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Caban-Rivera DA, Williams LT, McGarry MDJ, Smith DR, Van Houten EEW, Paulsen KD, Bayly PV, Johnson CL. Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.593260. [PMID: 38766139 PMCID: PMC11100698 DOI: 10.1101/2024.05.08.593260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Magnetic resonance elastography (MRE) is a promising neuroimaging technique to probe tissue microstructure, which has revealed widespread softening with loss of structural integrity in the aging brain. Traditional MRE approaches assume mechanical isotropy. However, white matter is known to be anisotropic from aligned, myelinated axonal bundles, which can lead to uncertainty in mechanical property estimates in these areas when using isotropic MRE. Recent advances in anisotropic MRE now allow for estimation of shear and tensile anisotropy, along with substrate shear modulus, in white matter tracts. The objective of this study was to investigate age-related differences in anisotropic mechanical properties in human brain white matter tracts for the first time. Anisotropic mechanical properties in all tracts were found to be significantly lower in older adults compared to young adults, with average property differences ranging between 0.028-0.107 for shear anisotropy and between 0.139-0.347 for tensile anisotropy. Stiffness perpendicular to the axonal fiber direction was also significantly lower in older age, but only in certain tracts. When compared with fractional anisotropy measures from diffusion tensor imaging, we found that anisotropic MRE measures provided additional, complementary information in describing differences between the white matter integrity of young and older populations. Anisotropic MRE provides a new tool for studying white matter structural integrity in aging and neurodegeneration.
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2
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Dehghani H, Holzapfel GA, Mittelbronn M, Zilian A. Cell adhesion affects the properties of interstitial fluid flow: A study using multiscale poroelastic composite modeling. J Mech Behav Biomed Mater 2024; 153:106486. [PMID: 38428205 DOI: 10.1016/j.jmbbm.2024.106486] [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: 07/06/2023] [Revised: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 03/03/2024]
Abstract
In this study, we conduct a multiscale, multiphysics modeling of the brain gray matter as a poroelastic composite. We develop a customized representative volume element based on cytoarchitectural features that encompass important microscopic components of the tissue, namely the extracellular space, the capillaries, the pericapillary space, the interstitial fluid, cell-cell and cell-capillary junctions, and neuronal and glial cell bodies. Using asymptotic homogenization and direct numerical simulation, the effective properties at the tissue level are identified based on microscopic properties. To analyze the influence of various microscopic elements on the effective/macroscopic properties and tissue response, we perform sensitivity analyses on cell junction (cluster) stiffness, cell junction diameter (dimensions), and pericapillary space width. The results of this study suggest that changes in cell adhesion can greatly affect both mechanical and hydraulic (interstitial fluid flow and porosity) features of brain tissue, consistent with the effects of neurodegenerative diseases.
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Affiliation(s)
- Hamidreza Dehghani
- Institute of Computational Engineering and Sciences, Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
| | - Gerhard A Holzapfel
- Institute of Biomechanics, Graz University of Technology, 8010 Graz, Austria; Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Michel Mittelbronn
- National Center of Pathology (NCP), Laboratoire National de Santé (LNS), Dudelange, Luxembourg; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Belval, Luxembourg; Luxembourg Center of Neuropathology (LCNP), Dudelange, Luxembourg; Department of Oncology (DONC), Luxembourg Institute of Health (LIH), Luxembourg; Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Esch-sur-Alzette, Luxembourg; Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Andreas Zilian
- Institute of Computational Engineering and Sciences, Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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Wang S, Okamoto RJ, McGarry MDJ, Bayly PV. Shear wave speeds in a nearly incompressible fibrous material with two unequal fiber families. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2024; 155:2327-2338. [PMID: 38557738 PMCID: PMC10987194 DOI: 10.1121/10.0025467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/21/2024] [Accepted: 03/14/2024] [Indexed: 04/04/2024]
Abstract
The mechanical properties of soft biological tissues can be characterized non-invasively by magnetic resonance elastography (MRE). In MRE, shear wave fields are induced by vibration, imaged by magnetic resonance imaging, and inverted to estimate tissue properties in terms of the parameters of an underlying material model. Most MRE studies assume an isotropic material model; however, biological tissue is often anisotropic with a fibrous structure, and some tissues contain two or more families of fibers-each with different orientations and properties. Motivated by the prospect of using MRE to characterize such tissues, this paper describes the propagation of shear waves in soft fibrous material with two unequal fiber families. Shear wave speeds are expressed in terms of material parameters, and the effect of each parameter on the shear wave speeds is investigated. Analytical expressions of wave speeds are confirmed by finite element simulations of shear wave transmission with various polarization directions. This study supports the feasibility of estimating parameters of soft fibrous tissues with two unequal fiber families in vivo from local shear wave speeds and advances the prospects for the mechanical characterization of such biological tissues by MRE.
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Affiliation(s)
- Shuaihu Wang
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
| | - Ruth J Okamoto
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
| | - Matthew D J McGarry
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA
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4
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Wang S, Guertler CA, Okamoto RJ, Johnson CL, McGarry MDJ, Bayly PV. Mechanical stiffness and anisotropy measured by MRE during brain development in the minipig. Neuroimage 2023; 277:120234. [PMID: 37369255 PMCID: PMC11081136 DOI: 10.1016/j.neuroimage.2023.120234] [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: 02/15/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023] Open
Abstract
The relationship between brain development and mechanical properties of brain tissue is important, but remains incompletely understood, in part due to the challenges in measuring these properties longitudinally over time. In addition, white matter, which is composed of aligned, myelinated, axonal fibers, may be mechanically anisotropic. Here we use data from magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI) to estimate anisotropic mechanical properties in six female Yucatan minipigs at ages from 3 to 6 months. Fiber direction was estimated from the principal axis of the diffusion tensor in each voxel. Harmonic shear waves in the brain were excited by three different configurations of a jaw actuator and measured using a motion-sensitive MR imaging sequence. Anisotropic mechanical properties are estimated from displacement field and fiber direction data with a finite element- based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. TI-NLI finds spatially resolved TI material properties that minimize the error between measured and simulated displacement fields. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal at all four ages. These maps show that white matter is more dissipative and anisotropic than gray matter, and reveal significant effects of brain development on brain stiffness and structural anisotropy. Changes in brain mechanical properties may be a fundamental biophysical signature of brain development.
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Affiliation(s)
- Shuaihu Wang
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | - Charlotte A Guertler
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | - Ruth J Okamoto
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | | | | | - Philip V Bayly
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States; Biomedical Engineering, Washington University in St. Louis, United States.
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Kailash KA, Guertler CA, Johnson CL, Okamoto RJ, Bayly PV. Measurement of relative motion of the brain and skull in the mini-pig in-vivo. J Biomech 2023; 156:111676. [PMID: 37329640 PMCID: PMC11086683 DOI: 10.1016/j.jbiomech.2023.111676] [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: 07/19/2022] [Revised: 06/05/2023] [Accepted: 06/07/2023] [Indexed: 06/19/2023]
Abstract
The mechanical role of the skull-brain interface is critical to the pathology of concussion and traumatic brain injury (TBI) and may evolve with age. Here we characterize the skull-brain interface in juvenile, female Yucatan mini-pigs from 3 to 6 months old using techniques from magnetic resonance elastography (MRE). The displacements of the skull and brain were measured by a motion-sensitive MR imaging sequence during low-amplitude harmonic motion of the head. Each animal was scanned four times at 1-month intervals. Harmonic motion at 100 Hz was excited by three different configurations of a jaw actuator in order to vary the direction of loading. Rigid-body linear motions of the brain and skull were similar, although brain rotations were consistently smaller than corresponding skull rotations. Relative displacements between the brain and skull were estimated for voxels on the surface of the brain. Amplitudes of relative displacements between skull and brain were 1-3 μm, approximately 25-50% of corresponding skull displacements. Maps of relative displacement showed variations by anatomical region, and the normal component of relative displacement was consistently 25-50% of the tangential component. These results illuminate the mechanics of the skull-brain interface in a gyrencephalic animal model relevant to human brain injury and development.
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Affiliation(s)
- Keshav A Kailash
- Washington University in St. Louis, Biomedical Engineering, United States
| | - Charlotte A Guertler
- Washington University in St. Louis, Mechanical Engineering and Material Science, United States
| | | | - Ruth J Okamoto
- Washington University in St. Louis, Mechanical Engineering and Material Science, United States
| | - Philip V Bayly
- Washington University in St. Louis, Biomedical Engineering, United States; Washington University in St. Louis, Mechanical Engineering and Material Science, United States.
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Shakiba D, Genin GM, Zustiak SP. Mechanobiology of cancer cell responsiveness to chemotherapy and immunotherapy: Mechanistic insights and biomaterial platforms. Adv Drug Deliv Rev 2023; 196:114771. [PMID: 36889646 PMCID: PMC10133187 DOI: 10.1016/j.addr.2023.114771] [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: 08/30/2022] [Revised: 12/17/2022] [Accepted: 03/03/2023] [Indexed: 03/08/2023]
Abstract
Mechanical forces are central to how cancer treatments such as chemotherapeutics and immunotherapies interact with cells and tissues. At the simplest level, electrostatic forces underlie the binding events that are critical to therapeutic function. However, a growing body of literature points to mechanical factors that also affect whether a drug or an immune cell can reach a target, and to interactions between a cell and its environment affecting therapeutic efficacy. These factors affect cell processes ranging from cytoskeletal and extracellular matrix remodeling to transduction of signals by the nucleus to metastasis of cells. This review presents and critiques the state of the art of our understanding of how mechanobiology impacts drug and immunotherapy resistance and responsiveness, and of the in vitro systems that have been of value in the discovery of these effects.
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Affiliation(s)
- Delaram Shakiba
- NSF Science and Technology Center for Engineering Mechanobiology, Washington University, St. Louis, MO, USA; Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO, USA
| | - Guy M Genin
- NSF Science and Technology Center for Engineering Mechanobiology, Washington University, St. Louis, MO, USA; Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO, USA.
| | - Silviya P Zustiak
- NSF Science and Technology Center for Engineering Mechanobiology, Washington University, St. Louis, MO, USA; Department of Biomedical Engineering, School of Science and Engineering, Saint Louis University, St. Louis, MO, USA.
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Kainz MP, Greiner A, Hinrichsen J, Kolb D, Comellas E, Steinmann P, Budday S, Terzano M, Holzapfel GA. Poro-viscoelastic material parameter identification of brain tissue-mimicking hydrogels. Front Bioeng Biotechnol 2023; 11:1143304. [PMID: 37101751 PMCID: PMC10123293 DOI: 10.3389/fbioe.2023.1143304] [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: 01/12/2023] [Accepted: 03/27/2023] [Indexed: 04/28/2023] Open
Abstract
Understanding and characterizing the mechanical and structural properties of brain tissue is essential for developing and calibrating reliable material models. Based on the Theory of Porous Media, a novel nonlinear poro-viscoelastic computational model was recently proposed to describe the mechanical response of the tissue under different loading conditions. The model contains parameters related to the time-dependent behavior arising from both the viscoelastic relaxation of the solid matrix and its interaction with the fluid phase. This study focuses on the characterization of these parameters through indentation experiments on a tailor-made polyvinyl alcohol-based hydrogel mimicking brain tissue. The material behavior is adjusted to ex vivo porcine brain tissue. An inverse parameter identification scheme using a trust region reflective algorithm is introduced and applied to match experimental data obtained from the indentation with the proposed computational model. By minimizing the error between experimental values and finite element simulation results, the optimal constitutive model parameters of the brain tissue-mimicking hydrogel are extracted. Finally, the model is validated using the derived material parameters in a finite element simulation.
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Affiliation(s)
- Manuel P. Kainz
- Institute of Biomechanics, Graz University of Technology, Graz, Austria
| | - Alexander Greiner
- Department Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Jan Hinrichsen
- Department Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Dagmar Kolb
- Center for Medical Research, Gottfried Schatz Research Center, Core Facility Ultrastructure Analysis, Medical University of Graz, Graz, Austria
- Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Ester Comellas
- Department of Physics, Serra Húnter Fellow, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - Paul Steinmann
- Department Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany
- Glasgow Computational Engineering Centre, University of Glasgow, Glasgow, United Kingdom
| | - Silvia Budday
- Department Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Michele Terzano
- Institute of Biomechanics, Graz University of Technology, Graz, Austria
| | - Gerhard A. Holzapfel
- Institute of Biomechanics, Graz University of Technology, Graz, Austria
- Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- *Correspondence: Gerhard A. Holzapfel,
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Yousefsani SA, Karimi MZV. Bidirectional hyperelastic characterization of brain white matter tissue. Biomech Model Mechanobiol 2022; 22:495-513. [PMID: 36550243 DOI: 10.1007/s10237-022-01659-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/19/2022] [Indexed: 12/24/2022]
Abstract
Biomechanical study of brain injuries originated from mechanical damages to white matter tissue requires detailed information on mechanical characteristics of its main components, the axonal fibers and extracellular matrix, which is very limited due to practical difficulties of direct measurement. In this paper, a new theoretical framework was established based on microstructural modeling of brain white matter tissue as a soft composite for bidirectional hyperelastic characterization of its main components. First the tissue was modeled as an Ogden hyperelastic material, and its principal Cauchy stresses were formulated in the axonal and transverse directions under uniaxial and equibiaxial tension using the theory of homogenization. Upon fitting these formulae to the corresponding experimental test data, direction-dependent hyperelastic constants of the tissue were obtained. These directional properties then were used to estimate the strain energy stored in the homogenized model under each loading scenario. A new microstructural composite model of the tissue was also established using principles of composites micromechanics, in which the axonal fibers and surrounding matrix are modeled as different Ogden hyperelastic materials with unknown constants. Upon balancing the strain energies stored in the homogenized and composite models under different loading scenarios, fully coupled nonlinear equations as functions of unknown hyperelastic constants were derived, and their optimum solutions were found in a multi-parametric multi-objective optimization procedure using the response surface methodology. Finally, these solutions were implemented, in a bottom-up approach, into a micromechanical finite element model to reproduce the tissue responses under the same loadings and predict the tissue responses under unseen non-equibiaxial loadings. Results demonstrated a very good agreement between the model predictions and experimental results in both directions under different loadings. Moreover, the axonal fibers with hyperelastic characteristics stiffer than the extracellular matrix were shown to play the dominant role in directional reinforcement of the tissue.
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Affiliation(s)
- Seyed Abdolmajid Yousefsani
- Department of Mechanical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box: 9177948974, Mashhad, Iran.
| | - Mohammad Zohoor Vahid Karimi
- Department of Mechanical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box: 9177948974, Mashhad, Iran
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Li Y, Gao Q, Chen N, Zhang Y, Wang J, Li C, He X, Jiao Y, Zhang Z. Clinical studies of magnetic resonance elastography from 1995 to 2021: Scientometric and visualization analysis based on CiteSpace. Quant Imaging Med Surg 2022; 12:5080-5100. [PMID: 36330182 PMCID: PMC9622435 DOI: 10.21037/qims-22-207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 08/11/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND To assess the knowledge framework around magnetic resonance elastography (MRE) and to explore MRE research hotspots and emerging trends. METHODS The Science Citation Index Expanded of the Web of Science Core Collection was searched on 22 October 2021 for MRE-related studies published between 1995 and 2021. Excel 2016 and CiteSpace V (version 5.8.R3) were used to analyze the downloaded data. RESULTS In all, 1,236 articles published by 726 authors from 540 institutions in 40 countries were included in this study. The top 10 authors published 57.6% of all included articles. The 3 most productive countries were the USA (n=631), Germany (n=202), and France (n=134), and the 3 most productive institutions were the Mayo Clinic (n=240), Charité (n=131), and the University of Illinois (n=56). The USA and the Mayo Clinic had the highest betweenness centrality among countries and institutions, respectively, and played an important role in the field of MRE. In this study, the 24,347 distinct references were clustered into 48 categories via reasonable clustering using specific keywords, forming the knowledge framework. Among the 294 co-occurring keywords, "hepatic fibrosis", "stiffness", "skeletal muscle", "acoustic strain wave", "in vivo", and "non-invasive assessment" were research hotspots. "Diagnostic performance", "diagnostic accuracy", "hepatic steatosis", "chronic hepatitis B", "radiation force impulse", "children", and "echo" were frontier topics. CONCLUSIONS Scientometric and visualized analysis of MRE can provide information regarding the knowledge framework, research hotspots, frontier areas, and emerging trends in this field.
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Affiliation(s)
- Youwei Li
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Qiang Gao
- Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Na Chen
- Department of Otorhinolaryngology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Yuanfang Zhang
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Juan Wang
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Chang Li
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Xuan He
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Yang Jiao
- Department of Rehabilitation Psychology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Zongming Zhang
- Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing, China
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Upadhyay K, Alshareef A, Knutsen AK, Johnson CL, Carass A, Bayly PV, Pham DL, Prince JL, Ramesh KT. Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework. J R Soc Interface 2022; 19:20220561. [PMCID: PMC9554734 DOI: 10.1098/rsif.2022.0561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Computational head models are promising tools for understanding and predicting traumatic brain injuries. Most available head models are developed using inputs (i.e. head geometry, material properties and boundary conditions) from experiments on cadavers or animals and employ hereditary integral-based constitutive models that assume linear viscoelasticity in part of the rate-sensitive material response. This leads to high uncertainty and poor accuracy in capturing the nonlinear brain tissue response. To resolve these issues, a framework for the development of subject-specific three-dimensional head models is proposed, in which all inputs are derived in vivo from the same living human subject: head geometry via magnetic resonance imaging (MRI), brain tissue properties via magnetic resonance elastography (MRE), and full-field strain-response of the brain under rapid head rotation via tagged MRI. A nonlinear, viscous dissipation-based visco-hyperelastic constitutive model is employed to capture brain tissue response. Head models are validated using quantitative metrics that compare spatial strain distribution, temporal strain evolution, and the magnitude of strain maxima, with the corresponding experimental observations from tagged MRI. Results show that our head models accurately capture the strain-response of the brain. Further, employment of the nonlinear visco-hyperelastic constitutive framework provides improvements in the prediction of peak strains and temporal strain evolution over hereditary integral-based models.
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Affiliation(s)
- Kshitiz Upadhyay
- Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD 21218, USA,Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ahmed Alshareef
- Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD 21218, USA,Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Andrew K. Knutsen
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20814, USA
| | - Curtis L. Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE 19716, USA
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Philip V. Bayly
- Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Dzung L. Pham
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20814, USA
| | - Jerry L. Prince
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - K. T. Ramesh
- Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD 21218, USA,Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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Reiter R, Zampini MA, Guidetti M, Majumdar S, Royston TJ, Klatt D. Tabletop MR elastography for investigating effects of the freeze-thaw cycle on the mechanical properties of biological tissues. J Mech Behav Biomed Mater 2022; 135:105458. [PMID: 36116341 DOI: 10.1016/j.jmbbm.2022.105458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/23/2022] [Accepted: 09/08/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE We aimed at characterizing the effects of the freeze-thaw cycle (FTC) on ex vivo specimens of porcine muscle, liver, kidney, and brain using tabletop magnetic resonance elastography (MRE) combined with rheological modeling. While frozen tissue banks potentially facilitate access to large amounts of well-preserved biospecimens, the impact of the FTC on their viscoelastic properties remains elusive. METHODS In this proof-of-concept study, fresh specimens from porcine lumbar muscle (n = 6), liver (n = 6), kidney (n = 6), and brain (n = 6) were examined before and after the FTC using 0.5T tabletop MRE at 500 Hz, 1000 Hz, 1500 Hz, and 2000 Hz. Seven standard rheological models (Maxwell, Springpot, Voigt, Zener, Jeffrey, fractional Voigt, fractional Zener) were employed to calculate frequency independent viscoelastic parameters. RESULTS The Zener rheological model showed the best fit quality for tissues before and after FTC in the investigated frequency range. Global rheological behavior after the FTC was softer for all tissues. Differences in mechanical parameters between tissues were preserved after the FTC and showed similar trends as before the FTC. Moreover, rheological fit quality improved after the FTC - a result that will be beneficial in investigating frozen tissue bank samples. CONCLUSION Multifrequency tabletop MRE allows rheological characterization of tissue samples before and after the FTC. Our results encourage further biomechanical characterization of frozen tissue bank samples, which may provide valuable information on the diagnostic potential of elastographic methods.
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Affiliation(s)
- Rolf Reiter
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States; Department of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, 10117, Berlin, Germany.
| | - Marco A Zampini
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States; MR Solutions Ltd, Ashbourne House, Old Portsmouth Road, Guildford, Surrey, GU3 1LR, United Kingdom.
| | - Martina Guidetti
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States; Department of Orthopedic Surgery, Rush University, 1611 West Harrison Street, Chicago, IL, 60612, United States.
| | - Shreyan Majumdar
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States.
| | - Thomas J Royston
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States.
| | - Dieter Klatt
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, 830 South Wood Street, Chicago, IL, 60612, United States.
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12
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In vivo, in situ and ex vivo comparison of porcine skin for microprojection array penetration depth, delivery efficiency and elastic modulus assessment. J Mech Behav Biomed Mater 2022; 130:105187. [DOI: 10.1016/j.jmbbm.2022.105187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/13/2022] [Accepted: 03/17/2022] [Indexed: 11/18/2022]
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13
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Tavakoli J, Geargeflia S, Tipper JL, Diwan AD. Magnetic resonance elastography: A non-invasive biomarker for low back pain studies. BIOMEDICAL ENGINEERING ADVANCES 2021. [DOI: 10.1016/j.bea.2021.100014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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14
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Jordan JEL, Bertalan G, Meyer T, Tzschätzsch H, Gauert A, Bramè L, Herthum H, Safraou Y, Schröder L, Braun J, Hagemann AIH, Sack I. Microscopic multifrequency MR elastography for mapping viscoelasticity in zebrafish. Magn Reson Med 2021; 87:1435-1445. [PMID: 34752638 DOI: 10.1002/mrm.29066] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE The zebrafish (Danio rerio) has become an important animal model in a wide range of biomedical research disciplines. Growing awareness of the role of biomechanical properties in tumor progression and neuronal development has led to an increasing interest in the noninvasive mapping of the viscoelastic properties of zebrafish by elastography methods applicable to bulky and nontranslucent tissues. METHODS Microscopic multifrequency MR elastography is introduced for mapping shear wave speed (SWS) and loss angle (φ) as markers of stiffness and viscosity of muscle, brain, and neuroblastoma tumors in postmortem zebrafish with 60 µm in-plane resolution. Experiments were performed in a 7 Tesla MR scanner at 1, 1.2, and 1.4 kHz driving frequencies. RESULTS Detailed zebrafish viscoelasticity maps revealed that the midbrain region (SWS = 3.1 ± 0.7 m/s, φ = 1.2 ± 0.3 radian [rad]) was stiffer and less viscous than telencephalon (SWS = 2.6 ± 0. 5 m/s, φ = 1.4 ± 0.2 rad) and optic tectum (SWS = 2.6 ± 0.5 m/s, φ = 1.3 ± 0.4 rad), whereas the cerebellum (SWS = 2.9 ± 0.6 m/s, φ = 0.9 ± 0.4 rad) was stiffer but less viscous than both (all p < .05). Overall, brain tissue (SWS = 2.9 ± 0.4 m/s, φ = 1.2 ± 0.2 rad) had similar stiffness but lower viscosity values than muscle tissue (SWS = 2.9 ± 0.5 m/s, φ = 1.4 ± 0.2 rad), whereas neuroblastoma (SWS = 2.4 ± 0.3 m/s, φ = 0.7 ± 0.1 rad, all p < .05) was the softest and least viscous tissue. CONCLUSION Microscopic multifrequency MR elastography-generated maps of zebrafish show many details of viscoelasticity and resolve tissue regions, of great interest in neuromechanical and oncological research and for which our study provides first reference values.
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Affiliation(s)
| | - Gergely Bertalan
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Tom Meyer
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Heiko Tzschätzsch
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Anton Gauert
- Department of Hematology/Oncology, Charité-Universitätsmedizin Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Luca Bramè
- Department of Hematology/Oncology, Charité-Universitätsmedizin Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Helge Herthum
- Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Yasmine Safraou
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Leif Schröder
- Molecular Imaging, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany
| | - Jürgen Braun
- Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Anja I H Hagemann
- Department of Hematology/Oncology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ingolf Sack
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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15
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Escarcega JD, Knutsen AK, Okamoto RJ, Pham DL, Bayly PV. Natural oscillatory modes of 3D deformation of the human brain in vivo. J Biomech 2021; 119:110259. [PMID: 33618329 PMCID: PMC8055167 DOI: 10.1016/j.jbiomech.2021.110259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 01/04/2021] [Accepted: 01/10/2021] [Indexed: 12/12/2022]
Abstract
Natural modes and frequencies of three-dimensional (3D) deformation of the human brain were identified from in vivo tagged magnetic resonance images (MRI) acquired dynamically during transient mild acceleration of the head. Twenty 3D strain fields, estimated from tagged MRI image volumes in 19 adult subjects, were analyzed using dynamic mode decomposition (DMD). These strain fields represented dynamic, 3D brain deformations during constrained head accelerations, either involving rotation about the vertical axis of the neck or neck extension. DMD results reveal fundamental oscillatory modes of deformation at damped frequencies near 7 Hz (in neck rotation) and 11 Hz (in neck extension). Modes at these frequencies were found consistently among all subjects. These characteristic features of 3D human brain deformation are important for understanding the response of the brain in head impacts and provide valuable quantitative criteria for the evaluation and use of computer models of brain mechanics.
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Affiliation(s)
- J D Escarcega
- Mechanical Engineering and Materials Science, Washington University in St. Louis, MO, United States.
| | - A K Knutsen
- Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
| | - R J Okamoto
- Mechanical Engineering and Materials Science, Washington University in St. Louis, MO, United States
| | - D L Pham
- Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
| | - P V Bayly
- Mechanical Engineering and Materials Science, Washington University in St. Louis, MO, United States
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16
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Norris C, Lisinski J, McNeil E, VanMeter JW, VandeVord P, LaConte SM. MRI brain templates of the male Yucatan minipig. Neuroimage 2021; 235:118015. [PMID: 33798725 DOI: 10.1016/j.neuroimage.2021.118015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 03/14/2021] [Accepted: 03/17/2021] [Indexed: 10/21/2022] Open
Abstract
The pig is growing in popularity as an experimental animal because its gyrencephalic brain is similar to humans. Currently, however, there is a lack of appropriate brain templates to support functional and structural neuroimaging pipelines. The primary contribution of this work is an average volume from an iterative, non-linear registration of 70 five- to seven-month-old male Yucatan minipigs. In addition, several aspects of this study are unique, including the comparison of linear and non-linear template generation, the characterization of a large and homogeneous cohort, an analysis of effective resolution after averaging, and the evaluation of potential in-template bias as well as a comparison with a template from another minipig species using a "left-out" validation set. We found that within our highly homogeneous cohort, non-linear registration produced better templates, but only marginally so. Although our T1-weighted data were resolution limited, we preserved effective resolution across the multi-subject average, produced templates that have high gray-white matter contrast and demonstrate superior registration accuracy compared to an alternative minipig template.
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Affiliation(s)
- Carly Norris
- Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, United States
| | - Jonathan Lisinski
- Fralin Biomedical Research Institute, Virginia Tech, Roanoke, VA, United States
| | - Elizabeth McNeil
- Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, United States
| | - John W VanMeter
- Neurology, Georgetown University, Washington, DC, United States
| | - Pamela VandeVord
- Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, United States; Salem VA Medical Center, Salem VA, United States
| | - Stephen M LaConte
- Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, United States; Fralin Biomedical Research Institute, Virginia Tech, Roanoke, VA, United States.
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17
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Hou Z, Bayly PV, Okamoto RJ. Shear wave speeds in nearly-incompressible fibrous materials with two fiber families. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2021; 149:1097. [PMID: 33639778 PMCID: PMC7878018 DOI: 10.1121/10.0003528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 01/13/2021] [Accepted: 01/25/2021] [Indexed: 06/12/2023]
Abstract
An analytical and numerical investigation of shear wave behavior in nearly-incompressible soft materials with two fiber families was performed, focusing on the effects of material parameters and imposed pre-deformations on wave speed. This theoretical study is motivated by the emerging ability to image shear waves in soft biological tissues by magnetic resonance elastography (MRE). In MRE, the relationships between wave behavior and mechanical properties can be used to characterize tissue properties non-invasively. We demonstrate these principles in two material models, each with two fiber families. One model is a nearly-incompressible linear elastic model that exhibits both shear and tensile anisotropy; the other is a two-fiber-family version of the widely-used Holzapfel-Gasser-Ogden (HGO) model, which is nonlinear. Shear waves can be used to probe nonlinear material behavior using infinitesimal dynamic deformations superimposed on larger, quasi-static "pre-deformations." In this study, closed-form expressions for shear wave speeds in the HGO model are obtained in terms of the model parameters and imposed pre-deformations. Analytical expressions for wave speeds are confirmed by finite element simulations of shear waves with various polarizations and propagation directions. These studies support the feasibility of estimating the parameters of an HGO material model noninvasively from measured shear wave speeds.
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Affiliation(s)
- Zuoxian Hou
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
| | - Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
| | - Ruth J Okamoto
- Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri 63130, USA
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18
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Sullivan DJ, Wu X, Gallo NR, Naughton NM, Georgiadis JG, Pelegri AA. Sensitivity analysis of effective transverse shear viscoelastic and diffusional properties of myelinated white matter. Phys Med Biol 2021; 66:035027. [PMID: 32599577 DOI: 10.1088/1361-6560/aba0cc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Motivated by the need to interpret the results from a combined use of in vivo brain Magnetic Resonance Elastography (MRE) and Diffusion Tensor Imaging (DTI), we developed a computational framework to study the sensitivity of single-frequency MRE and DTI metrics to white matter microstructure and cell-level mechanical and diffusional properties. White matter was modeled as a triphasic unidirectional composite, consisting of parallel cylindrical inclusions (axons) surrounded by sheaths (myelin), and embedded in a matrix (glial cells plus extracellular matrix). Only 2D mechanics and diffusion in the transverse plane (perpendicular to the axon direction) was considered, and homogenized (effective) properties were derived for a periodic domain containing a single axon. The numerical solutions of the MRE problem were performed with ABAQUS and by employing a sophisticated boundary-conforming grid generation scheme. Based on the linear viscoelastic response to harmonic shear excitation and steady-state diffusion in the transverse plane, a systematic sensitivity analysis of MRE metrics (effective transverse shear storage and loss moduli) and DTI metric (effective radial diffusivity) was performed for a wide range of microstructural and intrinsic (phase-based) physical properties. The microstructural properties considered were fiber volume fraction, and the myelin sheath/axon diameter ratio. The MRE and DTI metrics are very sensitive to the fiber volume fraction, and the intrinsic viscoelastic moduli of the glial phase. The MRE metrics are nonlinear functions of the fiber volume fraction, but the effective diffusion coefficient varies linearly with it. Finally, the transverse metrics of both MRE and DTI are insensitive to the axon diameter in steady state. Our results are consistent with the limited anisotropic MRE and co-registered DTI measurements, mainly in the corpus callosum, available in the literature. We conclude that isotropic MRE and DTI constitutive models are good approximations for myelinated white matter in the transverse plane. The unidirectional composite model presented here is used for the first time to model harmonic shear stress under MRE-relevant frequency on the cell level. This model can be extended to 3D in order to inform the solution of the inverse problem in MRE, establish the biological basis of MRE metrics, and integrate MRE/DTI with other modalities towards increasing the specificity of neuroimaging.
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Affiliation(s)
- Daniel J Sullivan
- Department of Mechanical and Aerospace Engineering, Rutgers, the State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854-8058, United States of America
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19
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Hiscox LV, McGarry MDJ, Schwarb H, Van Houten EEW, Pohlig RT, Roberts N, Huesmann GR, Burzynska AZ, Sutton BP, Hillman CH, Kramer AF, Cohen NJ, Barbey AK, Paulsen KD, Johnson CL. Standard-space atlas of the viscoelastic properties of the human brain. Hum Brain Mapp 2020; 41:5282-5300. [PMID: 32931076 PMCID: PMC7670638 DOI: 10.1002/hbm.25192] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/28/2020] [Accepted: 08/16/2020] [Indexed: 12/16/2022] Open
Abstract
Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast‐based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18–35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM‐152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross‐center comparisons.
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Affiliation(s)
- Lucy V Hiscox
- Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
| | - Matthew D J McGarry
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Hillary Schwarb
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Interdisciplinary Health Sciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Elijah E W Van Houten
- Département de génie mécanique, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Ryan T Pohlig
- College of Health Sciences, University of Delaware, Newark, Delaware, USA
| | - Neil Roberts
- School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Graham R Huesmann
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Carle Neuroscience Institute, Carle Foundation Hospital, Urbana, Illinois, USA
| | - Agnieszka Z Burzynska
- Department of Human Development and Family Studies and Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, Colorado, USA
| | - Bradley P Sutton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Charles H Hillman
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA.,Department of Physical Therapy, Movement, & Rehabilitation Sciences, Northeastern University, Boston, Massachusetts, USA
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, Northeastern University, Boston, Massachusetts, USA
| | - Neal J Cohen
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Interdisciplinary Health Sciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Aron K Barbey
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Keith D Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
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20
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Eskandari F, Shafieian M, Aghdam MM, Laksari K. Tension Strain-Softening and Compression Strain-Stiffening Behavior of Brain White Matter. Ann Biomed Eng 2020; 49:276-286. [PMID: 32494967 DOI: 10.1007/s10439-020-02541-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Accepted: 05/26/2020] [Indexed: 11/29/2022]
Abstract
Brain, the most important component of the central nervous system (CNS), is a soft tissue with a complex structure. Understanding the role of brain tissue microstructure in mechanical properties is essential to have a more profound knowledge of how brain development, disease, and injury occur. While many studies have investigated the mechanical behavior of brain tissue under various loading conditions, there has not been a clear explanation for variation reported for material properties of brain tissue. The current study compares the ex-vivo mechanical properties of brain tissue under two loading modes, namely compression and tension, and aims to explain the differences observed by closely examining the microstructure under loading. We tested bovine brain samples under uniaxial tension and compression loading conditions, and fitted hyperelastic material parameters. At 20% strain, we observed that the shear modulus of brain tissue in compression is about 6 times higher than in tension. In addition, we observed that brain tissue exhibited strain-stiffening in compression and strain-softening in tension. In order to investigate the effect of loading modes on the tissue microstructure, we fixed the samples using a novel method that enabled keeping the samples at the loaded stage during the fixation process. Based on the results of histology, we hypothesize that during compressive loading, the strain-stiffening behavior of the tissue could be attributed to glial cell bodies being pushed against surroundings, contacting each other and resisting compression, while during tension, cell connections are detached and the tissue displays softening behavior.
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Affiliation(s)
- Faezeh Eskandari
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Mehdi Shafieian
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
| | - Mohammad M Aghdam
- Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Kaveh Laksari
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA
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21
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Hall CM, Moeendarbary E, Sheridan GK. Mechanobiology of the brain in ageing and Alzheimer's disease. Eur J Neurosci 2020; 53:3851-3878. [DOI: 10.1111/ejn.14766] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 04/20/2020] [Accepted: 04/23/2020] [Indexed: 02/07/2023]
Affiliation(s)
- Chloe M. Hall
- Department of Mechanical Engineering University College London London UK
- School of Pharmacy and Biomolecular Sciences University of Brighton Brighton UK
| | - Emad Moeendarbary
- Department of Mechanical Engineering University College London London UK
- Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA USA
| | - Graham K. Sheridan
- School of Life Sciences Queens Medical Centre University of Nottingham Nottingham UK
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22
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Eskandari F, Shafieian M, Aghdam MM, Laksari K. A knowledge map analysis of brain biomechanics: Current evidence and future directions. Clin Biomech (Bristol, Avon) 2020; 75:105000. [PMID: 32361083 DOI: 10.1016/j.clinbiomech.2020.105000] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 01/27/2020] [Accepted: 03/18/2020] [Indexed: 02/07/2023]
Abstract
Although brain, one of the most complex organs in the mammalian body, has been subjected to many studies from physiological and pathological points of view, there remain significant gaps in the available knowledge regarding its biomechanics. This article reviews the research trends in brain biomechanics with a focus on injury. We used published scientific articles indexed by Web of Science database over the past 40 years and tried to address the gaps that still exist in this field. We analyzed the data using VOSviewer, which is a software tool designed for scientometric studies. The results of this study showed that the response of brain tissue to external forces has been one of the significant research topics among biomechanicians. These studies have addressed the effects of mechanical forces on the brain and mechanisms of traumatic brain injury, as well as characterized changes in tissue behavior under trauma and other neurological diseases to provide new diagnostic and monitoring methods. In this study, some challenges in the field of brain injury biomechanics have been identified and new directions toward understanding the gaps in this field are suggested.
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Affiliation(s)
- Faezeh Eskandari
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Mehdi Shafieian
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
| | - Mohammad M Aghdam
- Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Kaveh Laksari
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA
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23
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Towards microstructure-informed material models for human brain tissue. Acta Biomater 2020; 104:53-65. [PMID: 31887455 DOI: 10.1016/j.actbio.2019.12.030] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 12/19/2019] [Accepted: 12/20/2019] [Indexed: 02/06/2023]
Abstract
Emerging evidence suggests that the mechanical behavior of the brain plays a critical role in development, disease, and aging. Recent studies have begun to characterize the mechanical behavior of gray and white matter tissue and to identify sets of material models that best reproduce the stress-strain behavior of different brain regions. Yet, these models are mainly phenomenological in nature, their parameters often lack clear physical interpretation, and they fail to correlate the mechanical behavior to the underlying microstructural composition. Here we make a first attempt towards identifying general relations between microstructure and mechanics with the ultimate goal to develop microstructurally motivated constitutive equations for human brain tissue. Using histological staining, we analyze the microstructure of brain specimens from different anatomical regions, the cortex, basal ganglia, corona radiata, and corpus callosum, and identify the regional stiffness and viscosity under multiple loading conditions, simple shear, compression, and tension. Strikingly, our study reveals a negative correlation between cell count and stiffness, a positive correlation between myelin content and stiffness, and a negative correlation between proteoglycan content and stiffness. Additionally, our analysis shows a positive correlation between lipid and proteoglycan content and viscosity. We demonstrate how understanding the microstructural origin of the macroscopic behavior of the brain can help us design microstructure-informed material models for human brain tissue that inherently capture regional heterogeneities. This study represents an important step towards using brain tissue stiffness and viscosity as early diagnostic markers for clinical conditions including chronic traumatic encephalopathy, Alzheimer's and Parkinson's disease, or multiple sclerosis. STATEMENT OF SIGNIFICANCE: The complex and heterogeneous mechanical properties of brain tissue play a critical role for brain function. To understand and predict how brain tissue properties vary in space and time, it will be key to link the mechanical behavior to the underlying microstructural composition. Here we use histological staining to quantify area fractions of microstructural components of mechanically tested specimens and evaluate their individual contributions to the nonlinear macroscopic mechanical response. We further propose a microstructure-informed material model for human brain tissue that inherently captures regional heterogeneities. The current work provides unprecedented insights into the biomechanics of human brain tissue, which are highly relevant to develop refined computational models for brain tissue behavior or to advance neural tissue engineering.
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24
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Frequency dependent viscoelastic properties of porcine brain tissue. J Mech Behav Biomed Mater 2020; 102:103460. [DOI: 10.1016/j.jmbbm.2019.103460] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 09/24/2019] [Accepted: 09/28/2019] [Indexed: 02/06/2023]
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25
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Modo M, Badylak SF. A roadmap for promoting endogenous in situ tissue restoration using inductive bioscaffolds after acute brain injury. Brain Res Bull 2019; 150:136-149. [PMID: 31128250 DOI: 10.1016/j.brainresbull.2019.05.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Revised: 05/10/2019] [Accepted: 05/17/2019] [Indexed: 02/08/2023]
Abstract
The regeneration of brain tissue remains one of the greatest unsolved challenges in medicine and by many is considered unfeasible. Indeed, the adult mammalian brain does not regenerate tissue, but there is ongoing endogenous neurogenesis, which is upregulated after injury and contributes to tissue repair. This endogenous repair response is a conditio sine que non for tissue regeneration. However, scarring around the lesion core and cavitation provide unfavorable conditions for tissue regeneration in the brain. Based on the success of using extracellular matrix (ECM)-based bioscaffolds in peripheral soft tissue regeneration, it is plausible that the provision of an inductive ECM-based hydrogel inside the volumetric tissue loss can attract neural cells and create a de novo viable tissue. Following perturbation theory of these successes in peripheral tissues, we here propose 9 perturbation parts (i.e. requirements) that can be solved independently to create an integrated series to build a functional and integrated de novo neural tissue. Necessities for tissue formation, anatomical and functional connectivity are further discussed to provide a new substrate to support the improvement of behavioral impairments after acute brain injury. We also consider potential parallel developments of this tissue engineering effort that can support therapeutic benefits in the absence of de novo tissue formation (e.g. structural support to veterate brain tissue). It is envisaged that eventually top-down inductive "natural" bioscaffolds composed of decellularized tissues (i.e. ECM) will be replaced by bottom-up synthetic designer hydrogels that will provide very defined structural and signaling properties, potentially even opening up opportunities we currently do not envisage using natural materials.
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Affiliation(s)
- Michel Modo
- University of Pittsburgh, McGowan Institute for Regenerative Medicine, Pittsburgh, Pennsylvania, USA; University of Pittsburgh, Department of Bioengineering, Pittsburgh, PA, USA; University of Pittsburgh, Department of Radiology, Pittsburgh, PA, USA.
| | - Stephen F Badylak
- University of Pittsburgh, McGowan Institute for Regenerative Medicine, Pittsburgh, Pennsylvania, USA; University of Pittsburgh, Department of Bioengineering, Pittsburgh, PA, USA; University of Pittsburgh, Department of Surgery, Pittsburgh, PA, USA
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26
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Embedded Finite Elements for Modeling Axonal Injury. Ann Biomed Eng 2018; 47:1889-1907. [PMID: 30519759 DOI: 10.1007/s10439-018-02166-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Accepted: 11/14/2018] [Indexed: 10/27/2022]
Abstract
The purpose of this paper is to propose and develop a large strain embedded finite element formulation that can be used to explicitly model axonal fiber bundle tractography from diffusion tensor imaging of the brain. Once incorporated, the fibers offer the capability to monitor tract-level strains that give insight into the biomechanics of brain injury. We show that one commercial software has a volume and mass redundancy issue when including embedded axonal fiber and that a newly developed algorithm is able to correct this discrepancy. We provide a validation analysis for stress and energy to demonstrate the method.
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27
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Dilation of tricuspid valve annulus immediately after rupture of chordae tendineae in ex-vivo porcine hearts. PLoS One 2018; 13:e0206744. [PMID: 30408050 PMCID: PMC6226105 DOI: 10.1371/journal.pone.0206744] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 10/18/2018] [Indexed: 12/18/2022] Open
Abstract
Purpose Chordae rupture is one of the main lesions observed in traumatic heart events that might lead to severe tricuspid valve (TV) regurgitation. TV regurgitation following chordae rupture is often well tolerated with few or no symptoms for most patients. However, early repair of the TV is of great importance, as it might prevent further exacerbation of the regurgitation due to remodeling responses. To understand how TV regurgitation develops following this acute event, we investigated the changes on TV geometry, mechanics, and function of ex-vivo porcine hearts following chordae rupture. Methods Sonomicrometry techniques were employed in an ex-vivo heart apparatus to identify how the annulus geometry alters throughout the cardiac cycle after chordae rupture, leading to the development of TV regurgitation. Results We observed that the TV annulus significantly dilated (~9% in area) immediately after chordae rupture. The annulus area and circumference ranged from 11.4 ± 2.8 to 13.3 ± 2.9 cm2 and from 12.5 ± 1.5 to 13.5 ± 1.3 cm, respectively, during the cardiac cycle for the intact heart. After chordae rupture, the annulus area and circumference were larger and ranged from 12.3 ± 3.0 to 14.4 ± 2.9 cm2 and from 13.0 ± 1.5 to 14.0 ± 1.2 cm, respectively. Conclusions In our ex-vivo study, we showed for the first time that the TV annulus dilates immediately after chordae rupture. Consequently, secondary TV regurgitation may be developed because of such changes in the annulus geometry. In addition, the TV leaflet and the right ventricle myocardium are subjected to a different mechanical environment, potentially causing further negative remodeling responses and exacerbating the detrimental outcomes of chordae rupture.
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Liu YL, Liu D, Xu L, Su C, Li GY, Qian LX, Cao Y. In vivo and ex vivo elastic properties of brain tissues measured with ultrasound elastography. J Mech Behav Biomed Mater 2018; 83:120-125. [DOI: 10.1016/j.jmbbm.2018.04.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 04/11/2018] [Accepted: 04/17/2018] [Indexed: 12/18/2022]
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Compressive mechanical characterization of non-human primate spinal cord white matter. Acta Biomater 2018; 74:260-269. [PMID: 29729417 DOI: 10.1016/j.actbio.2018.05.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 04/27/2018] [Accepted: 05/01/2018] [Indexed: 11/22/2022]
Abstract
The goal of developing computational models of spinal cord injury (SCI) is to better understand the human injury condition. However, finite element models of human SCI have used rodent spinal cord tissue properties due to a lack of experimental data. Central nervous system tissues in non human primates (NHP) closely resemble that of humans and therefore, it is expected that material constitutive models obtained from NHPs will increase the fidelity and the accuracy of human SCI models. Human SCI most often results from compressive loading and spinal cord white matter properties affect FE predicted patterns of injury; therefore, the objectives of this study were to characterize the unconfined compressive response of NHP spinal cord white matter and present an experimentally derived, finite element tractable constitutive model for the tissue. Cervical spinal cords were harvested from nine male adult NHPs (Macaca mulatta). White matter biopsy samples (3 mm in diameter) were taken from both lateral columns of the spinal cord and were divided into four strain rate groups for unconfined dynamic compression and stress relaxation (post-mortem <1-hour). The NHP spinal cord white matter compressive response was sensitive to strain rate and showed substantial stress relaxation confirming the viscoelastic behavior of the material. An Ogden 1st order model best captured the non-linear behavior of NHP white matter in a quasi-linear viscoelastic material model with 4-term Prony series. This study is the first to characterize NHP spinal cord white matter at high (>10/sec) strain rates typical of traumatic injury. The finite element derived material constitutive model of this study will increase the fidelity of SCI computational models and provide important insights for transferring pre-clinical findings to clinical treatments. STATEMENT OF SIGNIFICANCE Spinal cord injury (SCI) finite element (FE) models provide an important tool to bridge the gap between animal studies and human injury, assess injury prevention technologies (e.g. helmets, seatbelts), and provide insight into the mechanisms of injury. Although, FE model outcomes depend on the assumed material constitutive model, there is limited experimental data for fresh spinal cords and all was obtained from rodent, porcine or bovine tissues. Central nervous system tissues in non human primates (NHP) more closely resemble humans. This study characterizes fresh NHP spinal cord material properties at high strains rates and large deformations typical of SCI for the first time. A constitutive model was defined that can be readily implemented in finite strain FE analysis of SCI.
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Bayly PV, Garbow JR. Pre-clinical MR elastography: Principles, techniques, and applications. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 291:73-83. [PMID: 29705042 PMCID: PMC5943171 DOI: 10.1016/j.jmr.2018.01.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 01/07/2018] [Indexed: 05/09/2023]
Abstract
Magnetic resonance elastography (MRE) is a method for measuring the mechanical properties of soft tissue in vivo, non-invasively, by imaging propagating shear waves in the tissue. The speed and attenuation of waves depends on the elastic and dissipative properties of the underlying material. Tissue mechanical properties are essential for biomechanical models and simulations, and may serve as markers of disease, injury, development, or recovery. MRE is already established as a clinical technique for detecting and characterizing liver disease. The potential of MRE for diagnosing or characterizing disease in other organs, including brain, breast, and heart is an active research area. Studies involving MRE in the pre-clinical setting, in phantoms and artificial biomaterials, in the mouse, and in other mammals, are critical to the development of MRE as a robust, reliable, and useful modality.
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Affiliation(s)
- P V Bayly
- Mechanical Engineering and Materials Science, Washington University in Saint Louis, MO, USA.
| | - J R Garbow
- Radiology, Washington University School of Medicine, Saint Louis, MO, USA
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