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Article ; Online: Exploring the multiphysics of the brain during development, aging, and in neurological diseases.

Weickenmeier, Johannes

Brain multiphysics

2023 Volume 4

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 ... ...

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.
Language	English
Publishing date	2023-04-24
Publishing country	England
Document type	Journal Article
ISSN	2666-5220
ISSN (online)	2666-5220
DOI	10.1016/j.brain.2023.100068
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Article ; Online: Brain Stiffness Follows Cuprizone-Induced Variations in Local Myelin Content.

Zhang, Xuesong / Weickenmeier, Johannes

Acta biomaterialia

2023 Volume 170, Page(s) 507–518

Abstract: Brain maturation and neurological diseases are intricately linked to microstructural changes that inherently affect the brain's mechanical behavior. Animal models are frequently used to explore relative brain stiffness changes as a function of underlying ...

Abstract	Brain maturation and neurological diseases are intricately linked to microstructural changes that inherently affect the brain's mechanical behavior. Animal models are frequently used to explore relative brain stiffness changes as a function of underlying microstructure. Here, we are using the cuprizone mouse model to study indentation-derived stiffness changes resulting from acute and chronic demyelination during a 15-week observation period. We focus on the corpus callosum, cingulum, and cortex which undergo different degrees of de- and remyelination and, therefore, result in region-specific stiffness changes. Mean stiffness of the corpus callosum starts at 1.1 ± 0.3 kPa in untreated mice, then cuprizone treatment causes stiffness to drop to 0.6 ± 0.1 kPa by week 3, temporarily increase to 0.9 ± 0.3 kPa by week 6, and ultimately stabilize around 0.7 ± 0.1 kPa by week 9 for the rest of the observation period. The cingulum starts at 3.2 ± 0.9 kPa, then drops to 1.6 ± 0.4 kPa by week 3, and then gradually stabilizes around 1.4 ± 0.3 kPa by week 9. Cortical stiffness exhibits less stiffness variations overall; it starts at 4.2 ± 1.3 kPa, drops to 2.4 ± 0.6 kPa by week 3, and stabilizes around 2.7 ± 0.9 kPa by week 6. We also assess the impact of tissue fixation on indentation-based mechanical tissue characterization. On the one hand, fixation drastically increases untreated mean tissue stiffness by a factor of 3.3 for the corpus callosum, 2.9 for the cingulum, and 3.6 for the cortex; on the other hand, fixation influences interregional stiffness ratios during demyelination, thus suggesting that fixation affects individual brain tissues differently. Lastly, we determine the spatial correlation between stiffness measurements and myelin density and observe a region-specific proportionality between myelin content and tissue stiffness. STATEMENT OF SIGNIFICANCE: Despite extensive work, the relationship between microstructure and mechanical behavior in the brain remains mostly unknown. Additionally, the existing variation of measurement results reported in literature requires in depth investigation of the impact of individual cell and protein populations on tissue stiffness and interregional stiffness ratios. Here, we used microindentation measurements to show that brain stiffness changes with myelin density in the cuprizone-based demyelination mouse model. Moreover, we explored the impact of tissue fixation prior to mechanical characterization because of conflicting results reported in literature. We observe that fixation has a distinctly different impact on our three regions of interest, thus causing region-specific tissue stiffening and, more importantly, changing interregional stiffness ratios.
Language	English
Publishing date	2023-09-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2173841-5
ISSN	1878-7568 ; 1742-7061
ISSN (online)	1878-7568
ISSN	1742-7061
DOI	10.1016/j.actbio.2023.08.033
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Article ; Online: An inverse modelling study on the local volume changes during early morphoelastic growth of the fetal human brain.

Wang, Z / Martin, B / Weickenmeier, J / Garikipati, K

Brain multiphysics

2021 Volume 2

Abstract: We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum ... ...

Abstract	We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum mechanics model of morphoelastic growth, we invert the deformation obtained from MRI registration to arrive at a field for the growth deformation gradient tensor. Our field inversion uses a combination of direct and adjoint methods for computing gradients of the objective function while constraining the optimization by the physics of morphoelastic growth. We thus infer a growth deformation gradient field that obeys the laws of morphoelastic growth. The errors between the MRI data and the forward displacement solution driven by the inverted growth deformation gradient field are found to be smaller than the reference displacement by well over an order of magnitude, and can be driven even lower. The results thus reproduce the three-dimensional growth during the early development of the fetal brain with controllable error. Our findings confirm that early growth is dominated by in plane cortical expansion rather than thickness increase.
Language	English
Publishing date	2021-03-23
Publishing country	England
Document type	Journal Article
ISSN	2666-5220
ISSN (online)	2666-5220
DOI	10.1016/j.brain.2021.100023
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Article ; Online: Insights into the Mechanical Characterization of Mouse Brain Tissue Using Microindentation Testing.

Zhang, Xuesong / van den Hurk, Eva A N / Weickenmeier, Johannes

Current protocols

2024 Volume 4, Issue 4, Page(s) e1011

Abstract: Indentation testing is the most common approach to quantify mechanical brain tissue properties. Despite a myriad of studies conducted already, reported stiffness values vary extensively and continue to be subject of study. Moreover, the growing interest ... ...

Abstract	Indentation testing is the most common approach to quantify mechanical brain tissue properties. Despite a myriad of studies conducted already, reported stiffness values vary extensively and continue to be subject of study. Moreover, the growing interest in the relationship between the brain's spatially heterogeneous microstructure and local tissue stiffness warrants the development of standardized measurement protocols to enable comparability between studies and assess repeatability of reported data. Here, we present three individual protocols that outline (1) sample preparation of a 1000-µm thick coronal slice, (2) a comprehensive list of experimental parameters associated with the FemtoTools FT-MTA03 Micromechanical Testing System for spherical indentation, and (3) two different approaches to derive the elastic modulus from raw force-displacement data. Lastly, we demonstrate that our protocols deliver a robust experimental framework that enables us to determine the spatially heterogeneous microstructural properties of (mouse) brain tissue. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Mouse brain sample preparation Basic Protocol 2: Indentation testing of mouse brain tissue using the FemtoTools FT-MTA03 Micromechanical Testing and Assembly System Basic Protocol 3: Tissue stiffness identification from force-displacement data.
MeSH term(s)	Animals ; Brain/physiology ; Brain/diagnostic imaging ; Mice ; Elastic Modulus ; Biomechanical Phenomena ; Mechanical Tests
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2691-1299
ISSN (online)	2691-1299
DOI	10.1002/cpz1.1011
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Article ; Online: A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging.

Caçoilo, Andreia / Dortdivanlioglu, Berkin / Rusinek, Henry / Weickenmeier, Johannes

Brain multiphysics

2023 Volume 5

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 ... ...

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 mm
Language	English
Publishing date	2023-05-26
Publishing country	England
Document type	Journal Article
ISSN	2666-5220
ISSN (online)	2666-5220
DOI	10.1016/j.brain.2023.100072
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Article ; Online: Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer's Disease.

Blinkouskaya, Yana / Weickenmeier, Johannes

Frontiers in Mechanical Engineering

2021 Volume 7

Abstract: Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white ... ...

Abstract	Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer's disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer's disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results
Language	English
Publishing date	2021-07-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2835636-6
ISSN	2297-3079 ; 2297-3079
ISSN (online)	2297-3079
ISSN	2297-3079
DOI	10.3389/fmech.2021.705653
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Article ; Online: Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration.

Visser, Valery L / Caçoilo, Andreia / Rusinek, Henry / Weickenmeier, Johannes

Journal of the mechanical behavior of biomedical materials

2023 Volume 143, Page(s) 105921

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 ... ...

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.
MeSH term(s)	Animals ; White Matter/diagnostic imaging ; Magnetic Resonance Imaging ; Neurodegenerative Diseases/pathology ; Brain/diagnostic imaging ; Brain/pathology
Language	English
Publishing date	2023-05-24
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2378381-3
ISSN	1878-0180 ; 1751-6161
ISSN (online)	1878-0180
ISSN	1751-6161
DOI	10.1016/j.jmbbm.2023.105921
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Article: 3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations.

Caçoilo, Andreia / Rusinek, Henry / Weickenmeier, Johannes

Engineering with computers

2022 Volume 38, Issue 5, Page(s) 3939–3955

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 ... ...

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 (
Language	English
Publishing date	2022-07-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	1459031-1
ISSN	1435-5663 ; 0177-0667
ISSN (online)	1435-5663
ISSN	0177-0667
DOI	10.1007/s00366-022-01700-y
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Article ; Online: Peak ependymal cell stretch overlaps with the onset locations of periventricular white matter lesions.

Visser, Valery L / Rusinek, Henry / Weickenmeier, Johannes

Scientific reports

2021 Volume 11, Issue 1, Page(s) 21956

Abstract: Deep and periventricular white matter hyperintensities (dWMH/pvWMH) are bright appearing white matter tissue lesions in T2-weighted fluid attenuated inversion recovery magnetic resonance images and are frequent observations in the aging human brain. ... ...

Abstract	Deep and periventricular white matter hyperintensities (dWMH/pvWMH) are bright appearing white matter tissue lesions in T2-weighted fluid attenuated inversion recovery magnetic resonance images and are frequent observations in the aging human brain. While early stages of these white matter lesions are only weakly associated with cognitive impairment, their progressive growth is a strong indicator for long-term functional decline. DWMHs are typically associated with vascular degeneration in diffuse white matter locations; for pvWMHs, however, no unifying theory exists to explain their consistent onset around the horns of the lateral ventricles. We use patient imaging data to create anatomically accurate finite element models of the lateral ventricles, white and gray matter, and cerebrospinal fluid, as well as to reconstruct their WMH volumes. We simulated the mechanical loading of the ependymal cells forming the primary brain-fluid interface, the ventricular wall, and its surrounding tissues at peak ventricular pressure during the hemodynamic cycle. We observe that both the maximum principal tissue strain and the largest ependymal cell stretch consistently localize in the anterior and posterior horns. Our simulations show that ependymal cells experience a loading state that causes the ventricular wall to be stretched thin. Moreover, we show that maximum wall loading coincides with the pvWMH locations observed in our patient scans. These results warrant further analysis of white matter pathology in the periventricular zone that includes a mechanics-driven deterioration model for the ventricular wall.
MeSH term(s)	Aged ; Ependyma/diagnostic imaging ; Ependyma/pathology ; Female ; Humans ; Lateral Ventricles/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Male ; White Matter/diagnostic imaging ; White Matter/pathology
Language	English
Publishing date	2021-11-09
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-00610-1
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Article ; Online: Elastic-viscoplastic modeling of soft biological tissues using a mixed finite element formulation based on the relative deformation gradient.

Weickenmeier, J / Jabareen, M

International journal for numerical methods in biomedical engineering

2014 Volume 30, Issue 11, Page(s) 1238–1262

Abstract: The characteristic highly nonlinear, time-dependent, and often inelastic material response of soft biological tissues can be expressed in a set of elastic-viscoplastic constitutive equations. The specific elastic-viscoplastic model for soft tissues ... ...

Abstract	The characteristic highly nonlinear, time-dependent, and often inelastic material response of soft biological tissues can be expressed in a set of elastic-viscoplastic constitutive equations. The specific elastic-viscoplastic model for soft tissues proposed by Rubin and Bodner (2002) is generalized with respect to the constitutive equations for the scalar quantity of the rate of inelasticity and the hardening parameter in order to represent a general framework for elastic-viscoplastic models. A strongly objective integration scheme and a new mixed finite element formulation were developed based on the introduction of the relative deformation gradient-the deformation mapping between the last converged and current configurations. The numerical implementation of both the generalized framework and the specific Rubin and Bodner model is presented. As an example of a challenging application of the new model equations, the mechanical response of facial skin tissue is characterized through an experimental campaign based on the suction method. The measurement data are used for the identification of a suitable set of model parameters that well represents the experimentally observed tissue behavior. Two different measurement protocols were defined to address specific tissue properties with respect to the instantaneous tissue response, inelasticity, and tissue recovery.
MeSH term(s)	Algorithms ; Elasticity ; Face/physiology ; Finite Element Analysis ; Models, Biological ; Nonlinear Dynamics ; Skin Physiological Phenomena ; Stress, Mechanical ; Viscosity
Language	English
Publishing date	2014-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2540968-2
ISSN	2040-7947 ; 2040-7939
ISSN (online)	2040-7947
ISSN	2040-7939
DOI	10.1002/cnm.2654
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