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Caçoilo A, Dortdivanlioglu B, Rusinek H, Weickenmeier J. A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging. BRAIN MULTIPHYSICS 2023; 5:100072. [PMID: 37546181 PMCID: PMC10399513 DOI: 10.1016/j.brain.2023.100072] [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] [Indexed: 08/08/2023] Open
Abstract
Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm2/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
| | - Berkin Dortdivanlioglu
- Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
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Bennett J, van Dinther M, Voorter P, Backes W, Barnes J, Barkhof F, Captur G, Hughes AD, Sudre C, Treibel TA. Assessment of Microvascular Disease in Heart and Brain by MRI: Application in Heart Failure with Preserved Ejection Fraction and Cerebral Small Vessel Disease. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1596. [PMID: 37763715 PMCID: PMC10534635 DOI: 10.3390/medicina59091596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023]
Abstract
The objective of this review is to investigate the commonalities of microvascular (small vessel) disease in heart failure with preserved ejection fraction (HFpEF) and cerebral small vessel disease (CSVD). Furthermore, the review aims to evaluate the current magnetic resonance imaging (MRI) diagnostic techniques for both conditions. By comparing the two conditions, this review seeks to identify potential opportunities to improve the understanding of both HFpEF and CSVD.
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Affiliation(s)
- Jonathan Bennett
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Department of Cardiology, Barts Heart Centre, London EC1A 7BE, UK
| | - Maud van Dinther
- Department of Neurology, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6211 LX Maastricht, The Netherlands
| | - Paulien Voorter
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Walter Backes
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6211 LX Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Josephine Barnes
- Dementia Research Centre, UCL Queens Square Institute of Neurology, University College London, London WC1E 6BT, UK
| | - Frederick Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije University, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
- Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK
- Centre for Medical Image Computing, University College London, London WC1E 6BT, UK
| | - Gabriella Captur
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
- Centre for Inherited Heart Muscle Conditions, Cardiology Department, The Royal Free Hospital, London NW3 2QG, UK
| | - Alun D. Hughes
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
| | - Carole Sudre
- Dementia Research Centre, UCL Queens Square Institute of Neurology, University College London, London WC1E 6BT, UK
- Centre for Medical Image Computing, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | - Thomas A. Treibel
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Department of Cardiology, Barts Heart Centre, London EC1A 7BE, UK
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Visser VL, Caçoilo A, Rusinek H, Weickenmeier J. Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration. J Mech Behav Biomed Mater 2023; 143:105921. [PMID: 37269602 PMCID: PMC10266836 DOI: 10.1016/j.jmbbm.2023.105921] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 06/05/2023]
Abstract
Progressive white matter degeneration in periventricular and deep white matter regions appears as white matter hyperintensities (WMH) on MRI scans. To date, periventricular WMHs are often associated with vascular dysfunction. Here, we demonstrate that ventricular inflation resulting from cerebral atrophy and hemodynamic pulsation with every heartbeat leads to a mechanical loading state of periventricular tissues that significantly affects the ventricular wall. Specifically, we present a physics-based modeling approach that provides a rationale for ependymal cell involvement in periventricular WMH formation. Building on eight previously created 2D finite element brain models, we introduce novel mechanomarkers for ependymal cell loading and geometric measures that characterize lateral ventricular shape. We show that our novel mechanomarkers, such as maximum ependymal cell deformations and maximum curvature of the ventricular wall, spatially overlap with periventricular WMH locations and are sensitive predictors for WMH formation. We also explore the role of the septum pellucidum in mitigating mechanical loading of the ventricular wall by constraining the radial expansion of the lateral ventricles during loading. Our models consistently show that ependymal cells are stretched thin only in the horns of the ventricles irrespective of ventricular shape. We therefore pose that periventricular WMH etiology is strongly linked to the deterioration of the over-stretched ventricular wall resulting in CSF leakage into periventricular white matter. Subsequent secondary damage mechanisms, including vascular degeneration, exacerbate lesion formation and lead to progressive growth into deep white matter regions.
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Affiliation(s)
- Valery L Visser
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America; Department of Biomedical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
| | - Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.
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Weickenmeier J. Exploring the multiphysics of the brain during development, aging, and in neurological diseases. BRAIN MULTIPHYSICS 2023; 4:100068. [PMID: 37476409 PMCID: PMC10358452 DOI: 10.1016/j.brain.2023.100068] [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] [Indexed: 07/22/2023] Open
Abstract
The human brain remains an endless source of wonder and represents an intruiging scientific frontier. Multiphysics approaches naturally lend themselves to combine our extensive knowledge about the neurobiology of aging and diseases with mechanics to better capture the multiscale behavior of the brain. Our group uses experimental methods, medical image analysis, and constitutive modeling to develop better disease models with the long-term goal to improve diagnosis, treatment, and ultimately enable prevention of many prevalent age- and disease-related brain changes. In the present perspective, we outline on-going work related to neurodevelopment, aging, and neurodegenerative disease.
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Affiliation(s)
- Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
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Caçoilo A, Rusinek H, Weickenmeier J. 3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations. ENGINEERING WITH COMPUTERS 2022; 38:3939-3955. [PMID: 37485473 PMCID: PMC10361695 DOI: 10.1007/s00366-022-01700-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/19/2022] [Indexed: 07/25/2023]
Abstract
Aging-related periventricular white matter hyperintensities (pvWMHs) are a common observation in medical images of the aging brain. The underlying tissue damage is part of the complex pathophysiology associated with age-related microstructural changes and cognitive decline. PvWMH formation is linked to blood-brain barrier dysfunction from cerebral small vessel disease as well as the accumulation of cerebrospinal fluid in periventricular tissue due to progressive denudation of the ventricular wall. In need of a unifying theory for pvWMH etiology, image-based finite-element modeling is used to demonstrate that ventricular expansion from age-related cerebral atrophy and hemodynamic loading leads to maximum mechanical loading of the ventricular wall in the same locations that show pvWMHs. Ventricular inflation, induced via pressurization of the ventricular wall, creates significant ventricular wall stretch and stress on the ependymal cells lining the wall, that are linked to cerebrospinal fluid leaking from the lateral ventricles into periventricular white matter tissue. Eight anatomically accurate 3D brain models of cognitively healthy subjects with a wide range of ventricular shapes are created. For all models, our simulations show that mechanomarkers of mechanical wall loading are consistently highest in pvWMHs locations (p < 0.05). Maximum principal strain, the ependymal cell thinning ratio, and wall curvature are on average 14%, 8%, and 24% higher in pvWMH regions compared to the remaining ventricular wall, respectively. Computational modeling provides a powerful framework to systematically study pvWMH formation and growth with the goal to develop pharmacological interventions in the future.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
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Yun W, Kim YJ, Lee G. Direct Conversion to Achieve Glial Cell Fates: Oligodendrocytes and Schwann Cells. Int J Stem Cells 2022; 15:14-25. [PMID: 35220289 PMCID: PMC8889328 DOI: 10.15283/ijsc22008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/03/2022] [Indexed: 11/13/2022] Open
Abstract
Glia have been known for its pivotal roles in physiological and pathological conditions in the nervous system. To study glial biology, multiple approaches have been applied to utilize glial cells for research, including stem cell-based technologies. Human glial cells differentiated from pluripotent stem cells are now available, allowing us to study the structural and functional roles of glia in the nervous system, although the efficiency is still low. Direct conversion is an advanced strategy governing fate conversion of diverse cell types directly into the desired lineage. This novel strategy stands as a promising approach for preliminary research and regenerative medicine. Direct conversion employs genetic and environmental cues to change cell fate to that with the required functional cell properties while retaining maturity-related molecular features. As an alternative method, it is now possible to obtain a variety of mature cell populations that could not be obtained using conventional differentiation methods. This review summarizes current achievements in obtaining glia, particularly oligodendrocytes and Schwann cells.
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Affiliation(s)
- Wonjin Yun
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yong Jun Kim
- Department of Pathology, College of Medicine, Kyung Hee University, Seoul, Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Korea
| | - Gabsang Lee
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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