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Wang S, Eckstein KN, Guertler CA, Johnson CL, Okamoto RJ, McGarry MD, Bayly PV. Post-mortem changes of anisotropic mechanical properties in the porcine brain assessed by MR elastography. BRAIN MULTIPHYSICS 2024; 6:100091. [PMID: 38933498 PMCID: PMC11207183 DOI: 10.1016/j.brain.2024.100091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024] Open
Abstract
Knowledge of the mechanical properties of brain tissue in vivo is essential to understanding the mechanisms underlying traumatic brain injury (TBI) and to creating accurate computational models of TBI and neurosurgical simulation. Brain white matter, which is composed of aligned, myelinated, axonal fibers, is structurally anisotropic. White matter in vivo also exhibits mechanical anisotropy, as measured by magnetic resonance elastography (MRE), but measurements of anisotropy obtained by mechanical testing of white matter ex vivo have been inconsistent. The minipig has a gyrencephalic brain with similar white matter and gray matter proportions to humans and therefore provides a relevant model for human brain mechanics. In this study, we compare estimates of anisotropic mechanical properties of the minipig brain obtained by identical, non-invasive methods in the live (in vivo) and dead animals (in situ). To do so, we combine wave displacement fields from MRE and fiber directions derived from diffusion tensor imaging (DTI) with a finite element-based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal alive and at specific times post-mortem. These maps show that white matter is stiffer, more dissipative, and more anisotropic than gray matter when the minipig is alive, but that these differences largely disappear post-mortem, with the exception of tensile anisotropy. Overall, brain tissue becomes stiffer, less dissipative, and less mechanically anisotropic post-mortem. These findings emphasize the importance of testing brain tissue properties in vivo. Statement of Significance In this study, MRE and DTI in the minipig were combined to estimate, for the first time, anisotropic mechanical properties in the living brain and in the same brain after death. Significant differences were observed in the anisotropic behavior of brain tissue post-mortem. These results demonstrate the importance of measuring brain tissue properties in vivo as well as ex vivo, and provide new quantitative data for the development of computational models of brain biomechanics.
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Affiliation(s)
- Shuaihu Wang
- Washington University in St. Louis, Mechanical Engineering and Material Science, United States
| | - Kevin N. Eckstein
- Washington University in St. Louis, Mechanical Engineering and Material Science, 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, Mechanical Engineering and Material Science, United States
- Washington University in St. Louis, Biomedical Engineering, United States
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2
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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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3
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Ito D, Numano T, Habe T, Okuda S, Nozaki T, Jinzaki M. Fast abdominal magnetic resonance elastography with simultaneous encoding of three-dimensional displacements. Magn Reson Imaging 2024; 108:138-145. [PMID: 38360120 DOI: 10.1016/j.mri.2024.02.009] [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: 10/21/2023] [Revised: 02/07/2024] [Accepted: 02/11/2024] [Indexed: 02/17/2024]
Abstract
Three-dimensional (3D) magnetic resonance elastography (MRE) is more accurate than two-dimensional (2D) MRE; however, it requires long-term acquisition. This study aimed to reduce the acquisition time of abdominal 3D MRE using a new sample interval modulation (short-SLIM) approach that can acquire all three motions faster while reducing the prolongation of echo time and flow compensation. To this end, two types of phantom studies and an in vivo test of the liver in three healthy volunteers were performed to compare the performances of conventional spin-echo echo-planar (SE-EPI) MRE, conventional SLIM and short-SLIM. One phantom study measured the mean amplitude and shear modulus within the overall region of a homogeneous phantom by changing the mechanical vibration power to assess the robustness to the lowered phase-to-noise ratio in short-SLIM. The other measured the mean shear modulus in the stiff and background materials of a phantom with an embedded stiffer rod to assess the performance of short-SLIM for complex wave patterns with wave interference. The Spearman's rank correlation coefficient was used to assess similarity of elastograms in the rod-embedded phantom and liver between methods. The results of the phantom study changing the vibration power indicated that there was little difference between conventional MRE and short-SLIM. Moreover, the elastogram pattern and the mean shear modulus in the rod-embedded phantom in conventional SLIM and short-SLIM did not change for conventional MRE; the liver test also showed a small difference between the acquisition techniques. This study demonstrates that short-SLIM can provide MRE results comparable to those of conventional MRE. Short-SLIM can reduce the total acquisition time by a factor of 2.25 compared to conventional 3D MRE time, leading to an improvement in the accuracy of shear modulus estimation by suppressing the patient movements.
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Affiliation(s)
- Daiki Ito
- Office of Radiation Technology, Keio University Hospital, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10, Higashiogu, Arakawa-ku, Tokyo 116-8551, Japan.
| | - Tomokazu Numano
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10, Higashiogu, Arakawa-ku, Tokyo 116-8551, Japan; Health Research Institute, National Institute of Advanced Industrial Science and Technology, 1-2-1, Namiki, Tsukuba-shi, Ibaraki 305-8564, Japan
| | - Tetsushi Habe
- Office of Radiation Technology, Keio University Hospital, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Shigeo Okuda
- Department of Diagnostic Radiology, National Tokyo Medical Center, 2-5-1, Higashigaoka, Meguro-ku, Tokyo 152-8902, Japan; Department of Radiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Taiki Nozaki
- Department of Radiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
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4
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McIlvain G, Magoon EM, Clements RG, Merritt A, Hiscox LV, Schwarb H, Johnson CL. Acute effects of high-intensity exercise on brain mechanical properties and cognitive function. Brain Imaging Behav 2024:10.1007/s11682-024-00873-y. [PMID: 38538876 DOI: 10.1007/s11682-024-00873-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/07/2024] [Indexed: 04/26/2024]
Abstract
Previous studies have shown that engagement in even a single session of exercise can improve cognitive performance in the short term. However, the underlying physiological mechanisms contributing to this effect are still being studied. Recently, with improvements to advanced quantitative neuroimaging techniques, brain tissue mechanical properties can be sensitively and noninvasively measured with magnetic resonance elastography (MRE) and regional brain mechanical properties have been shown to reflect individual cognitive performance. Here we assess brain mechanical properties before and immediately after engagement in a high-intensity interval training (HIIT) regimen, as well as one-hour post-exercise. We find that immediately after exercise, subjects in the HIIT group had an average global brain stiffness decrease of 4.2% (p < 0.001), and an average brain damping ratio increase of 3.1% (p = 0.002). In contrast, control participants who did not engage in exercise showed no significant change over time in either stiffness or damping ratio. Changes in brain mechanical properties with exercise appeared to be regionally dependent, with the hippocampus decreasing in stiffness by 10.4%. We also found that one-hour after exercise, brain mechanical properties returned to initial baseline values. The magnitude of changes to brain mechanical properties also correlated with improvements in reaction time on executive control tasks (Eriksen Flanker and Stroop) with exercise. Understanding the neural changes that arise in response to exercise may inform potential mechanisms behind improvements to cognitive performance with acute exercise.
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Affiliation(s)
- Grace McIlvain
- Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Emily M Magoon
- Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA
| | - Rebecca G Clements
- Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA
| | - Alexis Merritt
- Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA
| | - Lucy V Hiscox
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Hillary Schwarb
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA.
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5
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Khair AM, McIlvain G, McGarry MDJ, Kandula V, Yue X, Kaur G, Averill LW, Choudhary AK, Johnson CL, Nikam RM. Clinical application of magnetic resonance elastography in pediatric neurological disorders. Pediatr Radiol 2023; 53:2712-2722. [PMID: 37794174 PMCID: PMC11086054 DOI: 10.1007/s00247-023-05779-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 09/15/2023] [Accepted: 09/18/2023] [Indexed: 10/06/2023]
Abstract
Magnetic resonance elastography is a relatively new, rapidly evolving quantitative magnetic resonance imaging technique which can be used for mapping the viscoelastic mechanical properties of soft tissues. MR elastography measurements are akin to manual palpation but with the advantages of both being quantitative and being useful for regions which are not available for palpation, such as the human brain. MR elastography is noninvasive, well tolerated, and complements standard radiological and histopathological studies by providing in vivo measurements that reflect tissue microstructural integrity. While brain MR elastography studies in adults are becoming frequent, published studies on the utility of MR elastography in children are sparse. In this review, we have summarized the major scientific principles and recent clinical applications of brain MR elastography in diagnostic neuroscience and discuss avenues for impact in assessing the pediatric brain.
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Affiliation(s)
| | - Grace McIlvain
- Department of Biomedical Engineering, University of Delaware, Newark, DE, USA
| | | | - Vinay Kandula
- Department of Radiology, Nemours Children's Hospital, Wilmington, DE, USA
| | - Xuyi Yue
- Department of Radiology, Nemours Children's Hospital, Wilmington, DE, USA
- Department of Biomedical Research, Nemours Children's Hospital, Wilmington, DE, USA
| | - Gurcharanjeet Kaur
- Department of Neurology, New York-Presbyterian / Columbia University Irving Medical Center, New York, NY, USA
| | - Lauren W Averill
- Department of Radiology, Nemours Children's Hospital, Wilmington, DE, USA
| | - Arabinda K Choudhary
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, USA
- Department of Biomedical Research, Nemours Children's Hospital, Wilmington, DE, USA
| | - Rahul M Nikam
- Department of Radiology, Nemours Children's Hospital, Wilmington, DE, USA.
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6
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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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7
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Mohammed S, Kozlowski P, Salcudean S. Phase-regularized and displacement-regularized compressed sensing for fast magnetic resonance elastography. NMR IN BIOMEDICINE 2023; 36:e4899. [PMID: 36628624 DOI: 10.1002/nbm.4899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 12/12/2022] [Accepted: 01/01/2023] [Indexed: 06/15/2023]
Abstract
Liver magnetic resonance elastography (MRE) is a noninvasive stiffness measurement technique that captures the tissue displacement in the phase of the signal. To limit the scanning time to a single breath-hold, liver MRE usually involves advanced readout techniques such as simultaneous multislice (SMS) or multishot methods. Furthermore, all these readout techniques require additional in-plane acceleration using either parallel imaging capabilities, such as sensitivity encoding (SENSE), or k -space undersampling, such as compressed sensing (CS). However, these methods apply a single regularization function on the complex image. This study aims to design and evaluate methods that use separate regularization on the magnitude and phase of MRE to exploit their distinct spatiotemporal characteristics. Specifically, we introduce two compressed sensing methods. The first method, termed phase-regularized compressed sensing (PRCS), applies a two-dimensional total variation (TV) prior to the magnitude and two-dimensional wavelet regularization to the phase. The second method, termed displacement-regularized compressed sensing (DRCS), exploits the spatiotemporal redundancy using 3D total variation on the magnitude. Additionally, DRCS includes a displacement fitting function to apply wavelet regularization to the displacement phasor. Both DRCS and PRCS were evaluated with different levels of compression factors in three datasets: an in silico abdomen dataset, an in vitro tissue-mimicking phantom, and an in vivo liver dataset. The reconstructed images were compared with the full sampled reconstruction, zero-filling reconstruction, wavelet-regularized compressed sensing, and a low rank plus sparse reconstruction. The metrics used for quantitative evaluation were the structural similarity index (SSIM) of magnitude (M-SSIM), displacement (D-SSIM), and shear modulus (S-SSIM), and mean shear modulus. Results from highly undersampled in silico and in vitro datasets demonstrate that the DRCS method provides higher reconstruction quality than the conventional compressed sensing method for a wide range of stiffness values. Notably, DRCS provides 24% and 22% increase in D-SSIM compared with CS for the in silico and in vitro datasets, respectively. Comparison with liver stiffness measured from full sampled data and highly undersampled data (CR=4) demonstrates that the DRCS method provided the strongest correlation ( R 2 =0.95), second-lowest mean bias (-0.18 kPa, lowest for CS with -0.16 kPa), and lowest coefficient of variation (CV=3.6%). Our results demonstrate the potential of using DRCS to improve the reconstruction quality of accelerated MRE.
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Affiliation(s)
- Shahed Mohammed
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
| | - Piotr Kozlowski
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Septimiu Salcudean
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
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8
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Jyoti D, McGarry M, Caban-Rivera DA, Van Houten E, Johnson CL, Paulsen K. Transversely-isotropic brain in vivo MR elastography with anisotropic damping. J Mech Behav Biomed Mater 2023; 141:105744. [PMID: 36893687 PMCID: PMC10084917 DOI: 10.1016/j.jmbbm.2023.105744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/17/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023]
Abstract
Measuring tissue parameters from increasingly sophisticated mechanical property models may uncover new contrast mechanisms with clinical utility. Building on previous work on in vivo brain MR elastography (MRE) with a transversely-isotropic with isotropic damping (TI-ID) model, we explore a new transversely-isotropic with anisotropic damping (TI-AD) model that involves six independent parameters describing direction-dependent behavior for both stiffness and damping. The direction of mechanical anisotropy is determined by diffusion tensor imaging and we fit three complex-valued moduli distributions across the full brain volume to minimize differences between measured and modeled displacements. We demonstrate spatially accurate property reconstruction in an idealized shell phantom simulation, as well as an ensemble of 20 realistic, randomly-generated simulated brains. We characterize the simulated precisions of all six parameters across major white matter tracts to be high, suggesting that they can be measured independently with acceptable accuracy from MRE data. Finally, we present in vivo anisotropic damping MRE reconstruction data. We perform t-tests on eight repeated MRE brain exams on a single-subject, and find that the three damping parameters are statistically distinct for most tracts, lobes and the whole brain. We also show that population variations in a 17-subject cohort exceed single-subject measurement repeatability for most tracts, lobes and whole brain, for all six parameters. These results suggest that the TI-AD model offers new information that may support differential diagnosis of brain diseases.
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Affiliation(s)
- Dhrubo Jyoti
- Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
| | - Matthew McGarry
- Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
| | | | | | | | - Keith Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA; Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA
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9
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Clements RG, Claros-Olivares CC, McIlvain G, Brockmeier AJ, Johnson CL. Mechanical Property Based Brain Age Prediction using Convolutional Neural Networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.12.528186. [PMID: 36824781 PMCID: PMC9948973 DOI: 10.1101/2023.02.12.528186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
Brain age is a quantitative estimate to explain an individual's structural and functional brain measurements relative to the overall population and is particularly valuable in describing differences related to developmental or neurodegenerative pathology. Accurately inferring brain age from brain imaging data requires sophisticated models that capture the underlying age-related brain changes. Magnetic resonance elastography (MRE) is a phase contrast MRI technology that uses external palpations to measure brain mechanical properties. Mechanical property measures of viscoelastic shear stiffness and damping ratio have been found to change across the entire life span and to reflect brain health due to neurodegenerative diseases and even individual differences in cognitive function. Here we develop and train a multi-modal 3D convolutional neural network (CNN) to model the relationship between age and whole brain mechanical properties. After training, the network maps the measurements and other inputs to a brain age prediction. We found high performance using the 3D maps of various mechanical properties to predict brain age. Stiffness maps alone were able to predict ages of the test group subjects with a mean absolute error (MAE) of 3.76 years, which is comparable to single inputs of damping ratio (MAE: 3.82) and outperforms single input of volume (MAE: 4.60). Combining stiffness and volume in a multimodal approach performed the best, with an MAE of 3.60 years, whereas including damping ratio worsened model performance. Our results reflect previous MRE literature that had demonstrated that stiffness is more strongly related to chronological age than damping ratio. This machine learning model provides the first prediction of brain age from brain biomechanical data-an advancement towards sensitively describing brain integrity differences in individuals with neuropathology.
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10
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Delgorio PL, Hiscox LV, McIlvain G, Kramer MK, Diano AM, Twohy KE, Merritt AA, McGarry MDJ, Schwarb H, Daugherty AM, Ellison JM, Lanzi AM, Cohen ML, Martens CR, Johnson CL. Hippocampal subfield viscoelasticity in amnestic mild cognitive impairment evaluated with MR elastography. Neuroimage Clin 2023; 37:103327. [PMID: 36682312 PMCID: PMC9871742 DOI: 10.1016/j.nicl.2023.103327] [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: 08/08/2022] [Revised: 01/06/2023] [Accepted: 01/16/2023] [Indexed: 01/19/2023]
Abstract
Hippocampal subfields (HCsf) are brain regions important for memory function that are vulnerable to decline with amnestic mild cognitive impairment (aMCI), which is often a preclinical stage of Alzheimer's disease. Studies in aMCI patients often assess HCsf tissue integrity using measures of volume, which has little specificity to microstructure and pathology. We use magnetic resonance elastography (MRE) to examine the viscoelastic mechanical properties of HCsf tissue, which is related to structural integrity, and sensitively detect differences in older adults with aMCI compared to an age-matched control group. Group comparisons revealed HCsf viscoelasticity is differentially affected in aMCI, with CA1-CA2 and DG-CA3 exhibiting lower stiffness and CA1-CA2 exhibiting higher damping ratio, both indicating poorer tissue integrity in aMCI. Including HCsf stiffness in a logistic regression improves classification of aMCI beyond measures of volume alone. Additionally, lower DG-CA3 stiffness predicted aMCI status regardless of DG-CA3 volume. These findings showcase the benefit of using MRE in detecting subtle pathological tissue changes in individuals with aMCI via the HCsf particularly affected in the disease.
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Affiliation(s)
- Peyton L Delgorio
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Lucy V Hiscox
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Grace McIlvain
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Mary K Kramer
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Alexa M Diano
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Kyra E Twohy
- Department of Mechanical Engineering, University of Delaware, Newark, DE, United States
| | - Alexis A Merritt
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | | | - Hillary Schwarb
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Ana M Daugherty
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI, United States
| | - James M Ellison
- Swank Memory Care and Geriatric Consultation, ChristianaCare, Wilmington, DE, United States; Department of Communication Sciences and Disorders, University of Delaware, Newark, DE, United States
| | - Alyssa M Lanzi
- Department of Communication Sciences and Disorders, University of Delaware, Newark, DE, United States
| | - Matthew L Cohen
- Department of Communication Sciences and Disorders, University of Delaware, Newark, DE, United States
| | - Christopher R Martens
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States; Department of Mechanical Engineering, University of Delaware, Newark, DE, United States.
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11
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McIlvain G, Schneider JM, Matyi MA, McGarry MD, Qi Z, Spielberg JM, Johnson CL. Mapping brain mechanical property maturation from childhood to adulthood. Neuroimage 2022; 263:119590. [PMID: 36030061 PMCID: PMC9950297 DOI: 10.1016/j.neuroimage.2022.119590] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/10/2022] [Accepted: 08/23/2022] [Indexed: 02/07/2023] Open
Abstract
Magnetic resonance elastography (MRE) is a phase contrast MRI technique which uses external palpation to create maps of brain mechanical properties noninvasively and in vivo. These mechanical properties are sensitive to tissue microstructure and reflect tissue integrity. MRE has been used extensively to study aging and neurodegeneration, and to assess individual cognitive differences in adults, but little is known about mechanical properties of the pediatric brain. Here we use high-resolution MRE imaging in participants of ages ranging from childhood to adulthood to understand brain mechanical properties across brain maturation. We find that brain mechanical properties differ considerably between childhood and adulthood, and that neuroanatomical subregions have differing maturational trajectories. Overall, we observe lower brain stiffness and greater brain damping ratio with increasing age from 5 to 35 years. Gray and white matter change differently during maturation, with larger changes occurring in gray matter for both stiffness and damping ratio. We also found that subregions of cortical and subcortical gray matter change differently, with the caudate and thalamus changing the most with age in both stiffness and damping ratio, while cortical subregions have different relationships with age, even between neighboring regions. Understanding how brain mechanical properties mature using high-resolution MRE will allow for a deeper understanding of the neural substrates supporting brain function at this age and can inform future studies of atypical maturation.
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Affiliation(s)
- Grace McIlvain
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Julie M Schneider
- Department of Communication Sciences and Disorders, Louisiana State University, Baton Rouge, LA, United States
| | - Melanie A Matyi
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
| | - Matthew Dj McGarry
- Thayer School of Engineering, Dartmouth College, Hanover, NH, United States
| | - Zhenghan Qi
- Department of Communication Sciences and Disorders, Northeastern University, Boston, MA, United States
| | - Jeffrey M Spielberg
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States; Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, United States.
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