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Costa T, Manuello J, Premi E, Mattioli I, Lasagna L, Lahoz CB, Cauda F, Duca S, Liloia D. Evaluating the robustness of DTI-ALPS in clinical context: a meta-analytic parallel on Alzheimer's and Parkinson's diseases. Sci Rep 2024; 14:26381. [PMID: 39487289 PMCID: PMC11530450 DOI: 10.1038/s41598-024-78132-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 10/29/2024] [Indexed: 11/04/2024] Open
Abstract
In recent years, the glymphatic system has received increasing attention due to its possible implications in biological mechanisms associated with neurodegeneration. In the field of human brain mapping, this led to the development of diffusion tensor image analysis along the perivascular space (DTI-ALPS) index. While this index has been repeatedly used to investigate possible differences between neurodegenerative disorders and healthy controls, a comprehensive evaluation of its stability across multiple measurements and different disorders is still missing. In this study, we perform a Bayesian meta-analysis aiming to assess the consistency of the DTI-ALPS results previously reported for 12 studies on Parkinson's disease and 11 studies on Alzheimer's disease. We also evaluated if the measured value of the DTI-ALPS index can quantitatively inform the diagnostic process, allowing disambiguation between these two disorders. Our results, expressed in terms of Bayes' Factor values, confirmed that the DTI-ALPS index is consistent in measuring the different functioning of the glymphatic system between healthy subjects and patients for both Parkinson's disease (Log10(BF10) = 30) and Alzheimer's disease (Log10(BF10) = 10). Moreover, we showed that the DTI-ALPS can be used to compare these two disorders directly, therefore providing a first proof of concept supporting the reliability of taking into consideration this neuroimaging measurement in the diagnostic process. Our study underscores the potential of the DTI-ALPS index in advancing our understanding of neurodegenerative pathologies and enhancing clinical diagnostics.
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Affiliation(s)
- Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
- FOCUS Laboratory, Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy.
| | - Enrico Premi
- Stroke Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Irene Mattioli
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Luca Lasagna
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Clara Ballonga Lahoz
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy
| | - Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy
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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; 23:268-290. [PMID: 38569866 PMCID: PMC11234944 DOI: 10.2463/mrms.rev.2023-0175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024] Open
Abstract
More than 5 years have passed since the Diffusion Tensor Image Analysis ALong the Perivascular Space (DTI-ALPS) method was proposed with the intention of evaluating the glymphatic system. This method is handy due to its noninvasiveness, provision of a simple index in a straightforward formula, and the possibility of retrospective analysis. Therefore, the ALPS method was adopted to evaluate the glymphatic system for many disorders in many studies. The purpose of this review is to look back and discuss the ALPS method at this moment.The ALPS-index was found to be an indicator of a number of conditions related to the glymphatic system. Thus, although this was expected in the original report, the results of the ALPS method are often interpreted as uniquely corresponding to the function of the glymphatic system. However, a number of subsequent studies have pointed out the problems on the data interpretation. As they rightly point out, a higher ALPS-index indicates predominant Brownian motion of water molecules in the radial direction at the lateral ventricular body level, no more and no less. Fortunately, the term "ALPS-index" has become common and is now known as a common term by many researchers. Therefore, the ALPS-index should simply be expressed as high or low, and whether it reflects a glymphatic system is better to be discussed carefully. In other words, when a decreased ALPS-index is observed, it should be expressed as "decreased ALPS-index" and not directly as "glymphatic dysfunction". Recently, various methods have been proposed to evaluate the glymphatic system. It has become clear that these methods also do not seem to reflect the entirety of the extremely complex glymphatic system. This means that it would be desirable to use various methods in combination to evaluate the glymphatic system in a comprehensive manner.
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Affiliation(s)
- Toshiaki Taoka
- Department of Innovative Biomedical Visualization (iBMV), Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
- Department of Radiology, Nagoya University, Nagoya, Aichi, Japan
| | - Rintaro Ito
- Department of Innovative Biomedical Visualization (iBMV), Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
- Department of Radiology, Nagoya University, Nagoya, Aichi, Japan
| | - Rei Nakamichi
- Department of Radiology, Nagoya University, Nagoya, Aichi, Japan
| | - Toshiki Nakane
- Department of Radiology, Nagoya University, Nagoya, Aichi, Japan
| | - Hisashi Kawai
- Department of Radiology, Aichi Medical University, Nagakute, Aichi, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University, Nagoya, Aichi, Japan
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Hsu JL, Wei YC, Hsiao IT, Lin KJ, Yen TC, Lu CS, Wang HC, Leemans A, Weng YH, Huang KL. Dominance of Tau Burden in Cortical Over Subcortical Regions Mediates Glymphatic Activity and Clinical Severity in PSP. Clin Nucl Med 2024; 49:387-396. [PMID: 38465965 DOI: 10.1097/rlu.0000000000005141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
BACKGROUND Progressive supranuclear palsy (PSP) is a tauopathy that involves subcortical regions but also extends to cortical areas. The clinical impact of different tau protein sites and their influence on glymphatic dysfunction have not been investigated. PATIENTS AND METHODS Participants (n = 55; 65.6 ± 7.1 years; 29 women) with PSP (n = 32) and age-matched normal controls (NCs; n = 23) underwent 18 F-Florzolotau tau PET, MRI, PSP Rating Scale (PSPRS), and Mini-Mental State Examination. Cerebellar gray matter (GM) and parametric estimation of reference signal intensity were used as references for tau burden measured by SUV ratios. Glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS). RESULTS Parametric estimation of reference signal intensity is a better reference than cerebellar GM to distinguish tau burden between PSP and NCs. PSP patients showed higher cortical and subcortical tau SUV ratios than NCs ( P < 0.001 and <0.001). Cortical and subcortical tau deposition correlated with PSPRS, UPDRS, and Mini-Mental State Examination scores (all P 's < 0.05). Cortical tau deposition was further associated with the DTI-ALPS index and frontal-temporal-parietal GM atrophy. The DTI-ALPS indexes showed a significantly negative correlation with the PSPRS total scores ( P < 0.01). Finally, parietal and occipital lobe tau depositions showed mediating effects between the DTI-ALPS index and PSPRS score. CONCLUSIONS Cortical tau deposition is associated with glymphatic dysfunction and plays a role in mediating glymphatic dysfunction and clinical severity. Our results provide a possible explanation for the worsening of clinical severity in patients with PSP.
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Affiliation(s)
| | | | | | | | | | | | | | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
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Tuerxun R, Kamagata K, Saito Y, Andica C, Takabayashi K, Uchida W, Yoshida S, Kikuta J, Tabata H, Naito H, Someya Y, Kaga H, Miyata M, Akashi T, Wada A, Taoka T, Naganawa S, Tamura Y, Watada H, Kawamori R, Aoki S. Assessing interstitial fluid dynamics in type 2 diabetes mellitus and prediabetes cases through diffusion tensor imaging analysis along the perivascular space. Front Aging Neurosci 2024; 16:1362457. [PMID: 38515515 PMCID: PMC10954820 DOI: 10.3389/fnagi.2024.1362457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 02/19/2024] [Indexed: 03/23/2024] Open
Abstract
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.
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Affiliation(s)
- Rukeye Tuerxun
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Faculty of Health Data Science, Juntendo University, Chiba, Japan
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Seina Yoshida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Junko Kikuta
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Hiroki Tabata
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Hitoshi Naito
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuki Someya
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Graduate School of Health and Sports Science, Juntendo University, Chiba, Japan
| | - Hideyoshi Kaga
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Mari Miyata
- Department of Functional Brain Imaging, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akihiko Wada
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Toshiaki Taoka
- Department of Innovative Biomedical Visualization, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yoshifumi Tamura
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Hirotaka Watada
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Ryuzo Kawamori
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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Okar SV, Fagiani F, Absinta M, Reich DS. Imaging of brain barrier inflammation and brain fluid drainage in human neurological diseases. Cell Mol Life Sci 2024; 81:31. [PMID: 38212566 PMCID: PMC10838199 DOI: 10.1007/s00018-023-05073-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 11/22/2023] [Accepted: 11/29/2023] [Indexed: 01/13/2024]
Abstract
The intricate relationship between the central nervous system (CNS) and the immune system plays a crucial role in the pathogenesis of various neurological diseases. Understanding the interactions among the immunopathological processes at the brain borders is essential for advancing our knowledge of disease mechanisms and developing novel diagnostic and therapeutic approaches. In this review, we explore the emerging role of neuroimaging in providing valuable insights into brain barrier inflammation and brain fluid drainage in human neurological diseases. Neuroimaging techniques have enabled us not only to visualize and assess brain structures, but also to study the dynamics of the CNS in health and disease in vivo. By analyzing imaging findings, we can gain a deeper understanding of the immunopathology observed at the brain-immune interface barriers, which serve as critical gatekeepers that regulate immune cell trafficking, cytokine release, and clearance of waste products from the brain. This review explores the integration of neuroimaging data with immunopathological findings, providing valuable insights into brain barrier integrity and immune responses in neurological diseases. Such integration may lead to the development of novel diagnostic markers and targeted therapeutic approaches that can benefit patients with neurological disorders.
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Affiliation(s)
- Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Francesca Fagiani
- Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy
| | - Martina Absinta
- Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy.
- Division of Neuroscience, Vita-Salute San Raffaele University, 20132, Milan, Italy.
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
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Kim M, Song YS, Han K, Bae YJ, Han JW, Kim KW. Impaired Glymphatic Flow on Diffusion Tensor MRI as a Marker of Neurodegeneration in Alzheimer's Disease: Correlation with Gray Matter Volume Loss and Cognitive Decline Independent of Cerebral Amyloid Deposition. J Alzheimers Dis 2024; 99:279-290. [PMID: 38669532 DOI: 10.3233/jad-231131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Background Impaired glymphatic flow on the Alzheimer's disease (AD) spectrum may be evaluated using diffusion tensor image analysis along the perivascular space (DTI-ALPS). Objective We aimed to validate impaired glymphatic flow and explore its association with gray matter volume, cognitive status, and cerebral amyloid deposition on the AD spectrum. Methods 80 participants (mean age, 76.9±8.5 years; 57 women) with AD (n = 65) and cognitively normal (CN) (n = 15) who underwent 3T brain MRI including DTI and/or amyloid PET were included. After adjusting for age, sex, apolipoprotein E status, and burden of white matter hyperintensities, the ALPS-index was compared according to the AD spectrum. The association between the ALPS-index and gray matter volume, cognitive status, and quantitative amyloid from PET was assessed. Results The ALPS-index in the AD was significantly lower (mean, 1.476; 95% CI, 1.395-1.556) than in the CN (1.784;1.615-1.952; p = 0.026). Volumes of the entorhinal cortex, hippocampus, temporal pole, and primary motor cortex showed significant associations with the ALPS-index (all, p < 0.05). There was a positive correlation between the ALPS-index and MMSE score (partial r = 0.435; p < 0.001), but there was no significant correlation between the ALPS-index and amyloid SUVRs (all, p > 0.05). Conclusions Decreased glymphatic flow measured by DTI-ALPS in AD may serve as a marker of neurodegeneration correlating with structural atrophy and cognitive decline.
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Affiliation(s)
- Minjae Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang-gu, Seongnam, Gyeonggi, Republic of Korea
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Yoo Sung Song
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang-gu, Seongnam, Gyeonggi, Republic of Korea
| | - Kyunghwa Han
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seodaemun-gu, Seoul, Republic of Korea
| | - Yun Jung Bae
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang-gu, Seongnam, Gyeonggi, Republic of Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang-gu, Seongnam, Gyeonggi, Republic of Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang-gu, Seongnam, Gyeonggi, Republic of Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea
- Department of Brain & Cognitive Sciences, Seoul National University, Seoul, Republic of Korea
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