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Rivas-Fernández MÁ, Bouhrara M, Canales-Rodríguez EJ, Lindín M, Zurrón M, Díaz F, Galdo-Álvarez S. Brain microstructure alterations in subjective cognitive decline: a multi-component T2 relaxometry study. Brain Commun 2025; 7:fcaf017. [PMID: 39845734 PMCID: PMC11752640 DOI: 10.1093/braincomms/fcaf017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 12/02/2024] [Accepted: 01/13/2025] [Indexed: 01/24/2025] Open
Abstract
Previous research has revealed patterns of brain atrophy in subjective cognitive decline, a potential preclinical stage of Alzheimer's disease. However, the involvement of myelin content and microstructural alterations in subjective cognitive decline has not previously been investigated. This study included three groups of participants recruited from the Compostela Aging Study project: 53 cognitively unimpaired adults, 16 individuals with subjective cognitive decline and hippocampal atrophy and 70 with subjective cognitive decline and no hippocampal atrophy. Group differences were analysed across five MRI biomarkers derived from multi-component T2 relaxometry, each sensitive to variations in cerebral composition and microstructural tissue integrity. Although no significant differences in myelin content were observed between groups, the subjective cognitive decline with hippocampal atrophy group exhibited a larger free-water fraction, and reduced fraction and relaxation times of the intra/extracellular water compartment in frontal, parietal and medial temporal lobe brain regions and white matter tracts as compared with the other groups. Moreover, both subjective cognitive decline groups displayed lower total water content as compared with the control group and the subjective cognitive decline with hippocampal atrophy group showed lower total water content as compared with the subjective cognitive decline without hippocampal atrophy group. These changes are likely related to microstructural tissue differences related to neuroinflammation, axonal degeneration, iron accumulation or other physiologic variations, calling for further examinations.
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Affiliation(s)
- Miguel Ángel Rivas-Fernández
- Division of Endocrinology, Diabetes and Metabolism, Children’s Hospital of Los Angeles, Los Angeles, CA 90027, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Erick J Canales-Rodríguez
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, CH-1011, Switzerland
- Computational Medical Imaging and Machine Learning Section, Center for Biomedical Imaging (CIBM), Lausanne, CH-1015, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Féderale de Lausanne (EPFL), Laussane, CH-1015, Switzerland
| | - Mónica Lindín
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
- Applied Cognitive Neuroscience and Psychogerontology Research Group (Neucoga-Aging), Instituto de Psicoloxía, USC (IPsiUS), Santiago de Compostela, 15782, Spain
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, 15706, Spain
| | - Montserrat Zurrón
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
- Applied Cognitive Neuroscience and Psychogerontology Research Group (Neucoga-Aging), Instituto de Psicoloxía, USC (IPsiUS), Santiago de Compostela, 15782, Spain
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, 15706, Spain
| | - Fernando Díaz
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
- Applied Cognitive Neuroscience and Psychogerontology Research Group (Neucoga-Aging), Instituto de Psicoloxía, USC (IPsiUS), Santiago de Compostela, 15782, Spain
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, 15706, Spain
| | - Santiago Galdo-Álvarez
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
- Applied Cognitive Neuroscience and Psychogerontology Research Group (Neucoga-Aging), Instituto de Psicoloxía, USC (IPsiUS), Santiago de Compostela, 15782, Spain
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, 15706, Spain
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Bergström S, Mravinacová S, Lindberg O, Zettergren A, Westman E, Wahlund LO, Blennow K, Zetterberg H, Kern S, Skoog I, Månberg A. CSF levels of brain-derived proteins correlate with brain ventricular volume in cognitively healthy 70-year-olds. Clin Proteomics 2024; 21:65. [PMID: 39668376 PMCID: PMC11636040 DOI: 10.1186/s12014-024-09517-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Accepted: 12/02/2024] [Indexed: 12/14/2024] Open
Abstract
BACKGROUND The effect of varying brain ventricular volume on the cerebrospinal fluid (CSF) proteome has been discussed as possible confounding factors in comparative protein level analyses. However, the relationship between CSF volume and protein levels remains largely unexplored. Moreover, the few existing studies provide conflicting findings, indicating the need for further research. METHODS Here, we explored the association between levels of 88 pre-selected CSF proteins and ventricular volume derived from magnetic resonance imaging (MRI) measurements in 157 cognitively healthy 70-year-olds from the H70 Gothenburg Birth Cohort Studies, including individuals with and without pathological levels of Alzheimer's disease (AD) CSF markers (n = 123 and 34, respectively). Both left and right lateral, the inferior horn as well as the third and the fourth ventricular volumes were measured. Different antibody-based methods were employed for the protein measurements, with most being analyzed using a multiplex bead-based microarray technology. Furthermore, the associations between the protein levels and cortical thickness, fractional anisotropy, and mean diffusivity were assessed. RESULTS CSF levels of many brain-derived proteins correlated with ventricular volumes in A-T- individuals, with lower levels in individuals with larger ventricles. The strongest negative correlations with total ventricular volume were observed for neurocan (NCAN) and neurosecretory protein VGF (rho = -0.34 for both). Significant negative correlations were observed also for amyloid beta (Ab) 38, Ab40, total tau (t-tau), and phosphorylated tau (p-tau), with correlation ranging between - 0.34 and - 0.28, while no association was observed between ventricular volumes and Ab42 or neurofilament light chain (NfL). Proteins with negative correlations to ventricular volumes further demonstrated negative correlations to mean diffusivity and positive correlation to fractional anisotropy. However, only weak or no correlations were observed between the CSF protein levels and cortical thickness. A + T + individuals demonstrated higher CSF protein levels compared to A-T- individuals with the most significant differences observed for neurogranin (NRGN) and synuclein beta (SNCB). CONCLUSIONS Our findings suggest that the levels of many brain-derived proteins in CSF may be subjected to dilution effects depending on the size of the brain ventricles in healthy individuals without AD pathology. This phenomenon could potentially contribute to the inter-individual variations observed in CSF proteomic studies.
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Affiliation(s)
- Sofia Bergström
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Sára Mravinacová
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Olof Lindberg
- Division of Clinical Geriatrics, Department of Neurobiology, Center for Alzheimer Research, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Mölndal, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Center for Alzheimer Research, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Department of Neurobiology, Center for Alzheimer Research, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Silke Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Mölndal, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Neuropsychiatry, Mölndal, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Mölndal, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Neuropsychiatry, Mölndal, Sweden
| | - Anna Månberg
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden.
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Bontempi P, Marangoni S, Cazzoletti L, Bajrami A, Giometto B, Farace P, Rozzanigo U. Very-long T2-weighted imaging of the non-lesional brain tissue in multiple sclerosis patients. NMR IN BIOMEDICINE 2024; 37:e5235. [PMID: 39086258 DOI: 10.1002/nbm.5235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 07/15/2024] [Accepted: 07/21/2024] [Indexed: 08/02/2024]
Abstract
The purpose of this study is to demonstrate that T2-weighted imaging with very long echo time (TE > 300 ms) can provide relevant information in neurodegenerative/inflammatory disorder. Twenty patients affected by relapsing-remitting multiple sclerosis with stable disease course underwent 1.5 T 3D FLAIR, 3D T1-weighted, and a multi-echo sequence with 32 echoes (TE = 10-320 ms). Focal lesions (FL) were identified on FLAIR. T1-images were processed to segment deep gray matter (dGM), white matter (WM), FL sub-volumes with T1 hypo-intensity (T1FL), and dGM volumes (atrophy). Clinical-radiological parameters included Expanded Disability Status Scale (EDSS), disease duration, patient age, T1FL, and dGM atrophy. Correlation analysis was performed between the mean signal intensity (SI) computed on the non-lesional dGM and WM at different TE versus the clinical-radiological parameters. Multivariable linear regressions were fitted to the data to assess the association between the dependent variable EDSS and the independent variables obtained by T1FL lesion load and the mean SI of dGM and WM at the different TE. A clear trend is observed, with a systematic strengthening of the significance of the correlation at longer TE for all the relationships with the clinical-radiological parameters, becoming significant (p < 0.05) for EDSS, T1FL volumes, and dGM atrophy. Multivariable linear regressions show that at shorter TE, the SI of the T2-weighted sequences is not relevant for describing the EDSS variability while the T1FL volumes are relevant, and vice versa, at very-long TEs (around 300 ms); the SI of the T2-weighted sequences significantly (p < 0.05) describes the EDSS variability. By very long TE, the SI primarily originates from water with a T2 longer than 250 ms and/or free water, which may be arising from the perivascular space (PVS). Very-long T2-weighting might detect dilated PVS and represent an unexplored MR approach in neurofluid imaging of neurodegenerative/inflammatory diseases.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | | | - Lucia Cazzoletti
- Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | | | | | - Paolo Farace
- Medical Physics Department, Hospital of Trento, Trento, Italy
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Filippi M, Preziosa P, Barkhof F, Ciccarelli O, Cossarizza A, De Stefano N, Gasperini C, Geraldes R, Granziera C, Haider L, Lassmann H, Margoni M, Pontillo G, Ropele S, Rovira À, Sastre-Garriga J, Yousry TA, Rocca MA. The ageing central nervous system in multiple sclerosis: the imaging perspective. Brain 2024; 147:3665-3680. [PMID: 39045667 PMCID: PMC11531849 DOI: 10.1093/brain/awae251] [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] [Received: 04/18/2024] [Revised: 06/10/2024] [Accepted: 06/23/2024] [Indexed: 07/25/2024] Open
Abstract
The interaction between ageing and multiple sclerosis is complex and carries significant implications for patient care. Managing multiple sclerosis effectively requires an understanding of how ageing and multiple sclerosis impact brain structure and function. Ageing inherently induces brain changes, including reduced plasticity, diminished grey matter volume, and ischaemic lesion accumulation. When combined with multiple sclerosis pathology, these age-related alterations may worsen clinical disability. Ageing may also influence the response of multiple sclerosis patients to therapies and/or their side effects, highlighting the importance of adjusted treatment considerations. MRI is highly sensitive to age- and multiple sclerosis-related processes. Accordingly, MRI can provide insights into the relationship between ageing and multiple sclerosis, enabling a better understanding of their pathophysiological interplay and informing treatment selection. This review summarizes current knowledge on the immunopathological and MRI aspects of ageing in the CNS in the context of multiple sclerosis. Starting from immunosenescence, ageing-related pathological mechanisms and specific features like enlarged Virchow-Robin spaces, this review then explores clinical aspects, including late-onset multiple sclerosis, the influence of age on diagnostic criteria, and comorbidity effects on imaging features. The role of MRI in understanding neurodegeneration, iron dynamics and myelin changes influenced by ageing and how MRI can contribute to defining treatment effects in ageing multiple sclerosis patients, are also discussed.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1N 3BG, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, UCL Institute of Neurology, UCL, London WC1N 3BG, UK
- NIHR (National Institute for Health and Care Research) UCLH (University College London Hospitals) BRC (Biomedical Research Centre), London WC1N 3BG, UK
| | - Andrea Cossarizza
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 42121 Modena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Claudio Gasperini
- Department of Neurosciences, S Camillo Forlanini Hospital Rome, 00152 Rome, Italy
| | - Ruth Geraldes
- Clinical Neurology, John Radcliffe Hospital, Oxford University Foundation Trust, Oxford OX3 9DU, UK
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Cristina Granziera
- Department of Neurology, University Hospital Basel and University of Basel, 4031 Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, 4031 Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, 4031 Basel, Switzerland
| | - Lukas Haider
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1N 3BG, UK
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, 1090 Vienna, Austria
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Giuseppe Pontillo
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1N 3BG, UK
- Department of Advanced Biomedical Sciences, University “Federico II”, 80138 Naples, Italy
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, 8010 Graz, Austria
| | - Àlex Rovira
- Neuroradiology Section, Department of Radiology, Hospital Universitari Vall d'Hebron, 08035 Barcelona, Spain
| | - Jaume Sastre-Garriga
- Neurology Department and Multiple Sclerosis Centre of Catalunya (Cemcat), Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Tarek A Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, Neuroradiological Academic Unit, UCL Institute of Neurology, London WC1N 3BG, UK
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
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Kohli JS, Linke AC, Martindale IA, Wilkinson M, Kinnear MK, Lincoln AJ, Hau J, Shryock I, Omaleki V, Alemu K, Pedrahita S, Fishman I, Müller R, Carper RA. Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD. Brain Behav 2024; 14:e3594. [PMID: 38849980 PMCID: PMC11161394 DOI: 10.1002/brb3.3594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 05/06/2024] [Accepted: 05/23/2024] [Indexed: 06/09/2024] Open
Abstract
INTRODUCTION In vivo myeloarchitectonic mapping based on Magnetic Resonance Imaging (MRI) provides a unique view of gray matter myelin content and offers information complementary to other morphological indices commonly employed in studies of autism spectrum disorder (ASD). The current study sought to determine if intracortical myelin content (MC) and its age-related trajectories differ between middle aged to older adults with ASD and age-matched typical comparison participants. METHODS Data from 30 individuals with ASD and 36 age-matched typical comparison participants aged 40-70 years were analyzed. Given substantial heterogeneity in both etiology and outcomes in ASD, we utilized both group-level and subject-level analysis approaches to test for signs of atypical intracortical MC as estimated by T1w/T2w ratio. RESULTS Group-level analyses showed no significant differences in average T1w/T2w ratio or its associations with age between groups, but revealed significant positive main effects of age bilaterally, with T1w/T2w ratio increasing with age across much of the cortex. In subject-level analyses, participants were classified into subgroups based on presence or absence of clusters of aberrant T1w/T2w ratio, and lower neuropsychological function was observed in the ASD subgroup with atypically high T1w/T2w ratio in spatially heterogeneous cortical regions. These differences were observed across several neuropsychological domains, including overall intellectual functioning, processing speed, and aspects of executive function. CONCLUSIONS The group-level and subject-level approaches employed here demonstrate the value of examining inter-individual variability and provide important preliminary insights into relationships between brain structure and cognition in the second half of the lifespan in ASD, suggesting shared factors contributing to atypical intracortical myelin content and poorer cognitive outcomes for a subset of middle aged to older autistic adults. These atypicalities likely reflect diverse histories of neurodevelopmental deficits, and possible compensatory changes, compounded by processes of aging, and may serve as useful markers of vulnerability to further cognitive decline in older adults with ASD.
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Affiliation(s)
- Jiwandeep S. Kohli
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Annika C. Linke
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian A. Martindale
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Molly Wilkinson
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Mikaela K. Kinnear
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Alan J. Lincoln
- California School of Professional PsychologyAlliant International UniversitySan DiegoCaliforniaUSA
| | - Janice Hau
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian Shryock
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Vinton Omaleki
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Kalekirstos Alemu
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Stephanie Pedrahita
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ralph‐Axel Müller
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ruth A. Carper
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
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Voss HU, Razlighi QR. Pulsatility analysis of the circle of Willis. AGING BRAIN 2024; 5:100111. [PMID: 38495808 PMCID: PMC10940807 DOI: 10.1016/j.nbas.2024.100111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/13/2024] [Accepted: 02/26/2024] [Indexed: 03/19/2024] Open
Abstract
Purpose To evaluate the phenomenological significance of cerebral blood pulsatility imaging in aging research. Methods N = 38 subjects from 20 to 72 years of age (24 females) were imaged with ultrafast MRI with a sampling rate of 100 ms and simultaneous acquisition of pulse oximetry data. Of these, 28 subjects had acceptable MRI and pulse data, with 16 subjects between 20 and 28 years of age, and 12 subjects between 61 and 72 years of age. Pulse amplitude in the circle of Willis was assessed with the recently developed method of analytic phase projection to extract blood volume waveforms. Results Arteries in the circle of Willis showed pulsatility in the MRI for both the young and old age groups. Pulse amplitude in the circle of Willis significantly increased with age (p = 0.01) but was independent of gender, heart rate, and head motion during MRI. Discussion and conclusion Increased pulse wave amplitude in the circle of Willis in the elderly suggests a phenomenological significance of cerebral blood pulsatility imaging in aging research. The physiologic origin of increased pulse amplitude (increased pulse pressure vs. change in arterial morphology vs. re-shaping of pulse waveforms caused by the heart, and possible interaction with cerebrospinal fluid pulsatility) requires further investigation.
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Affiliation(s)
- Henning U. Voss
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Cornell MRI Facility, College of Human Ecology, Cornell University, Ithaca, NY, USA
| | - Qolamreza R. Razlighi
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
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Zhou L, Nguyen TD, Chiang GC, Wang XH, Xi K, Hu T, Tanzi EB, Butler TA, de Leon MJ, Li Y. Parenchymal CSF fraction is a measure of brain glymphatic clearance and positively associated with amyloid beta deposition on PET. Alzheimers Dement 2024; 20:2047-2057. [PMID: 38184796 PMCID: PMC10984424 DOI: 10.1002/alz.13659] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/08/2024]
Abstract
INTRODUCTION Mapping of microscopic changes in the perivascular space (PVS) of the cerebral cortex, beyond magnetic resonance-visible PVS in white matter, may enhance our ability to diagnose Alzheimer's disease (AD) early. METHODS We used the cerebrospinal fluid (CSF) water fraction (CSFF), a magnetic resonance imaging-based biomarker, to characterize brain parenchymal CSF water, reflecting microscopic PVS in parenchyma. We measured CSFF and amyloid beta (Aβ) using 11 C Pittsburgh compound B positron emission tomography to investigate their relationship at both the subject and voxel levels. RESULTS Our research has demonstrated a positive correlation between the parenchymal CSFF, a non-invasive imaging biomarker indicative of parenchymal glymphatic clearance, and Aβ deposition, observed at both individual and voxel-based assessments in the posterior cingulate cortex. DISCUSSION This study shows that an increased parenchymal CSFF is associated with Aβ deposition, suggesting that CSFF could serve as a biomarker for brain glymphatic clearance, which can be used to detect early fluid changes in PVS predisposing individuals to the development of AD. HIGHLIGHTS Cerebrospinal fluid fraction (CSFF) could be a biomarker of parenchymal perivascular space. CSFF is positively associated with amyloid beta (Aβ) deposition at subject level. CSFF in an Aβ+ region is higher than in an Aβ- region in the posterior cingulate cortex. Correspondence is found between Aβ deposition and glymphatic clearance deficits measured by CSFF.
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Affiliation(s)
- Liangdong Zhou
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Thanh D. Nguyen
- Department of RadiologyMRI Research Institute (MRIRI)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Gloria C. Chiang
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
- Department of RadiologyDivision of NeuroradiologyWeill Cornell MedicineNew York‐Presbyterian HospitalNew YorkNew YorkUSA
| | - Xiuyuan H. Wang
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Ke Xi
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Tsung‐Wei Hu
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Emily B. Tanzi
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Tracy A. Butler
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Mony J. de Leon
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
| | - Yi Li
- Department of RadiologyBrain Health Imaging Institute (BHII)Weill Cornell MedicineNew YorkNew YorkUSA
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Bontempi P, Rozzanigo U, Marangoni S, Fogazzi E, Ravanelli D, Cazzoletti L, Giometto B, Farace P. Non-lesional white matter in relapsing-remitting multiple sclerosis assessed by multicomponent T2 relaxation. Brain Behav 2023; 13:e3334. [PMID: 38041516 PMCID: PMC10726908 DOI: 10.1002/brb3.3334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 12/03/2023] Open
Abstract
INTRODUCTION The purpose of the study is to investigate, by T2 relaxation, non-lesional white matter (WM) in relapsing-remitting (RR) multiple sclerosis (MS). METHODS Twenty stable RR MS patients underwent 1.5T Magnetic Resonance Imaging (MRI) with 3D Fluid-Attenuated Inversion-Recovery (FLAIR), 3D-T1-weighted, and T2-relaxation multi-echo sequences. The Lesion Segmentation Tool processed FLAIR images to identify focal lesions (FLs), whereas T1 images were segmented to identify WM and FL sub-volumes with T1 hypo-intensity. Non-lesional WM was obtained as the segmented WM, excluding FL volumes. The multi-echo sequence allowed decomposition into myelin water, intra-extracellular water, and free water (Fw), which were evaluated on the segmented non-lesional WM. Correlation analysis was performed between the non-lesional WM relaxation parameters and Expanded Disability Status Scale (EDSS), disease duration, patient age, and T1 hypo-intense FL volumes. RESULTS The T1 hypo-intense FL volumes correlated with EDSS. On the non-lesional WM, the median Fw correlated with EDSS, disease duration, age, and T1 hypo-intense FL volumes. Bivariate EDSS correlation of FL volumes and WM T2-relaxation parameters did not improve significance. CONCLUSION T2 relaxation allowed identifying subtle WM alterations, which significantly correlated with EDSS, disease duration, and age but do not seem to be EDSS-predictors independent from FL sub-volumes in stable RR patients. Particularly, the increase in the Fw component is suggestive of an uninvestigated prodromal phenomenon in brain degeneration.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation MedicineUniversity of VeronaVeronaItaly
| | - Umberto Rozzanigo
- Neuro‐radiology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Sabrina Marangoni
- Neurology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Elena Fogazzi
- Physics departmentUniversity of TrentoPovoTrentoItaly
| | - Daniele Ravanelli
- Medical Physics Department, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Lucia Cazzoletti
- Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public HealthUniversity of VeronaVeronaItaly
| | - Bruno Giometto
- Neurology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Paolo Farace
- Medical Physics Department, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
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