy Neuroimaging Initiative and the Frontotemporal Lobar Degeneration Neuroimaging Initiative databases. Diffusion magnetic resonance imaging was performed using a 3-Tesla MRI scanner. The ALPS index based on DTI-ALPS was automatically calculated after preprocessing. The ALPS index was compared between the CBD-CBS and HC groups via a general linear model analysis, with covariates such as age, sex, years of education, and intracranial volume (ICV). Furthermore, to confirm the relation between the ALPS index and the motor and cognitive score in CBD-CBS, the partial Spearman's rank correlation coefficient was calculated with covariates such as age, sex, years of education, and ICV. A p value of < 0.05 was considered as statistically significant in all statistical analyses. RESULTS: The ALPS index of CBD-CBS was significantly lower than that of HC (Cohen's d = - 1.53, p < 0.005). Moreover, the ALPS index had a significant positive correlation with the mini mental state evaluation score (rs = 0.65, p < 0.005) and a significant negative correlation with the unified Parkinson's Disease Rating Scale III score (rs = - 0.75, p < 0.001). CONCLUSION: The ALPS index of patients with CBD-CBS, which is significantly lower than that of HCs, is significantly associated with motor and cognitive functions.

Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity. MATERIALS AND METHODS: This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively. RESULTS: The ALPS index was significantly lower in the sleep disruption group than in the HC group (p = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p < 0.001). Two significant negative correlations were also found between the ALPS index and PSQI component 2 (sleep latency, FDR-corrected p < 0.001) and 6 (the use of sleep medication, FDR-corrected p < 0.001). CONCLUSION: Our findings suggest that glymphatic system impairment contributes to sleep disruption in young adults.

Reproducibility of automated calculation technique for diffusion tensor image analysis along the perivascular space.

PURPOSE: The method of diffusion tensor image analysis along the perivascular space (DTI-ALPS) was gathering attention to evaluate the brain's glymphatic function or interstitial fluid dynamics. However, to the best knowledge, no study was conducted on the reproducibility of these automated methods for ALPS index values. Therefore, the current study evaluated the ALPS index reproducibility based on DTI-ALPS using two major automated calculation techniques in scan and rescan of the same subject on the same day. MATERIALS AND METHODS: This study included 23 participants, including 2 with Alzheimer's disease, 15 with mild cognitive impairment, and 6 with cognitive normals. Scan and rescan data of diffusion magnetic resonance images were obtained, as well as automatically index for ALPS (ALPS index) and ALPS index maintaining tensor vector orientation information (vALPS index) with region of interest on the template fractional anisotropy map calculated by FSL software.These ALPS indices were compared in terms of scan and rescan reproducibility. RESULTS: The absolute difference in ALPS-index values between scan and rescan was larger in the ALPS index than in the vALPS index by approximately 0.6% as the relative difference. Cohen's d for the left and right ALPS indices between methods were 0.121 and 0.159, respectively. CONCLUSION: The vALPS index based on DTI-ALPS maintaining tensor vector orientation information has higher reproducibility than the ALPS index. This result encourages a multisite study on the ALPS index with a large sample size and helps detect a subtle pathological change in the ALPS index.

Multisite harmonization of diffusion tensor image analysis along the perivascular space using the COMBined Association Test.

PURPOSE: This multisite study aimed to use the COMBined Association Test (COMBAT), a harmonization technique that uses regression of covariates with an empirical Bayesian framework, to harmonize diffusion tensor image analysis along the perivascular space (DTI-ALPS) variations caused by scanner, site, and protocol differences. MATERIALS AND METHODS: This study included multisite diffusion magnetic resonance imaging (dMRI) data of 45 patients with Alzheimer's disease (AD) and 82 cognitively normal (CN) participants from the AD neuroimaging initiative database. The dMRI data were obtained with two b values (0 and 1000 s/mm2) from 27 institutions and three different 3-Tesla MRI scanners (two vendors). The ALPS index was calculated from multisite dMRI data, and COMBAT was used to harmonize the factors causing site variations. Welch's t test was used, Cohen's d was calculated to compare the difference in the ALPS index between AD and CN before and after harmonization, and Pearson's correlation coefficient was calculated to assess the relationships between the ALPS index and the cognitive score, [18F] fluorodeoxyglucose (FDG)-positron emission tomography (PET), and [18F] florbetapir (AV45)-PET standardized uptake value ratios (SUVRs). RESULTS: COMBAT harmonized scanner differences and increased Cohen's d of the left and right ALPS indexes between AD and CN from 0.288 to 0.438 and 0.328 to 0.480, respectively. The ALPS indexes were significantly different between AD and CN after harmonization (P < 0.05) but not before it. Moreover, Pearson's correlation coefficients between the ALPS index and cognitive score, FDG-PET, and AV45-PET SUVRs were higher after harmonization than before it. CONCLUSION: This study demonstrates the application of COMBAT harmonization to eliminate between-scanner, site, and protocol variations in the ALPS index calculated from DTI-ALPS using dMRI and possibly facilitate the use of the ALPS index in multi-center studies.