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Sollmann N, Fuderer M, Crameri F, Weingärtner S, Baeßler B, Gulani V, Keenan KE, Mandija S, Golay X, deSouza NM. Color Maps: Facilitating the Clinical Impact of Quantitative MRI. J Magn Reson Imaging 2025; 61:1572-1579. [PMID: 39180202 PMCID: PMC11896930 DOI: 10.1002/jmri.29573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/05/2024] [Accepted: 08/05/2024] [Indexed: 08/26/2024] Open
Abstract
Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Miha Fuderer
- Radiotherapy, Division Imaging and OncologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | | | - Bettina Baeßler
- Department of Diagnostic and Interventional RadiologyUniversity Hospital WuerzburgWuerzburgGermany
| | - Vikas Gulani
- Department of RadiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Kathryn E. Keenan
- Physical Measurement LaboratoryNational Institute of Standards and TechnologyBoulderColoradoUSA
| | - Stefano Mandija
- Radiotherapy, Division Imaging and OncologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Xavier Golay
- Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Gold Standard PhantomsSheffieldUK
- BioxydynManchesterUK
| | - Nandita M. deSouza
- The Institute of Cancer ResearchLondonUK
- The Royal Marsden NHS Foundation TrustLondonUK
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Twohy KE, Kramer MK, Diano AM, Bailey OM, Delgorio PL, McIlvain G, McGarry MDJ, Martens CR, Schwarb H, Hiscox LV, Johnson CL. Mechanical Properties of the Cortex in Older Adults and Relationships With Personality Traits. Hum Brain Mapp 2025; 46:e70147. [PMID: 39916406 PMCID: PMC11803078 DOI: 10.1002/hbm.70147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 01/13/2025] [Accepted: 01/19/2025] [Indexed: 02/11/2025] Open
Abstract
Aging and neurodegeneration impact structural brain integrity and can result in changes to behavior and cognition. Personality, a relatively stable trait in adults as compared to behavior, in part relies on normative individual differences in cellular organization of the cerebral cortex, but links between brain structure and personality expression have been mixed. One key finding is that personality has been shown to be a risk factor in the development of Alzheimer's disease, highlighting a structure-trait relationship. Magnetic resonance elastography (MRE) has been used to noninvasively study age-related changes in tissue mechanical properties because of its high sensitivity to both the microstructural health and the structure-function relationship of the tissue. Recent advancements in MRE methodology have allowed for reliable property recovery of cortical subregions, which had previously presented challenges due to the complex geometry and overall thin structure. This study aimed to quantify age-related changes in cortical mechanical properties and the relationship of these properties to measures of personality in an older adult population (N = 57; age 60-85 years) for the first time. Mechanical properties including shear stiffness and damping ratio were calculated for 30 bilateral regions of the cortex across all four lobes, and the NEO Personality Inventory (NEO-PI) was used to measure neuroticism and conscientiousness in all participants. Shear stiffness and damping ratio were found to vary widely across regions of the cortex, upward of 1 kPa in stiffness and by 0.3 in damping ratio. Shear stiffness changed regionally with age, with some regions experiencing accelerated degradation compared to neighboring regions. Greater neuroticism (i.e., the tendency to experience negative emotions and vulnerability to stress) was associated with high damping ratio, indicative of poorer tissue integrity, in the rostral middle frontal cortex and the precentral gyrus. This study provides evidence of structure-trait correlates between physical mechanical properties and measures of personality in older adults and adds to the supporting literature that neurotic traits may impact brain health in cognitively normal aging.
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Affiliation(s)
- Kyra E. Twohy
- Department of Mechanical EngineeringUniversity of DelawareNewarkDelawareUSA
| | - Mary K. Kramer
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
| | - Alexa M. Diano
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
| | - Olivia M. Bailey
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
| | - Peyton L. Delgorio
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
| | - Grace McIlvain
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
| | | | | | - Hillary Schwarb
- Department of PsychologyUniversity of Nebraska‐LincolnLincolnNebraskaUSA
- Center for Brain, Biology and BehaviorUniversity of Nebraska‐LincolnLincolnNebraskaUSA
| | - Lucy V. Hiscox
- Cardiff University Brain Research Imaging Centre (CUBRIC)Cardiff UniversityCardiffUK
| | - Curtis L. Johnson
- Department of Mechanical EngineeringUniversity of DelawareNewarkDelawareUSA
- Department of Biomedical EngineeringUniversity of DelawareNewarkDelawareUSA
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McIlvain G. The contributions of relative brain viscosity to brain function and health. Brain Commun 2024; 6:fcae424. [PMID: 39713240 PMCID: PMC11660954 DOI: 10.1093/braincomms/fcae424] [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: 06/18/2024] [Revised: 08/22/2024] [Accepted: 11/23/2024] [Indexed: 12/24/2024] Open
Abstract
Magnetic resonance elastography has emerged over the last two decades as a non-invasive method for quantitatively measuring the mechanical properties of the brain. Since the inception of the technology, brain stiffness has been the primary metric used to describe brain microstructural mechanics. However, more recently, a secondary measure has emerged as both theoretical and experimental significance, which is the ratio of tissue viscosity relative to tissue elasticity. This viscous-to-elastic ratio describes different but complementary aspects of brain microstructural health and is theorized to relate to microstructural organization, as opposed to stiffness, which is related to tissue composition. The relative viscosity of brain tissue changes regionally during maturation, aging and neurodegenerative disease. It also exhibits unique characteristics in brain tumours and hydrocephalus, and is of interest for characterizing traumatic head impacts. Most notably, regional measures of relative brain tissue viscosity appear to hold a unique role in describing cognitive function. For instance, in young adults, relatively lower hippocampal viscosity compared to elasticity repeatedly and sensitively relates to spatial, declarative and verbal memory performance. Importantly, these same trends are not found with hippocampal stiffness, or hippocampal volume, highlighting a potential sensitivity of relative viscosity to underlying cellularity that contributions to normal healthy brain function. Likewise in young adults, in the orbitofrontal cortex, lower relative viscosity relates to better performance on fluid intelligence tasks, and in the Broca's area of children ages 5-7, lower relative viscosity is indicative of better language performance. In these instances, this ratio shows heightened sensitivity over other structural MRI metrics, and importantly, provides a quantitative and intrinsic alternative to measuring structure-function relationships with task-based fMRI. There are ongoing efforts to improve the accuracy and repeatability of the relative viscosity measurement, and much work is needed to reveal the cellular underpinning of changes to tissue viscosity. But it appears clear that regionally measuring the viscous-to-elastic ratio holds the potential to noninvasively reveal an aspect of tissue microstructure that is clinically, cognitively and functionally relevant to our understanding of brain function and health.
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Affiliation(s)
- Grace McIlvain
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, Columbia University, New York, NY 10027, USA
- Department of Radiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
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Herthum H, Hetzer S, Kreft B, Tzschätzsch H, Shahryari M, Meyer T, Görner S, Neubauer H, Guo J, Braun J, Sack I. Cerebral tomoelastography based on multifrequency MR elastography in two and three dimensions. Front Bioeng Biotechnol 2022; 10:1056131. [PMID: 36532573 PMCID: PMC9755504 DOI: 10.3389/fbioe.2022.1056131] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 11/21/2022] [Indexed: 09/01/2023] Open
Abstract
Purpose: Magnetic resonance elastography (MRE) generates quantitative maps of the mechanical properties of biological soft tissues. However, published values obtained by brain MRE vary largely and lack detail resolution, due to either true biological effects or technical challenges. We here introduce cerebral tomoelastography in two and three dimensions for improved data consistency and detail resolution while considering aging, brain parenchymal fraction (BPF), systolic blood pressure, and body mass index (BMI). Methods: Multifrequency MRE with 2D- and 3D-tomoelastography postprocessing was applied to the brains of 31 volunteers (age range: 22-61 years) for analyzing the coefficient of variation (CV) and effects of biological factors. Eleven volunteers were rescanned after 1 day and 1 year to determine intraclass correlation coefficient (ICC) and identify possible long-term changes. Results: White matter shear wave speed (SWS) was slightly higher in 2D-MRE (1.28 ± 0.02 m/s) than 3D-MRE (1.22 ± 0.05 m/s, p < 0.0001), with less variation after 1 day in 2D (0.33 ± 0.32%) than in 3D (0.96 ± 0.66%, p = 0.004), which was also reflected in a slightly lower CV and higher ICC in 2D (1.84%, 0.97 [0.88-0.99]) than in 3D (3.89%, 0.95 [0.76-0.99]). Remarkably, 3D-MRE was sensitive to a decrease in white matter SWS within only 1 year, whereas no change in white matter volume was observed during this follow-up period. Across volunteers, stiffness correlated with age and BPF, but not with blood pressure and BMI. Conclusion: Cerebral tomoelastography provides high-resolution viscoelasticity maps with excellent consistency. Brain MRE in 2D shows less variation across volunteers in shorter scan times than 3D-MRE, while 3D-MRE appears to be more sensitive to subtle biological effects such as aging.
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Affiliation(s)
- Helge Herthum
- Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
- Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Bernhard Kreft
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Heiko Tzschätzsch
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Mehrgan Shahryari
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tom Meyer
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Steffen Görner
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Hennes Neubauer
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jing Guo
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jürgen Braun
- Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Ingolf Sack
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Berlin Institute of Health, Humboldt-Universität zu Berlin, Berlin, Germany
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Du Q, Bel-Brunon A, Lambert SA, Hamila N. Numerical simulation of wave propagation through interfaces using the extended finite element method for magnetic resonance elastography. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 151:3481. [PMID: 35649898 PMCID: PMC9381142 DOI: 10.1121/10.0011392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Magnetic resonance elastography (MRE) is an elasticity imaging technique for quantitatively assessing the stiffness of human tissues. In MRE, finite element method (FEM) is widely used for modeling wave propagation and stiffness reconstruction. However, in front of inclusions with complex interfaces, FEM can become burdensome in terms of the model partition and computationally expensive. In this work, we implement a formulation of FEM, known as the eXtended finite element method (XFEM), which is a method used for modeling discontinuity like crack and heterogeneity. Using a level-set method, it makes the interface independent of the mesh, thus relieving the meshing efforts. We investigate this method in two studies: wave propagation across an oblique linear interface and stiffness reconstruction of a random-shape inclusion. In the first study, numerical results by XFEM and FEM models revealing the wave conversion rules at linear interface are presented and successfully compared to the theoretical predictions. The second study, investigated in a pseudo-practical application, demonstrates further the applicability of XFEM in MRE and the convenience, accuracy, and speed of XFEM with respect to FEM. XFEM can be regarded as a promising alternative to FEM for inclusion modeling in MRE.
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Affiliation(s)
- Quanshangze Du
- Univ Lyon, INSA Lyon, CNRS, LaMCoS, UMR5259, 69621 Villeurbanne, France
| | - Aline Bel-Brunon
- Univ Lyon, INSA Lyon, CNRS, LaMCoS, UMR5259, 69621 Villeurbanne, France
- Electronic mail:
| | - Simon Auguste Lambert
- Université de Lyon, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, CNRS, Ampère UMR5005, Villeurbanne, France
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Hiscox LV, McGarry MDJ, Johnson CL. Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography. Phys Med Biol 2022; 67. [PMID: 35316794 PMCID: PMC9208651 DOI: 10.1088/1361-6560/ac5fde] [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: 09/27/2021] [Accepted: 03/22/2022] [Indexed: 12/25/2022]
Abstract
Objective. Magnetic resonance elastography (MRE) of the brain has shown promise as a sensitive neuroimaging biomarker for neurodegenerative disorders; however, the accuracy of performing MRE of the cerebral cortex warrants investigation due to the unique challenges of studying thinner and more complex geometries.Approach. A series of realistic, whole-brain simulation experiments are performed to examine the accuracy of MRE to measure the viscoelasticity (shear stiffness,μ, and damping ratio, ξ) of cortical structures predominantly effected in aging and neurodegeneration. Variations to MRE spatial resolution and the regularization of a nonlinear inversion (NLI) approach are examined.Main results. Higher-resolution MRE displacement data (1.25 mm isotropic resolution) and NLI with a low soft prior regularization weighting provided minimal measurement error compared to other studied protocols. With the optimized protocol, an average error inμand ξ was 3% and 11%, respectively, when compared with the known ground truth. Mid-line structures, as opposed to those on the cortical surface, generally display greater error. Varying model boundary conditions and reducing the thickness of the cortex by up to 0.67 mm (which is a realistic portrayal of neurodegenerative pathology) results in no loss in reconstruction accuracy.Significance. These experiments establish quantitative guidelines for the accuracy expected ofin vivoMRE of the cortex, with the proposed method providing valid MRE measures for future investigations into cortical viscoelasticity and relationships with health, cognition, and behavior.
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Affiliation(s)
- Lucy V Hiscox
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States of America.,Department of Psychology, University of Bath, Bath, United Kingdom
| | - Matthew D J McGarry
- Thayer School of Engineering, Dartmouth College, Hanover, NH, United States of America
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States of America
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Herthum H, Carrillo H, Osses A, Uribe S, Sack I, Bertoglio C. Multiple motion encoding in phase-contrast MRI: A general theory and application to elastography imaging. Med Image Anal 2022; 78:102416. [PMID: 35334444 DOI: 10.1016/j.media.2022.102416] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/23/2021] [Accepted: 03/01/2022] [Indexed: 01/04/2023]
Abstract
While MRI allows to encode the motion of tissue in the magnetization's phase, it remains yet a challenge to obtain high fidelity motion images due to wraps in the phase for high encoding efficiencies. Therefore, we propose an optimal multiple motion encoding method (OMME) and exemplify it in Magnetic Resonance Elastography (MRE) data. OMME is formulated as a non-convex least-squares problem for the motion using an arbitrary number of phase-contrast measurements with different motion encoding gradients (MEGs). The mathematical properties of OMME are proved in terms of standard deviation and dynamic range of the motion's estimate for arbitrary MEGs combination which are confirmed using synthetically generated data. OMME's performance is assessed on MRE data from in vivo human brain experiments and compared to dual encoding strategies. The unwrapped images are further used to reconstruct stiffness maps and compared to the ones obtained using conventional unwrapping methods. OMME allowed to successfully combine several MRE phase images with different MEGs, outperforming dual encoding strategies in either motion-to-noise ratio (MNR) or number of successfully reconstructed voxels with good noise stability. This lead to stiffness maps with greater resolution of details than obtained with conventional unwrapping methods. The proposed OMME method allows for a flexible and noise robust increase in the dynamic range and thus provides wrap-free phase images with high MNR. In MRE, the method may be especially suitable when high resolution images with high MNR are needed.
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Affiliation(s)
- Helge Herthum
- Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universitt zu Berlin, and Berlin Institute of Health, Berlin, 10117, Germany
| | - Hugo Carrillo
- Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile; Bernoulli Institute, University of Groningen, Groningen, 9747AG, the Netherlands
| | - Axel Osses
- Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile; Department of Mathematical Engineering, Universidad de Chile, Santiago, 8370456, Chile; ANID - Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile; ANID - Millenium Nucleus in Applied Control and Inverse Problems ACIP, Santiago, 7820436, Chile
| | - Sergio Uribe
- ANID - Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile; Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, 7820436, Chile
| | - Ingolf Sack
- Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universitt zu Berlin, and Berlin Institute of Health, Berlin, 10117, Germany
| | - Cristóbal Bertoglio
- Bernoulli Institute, University of Groningen, Groningen, 9747AG, the Netherlands.
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