1
|
Feng Y, Chandio BQ, Villalon‐Reina JE, Thomopoulos SI, Nir TM, Benavidez S, Laltoo E, Chattopadhyay T, Joshi H, Venkatasubramanian G, John JP, Jahanshad N, Reid RI, Jack CR, Weiner MW, Thompson PM. Microstructural mapping of neural pathways in Alzheimer's disease using macrostructure-informed normative tractometry. Alzheimers Dement 2025; 21:e14371. [PMID: 39737627 PMCID: PMC11782200 DOI: 10.1002/alz.14371] [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: 04/26/2024] [Revised: 08/19/2024] [Accepted: 08/21/2024] [Indexed: 01/01/2025]
Abstract
INTRODUCTION Diffusion-weighted magnetic resonance imaging (dMRI) is sensitive to the microstructural properties of brain tissues and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest without considering the underlying fiber geometry. METHODS We propose a novel macrostructure-informed normative tractometry (MINT) framework to investigate how white matter (WM) microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia. We compared MINT-derived metrics with univariate diffusion tensor imaging (DTI) metrics to examine how fiber geometry may impact the interpretation of microstructure. RESULTS In two multisite cohorts from North America and India, we find consistent patterns of microstructural and macrostructural anomalies implicated in MCI and dementia; we also rank diffusion metrics' sensitivity to dementia. DISCUSSION We show that MINT, by jointly modeling tract shape and microstructure, has the potential to disentangle and better interpret the effects of degenerative disease on the brain's neural pathways. HIGHLIGHTS Changes in diffusion tensor imaging metrics may be due to macroscopic changes. Normative models encode normal variability of diffusion metrics in healthy controls. Variational autoencoder applied on tractography can learn patterns of fiber geometry. WM microstructure and macrostructure are modeled with multivariate methods. Transfer learning uses pretraining and fine-tuning for increased efficiency.
Collapse
Affiliation(s)
- Yixue Feng
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Bramsh Q. Chandio
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Julio E. Villalon‐Reina
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Talia M. Nir
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sebastian Benavidez
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Emily Laltoo
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Tamoghna Chattopadhyay
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Himanshu Joshi
- Multimodal Brain Image Analysis Laboratory, National Institute of Mental Health and Neuro Sciences (NIMHANS)BangaloreIndia
| | - Ganesan Venkatasubramanian
- Translational Psychiatry LaboratoryNational Institute of Mental Health and Neuro Sciences (NIMHANS)BangaloreIndia
| | - John P. John
- Multimodal Brain Image Analysis Laboratory, National Institute of Mental Health and Neuro Sciences (NIMHANS)BangaloreIndia
| | - Neda Jahanshad
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Robert I. Reid
- Department of Information TechnologyMayo Clinic and FoundationRochesterMinnesotaUSA
- Department of RadiologyMayo Clinic and FoundationRochesterMinnesotaUSA
| | - Clifford R. Jack
- Department of RadiologyMayo Clinic and FoundationRochesterMinnesotaUSA
| | - Michael W. Weiner
- Department of Radiology and Biomedical ImagingUCSF School of MedicineSan FranciscoCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | | |
Collapse
|
2
|
Damestani NL, Jacoby J, Michel CB, Rashid B, Salat DH, Juttukonda MR. MRI Assessment of Cerebral White Matter Microvascular Hemodynamics Across the Adult Lifespan. J Magn Reson Imaging 2024; 60:1549-1562. [PMID: 38179863 PMCID: PMC11224140 DOI: 10.1002/jmri.29217] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 12/18/2023] [Accepted: 12/18/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Changes in cerebral hemodynamics with aging are important for understanding age-related variation in neuronal health. While many prior studies have focused on gray matter, less is known regarding white matter due in part to measurement challenges related to the lower vascular density in white matter. PURPOSE To investigate the impact of age and sex on white matter hemodynamics in a Human Connectome Project in Aging (HCP-A) cohort using tract-based spatial statistics (TBSS). STUDY TYPE Retrospective cross-sectional. POPULATION Six hundred seventy-eight typically aging individuals (381 female), aged 36-100 years. FIELD STRENGTH/SEQUENCE Multi-delay pseudo-continuous arterial spin labeling (ASL) and diffusion-weighted pulsed-gradient spin-echo echo planar imaging sequences at 3.0 T. ASSESSMENT A skeleton of mean fractional anisotropy (FA) was produced using TBSS. This skeleton was used to project ASL-derived cerebral blood flow (CBF) and arterial transit time (ATT) measures onto white matter tracts. STATISTICAL TESTS General linear models were applied to white matter FA, CBF, and ATT maps, while covarying for age and sex. Threshold-free cluster enhancement multiple comparisons correction was performed for the effects of age and sex, thresholded at PFWE < 0.05. CBF, ATT, and FA were compared between sex for each tract using analysis of covariance, with multiple comparisons correction for the number of tracts at PFDR < 0.05. RESULTS Significantly lower white matter CBF and significantly prolonged white matter ATTs were associated with older age. These effects were widespread across tracts for ATT. Significant (PFDR < 0.05) sex differences in ATT were observed across all tracts, and significant sex differences in CBF were observed in all tracts except the bilateral uncinate fasciculus. Females demonstrated significantly higher CBF compared to males across the lifespan. Few tracts demonstrated significant sex differences in FA. DATA CONCLUSION This study identified significant sex- and age-associated differences in white matter hemodynamics across tracts. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
Collapse
Affiliation(s)
- Nikou L. Damestani
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - John Jacoby
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Christa B. Michel
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Barnaly Rashid
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - David H. Salat
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston MA, USA
| | - Meher R. Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
3
|
Cheng C, Lu CF, Hsieh BY, Huang SH, Kao YCJ. Anisotropy component of DTI reveals long-term neuroinflammation following repetitive mild traumatic brain injury in rats. Eur Radiol Exp 2024; 8:82. [PMID: 39046630 PMCID: PMC11269550 DOI: 10.1186/s41747-024-00490-w] [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: 03/21/2024] [Accepted: 06/18/2024] [Indexed: 07/25/2024] Open
Abstract
BACKGROUND This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q). METHODS Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used. RESULTS At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035). CONCLUSION Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury. RELEVANCE STATEMENT Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI. KEY POINTS The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis.
Collapse
Affiliation(s)
- Ching Cheng
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Feng Lu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Bao-Yu Hsieh
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang-Gung University, Taoyuan, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Shu-Hui Huang
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Chieh Jill Kao
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| |
Collapse
|
4
|
Feng Y, Chandio BQ, Villalon-Reina JE, Thomopoulos SI, Nir TM, Benavidez S, Laltoo E, Chattopadhyay T, Joshi H, Venkatasubramanian G, John JP, Jahanshad N, Reid RI, Jack CR, Weiner MW, Thompson PM. Microstructural Mapping of Neural Pathways in Alzheimer's Disease using Macrostructure-Informed Normative Tractometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.25.591183. [PMID: 38712293 PMCID: PMC11071453 DOI: 10.1101/2024.04.25.591183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Introduction Diffusion MRI is sensitive to the microstructural properties of brain tissues, and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest, without considering the underlying fiber geometry. Methods Here, we propose a novel Macrostructure-Informed Normative Tractometry (MINT) framework, to investigate how white matter microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia. We compare MINT-derived metrics with univariate metrics from diffusion tensor imaging (DTI), to examine how fiber geometry may impact interpretation of microstructure. Results In two multi-site cohorts from North America and India, we find consistent patterns of microstructural and macrostructural anomalies implicated in MCI and dementia; we also rank diffusion metrics' sensitivity to dementia. Discussion We show that MINT, by jointly modeling tract shape and microstructure, has potential to disentangle and better interpret the effects of degenerative disease on the brain's neural pathways.
Collapse
Affiliation(s)
- Yixue Feng
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Bramsh Q. Chandio
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Julio E. Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Talia M. Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Sebastian Benavidez
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Emily Laltoo
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Tamoghna Chattopadhyay
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Himanshu Joshi
- Multimodal Brain Image Analysis Laboratory National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Ganesan Venkatasubramanian
- Translational Psychiatry Laboratory, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - John P. John
- Multimodal Brain Image Analysis Laboratory National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Robert I. Reid
- Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, United States
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, United States
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, United States
| | - Michael W. Weiner
- Department of Radiology and Biomedical Imaging, UCSF School of Medicine, San Francisco, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | | |
Collapse
|
5
|
Chad JA, Sochen N, Chen JJ, Pasternak O. Implications of fitting a two-compartment model in single-shell diffusion MRI. Phys Med Biol 2023; 68:10.1088/1361-6560/ad0216. [PMID: 37816373 PMCID: PMC10929942 DOI: 10.1088/1361-6560/ad0216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 10/10/2023] [Indexed: 10/12/2023]
Abstract
It is becoming increasingly common for studies to fit single-shell diffusion MRI data to a two-compartment model, which comprises a hindered cellular compartment and a freely diffusing isotropic compartment. These studies consistently find that the fraction of the isotropic compartment (f) is sensitive to white matter (WM) conditions and pathologies, although the actual biological source of changes infhas not been validated. In this work we put aside the biological interpretation offand study the sensitivity implications of fitting single-shell data to a two-compartment model. We identify a nonlinear transformation between the one-compartment model (diffusion tensor imaging, DTI) and a two-compartment model in which the mean diffusivities of both compartments are effectively fixed. While the analytic relationship implies that fitting this two-compartment model does not offer any more information than DTI, it explains why metrics derived from a two-compartment model can exhibit enhanced sensitivity over DTI to certain types of WM processes, such as age-related WM differences. The sensitivity enhancement should not be viewed as a substitute for acquiring multi-shell data. Rather, the results of this study provide insight into the consequences of choosing a two-compartment model when only single-shell data is available.
Collapse
Affiliation(s)
- Jordan A. Chad
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Nir Sochen
- School of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel
- School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - J Jean Chen
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Ofer Pasternak
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States of America
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States of America
| |
Collapse
|
6
|
Han A, Dhollander T, Sun YL, Chad JA, Chen JJ. Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis. Neurobiol Aging 2023; 130:22-29. [PMID: 37423114 DOI: 10.1016/j.neurobiolaging.2023.06.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/31/2023] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Diffusion magnetic resonance imaging studies often investigate white matter (WM) microstructural degeneration in aging by probing WM regions that exhibit negative age associations of fractional anisotropy (FA). However, WM regions in which FA is unassociated with age are not necessarily "spared" in aging. Besides the confound of inter-participant heterogeneity, FA conflates all intravoxel fiber populations and does not allow the detection of individual fiber-specific age associations. In this study of 541 healthy adults aged 36-100 years, we use fixel-based analysis to investigate age associations among each "fixel" within a voxel, representing individual fiber populations. We find age associations of fixel-based measures that indicate age-related differences in individual fiber populations amid complex fiber architectures. Different crossing fiber populations exhibit different slopes of age associations. Our findings may provide evidence of selective degeneration of intravoxel WM fibers in aging, which does not necessarily manifest as a change in FA and therefore escapes notice if conventional voxel-based analyses are relied upon alone.
Collapse
Affiliation(s)
- Ana Han
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Yutong L Sun
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
7
|
Teller N, Chad JA, Wong A, Gunraj H, Ji X, Goubran M, Gilboa A, Roudaia E, Sekuler A, Churchill N, Schweizer T, Gao F, Masellis M, Lam B, Heyn C, Cheng I, Fowler R, Black SE, MacIntosh BJ, Graham SJ, Chen JJ. Feasibility of diffusion-tensor and correlated diffusion imaging for studying white-matter microstructural abnormalities: Application in COVID-19. Hum Brain Mapp 2023; 44:3998-4010. [PMID: 37162380 PMCID: PMC10258529 DOI: 10.1002/hbm.26322] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/06/2023] [Accepted: 04/14/2023] [Indexed: 05/11/2023] Open
Abstract
There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion magnetic resonance imaging (MRI) methods for detecting such effects. In this work, the performances of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at the study initiation and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in tissue diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a viable single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.
Collapse
Affiliation(s)
- Nick Teller
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Alexander Wong
- Department of System Design Engineering, University of Waterloo, Waterloo, Canada
| | - Hayden Gunraj
- Department of System Design Engineering, University of Waterloo, Waterloo, Canada
| | - Xiang Ji
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Maged Goubran
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Asaf Gilboa
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Eugenie Roudaia
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Allison Sekuler
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Nathan Churchill
- Neuroscience Research Program, St. Michael's Hospital, Toronto, Canada
- Keenan Research Centre for Biomedical Science of St. Michael's Hospital, Toronto, Canada
- Department of Physics, Toronto Metropolitan University, Toronto, Canada
| | - Tom Schweizer
- Neuroscience Research Program, St. Michael's Hospital, Toronto, Canada
- Keenan Research Centre for Biomedical Science of St. Michael's Hospital, Toronto, Canada
- Department of Neurosurgery, University of Toronto, Toronto, Canada
| | - Fuqiang Gao
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Mario Masellis
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Benjamin Lam
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Chris Heyn
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Ivy Cheng
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Robert Fowler
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Sandra E Black
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - Simon J Graham
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| |
Collapse
|
8
|
Patel A, Chad JA, Chen JJ. Is adiposity associated with white matter microstructural health and intelligence differently in males and females? Obesity (Silver Spring) 2023; 31:1011-1023. [PMID: 36883598 DOI: 10.1002/oby.23686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/27/2022] [Accepted: 11/24/2022] [Indexed: 03/09/2023]
Abstract
OBJECTIVE The role of vascular risk factors in age-related brain degeneration has long been the subject of intense study, but the role of obesity remains understudied. Given known sex differences in fat storage and usage, this study investigates sex differences in the association between adiposity and white matter microstructural integrity, an important early marker of brain degeneration. METHODS This study assesses the associations between adiposity (abdominal fat ratio and liver proton density fat fraction) and brain health (measures of intelligence and white matter microstructure using diffusion-tensor imaging [DTI]) in a group of UK Biobank participants. RESULTS This study finds that intelligence and DTI metrics are indeed associated with adiposity differently in males and females. These sex differences are distinct from those in the associations of DTI metrics with age and blood pressure. CONCLUSIONS Taken together, these findings suggest that there are inherent sex-driven differences in how brain health is associated with obesity.
Collapse
Affiliation(s)
- Arjun Patel
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
9
|
Pang Y. Phase-shifted transverse relaxation orientation dependences in human brain white matter. NMR IN BIOMEDICINE 2023:e4925. [PMID: 36908074 DOI: 10.1002/nbm.4925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/24/2023] [Accepted: 03/02/2023] [Indexed: 06/18/2023]
Abstract
This work aimed to demonstrate an essential phase shift ε 0 $$ {\varepsilon}_0 $$ for better quantifying R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ in human brain white matter (WM), and to further elucidate its origin related to the directional diffusivities from standard diffusion tensor imaging (DTI). ε 0 $$ {\varepsilon}_0 $$ was integrated into a proposed generalized transverse relaxation model for characterizing previously published R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ orientation dependence profiles in brain WM, and then comparisons were made with those without ε 0 $$ {\varepsilon}_0 $$ . It was theorized that anisotropic diffusivity direction ε $$ \varepsilon $$ was collinear with an axon fiber subject to all eigenvalues and eigenvectors from an apparent diffusion tensor. To corroborate the origin of ε 0 $$ {\varepsilon}_0 $$ , R 2 $$ {R}_2 $$ orientation dependences referenced by ε $$ \varepsilon $$ were compared with those referenced by the standard principal diffusivity direction Φ $$ \Phi $$ at b-values of 1000 and 2500 (s/mm2 ). These R 2 $$ {R}_2 $$ orientation dependences were obtained from T 2 $$ {T}_2 $$ -weighted images (b = 0) of ultrahigh-resolution Connectome DTI datasets in the public domain. A normalized root-mean-square error ( NRMSE % $$ NRMSE\% $$ ) and an F $$ F $$ -test were used for evaluating curve-fittings, and statistical significance was considered to be a p of 0.05 or less. A phase-shifted model resulted in significantly reduced NRMSE % $$ NRMSE\% $$ compared with that without ε 0 $$ {\varepsilon}_0 $$ in quantifying various R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, both in vivo and ex vivo at multiple B 0 $$ {B}_0 $$ fields. The R 2 $$ {R}_2 $$ profiles based on Φ $$ \Phi $$ manifested a right-shifted phase ( ε 0 > 0 $$ {\varepsilon}_0>0 $$ ) at two b-values, while those based on ε $$ \varepsilon $$ became free from ε 0 $$ {\varepsilon}_0 $$ . For all phase-shifted R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, ε 0 $$ {\varepsilon}_0 $$ generally depended on the directional diffusivities by tan - 1 D ⊥ / D ∥ $$ {\tan}^{-1}\left({D}_{\perp }/{D}_{\parallel}\right) $$ , as predicted. In summary, a ubiquitous phase shift ε 0 $$ {\varepsilon}_0 $$ has been demonstrated as a prerequisite for better quantifying transverse relaxation orientation dependences in human brain WM. Furthermore, the origin of ε 0 $$ {\varepsilon}_0 $$ associated with the directional diffusivities from DTI has been elucidated. These findings could have a significant impact on interpretations of prior R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ datasets and on future research.
Collapse
Affiliation(s)
- Yuxi Pang
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| |
Collapse
|
10
|
Srisaikaew P, Chad JA, Mahakkanukrauh P, Anderson ND, Chen JJ. Effect of sex on the APOE4-aging interaction in the white matter microstructure of cognitively normal older adults using diffusion-tensor MRI with orthogonal-tensor decomposition (DT-DOME). Front Neurosci 2023; 17:1049609. [PMID: 36908785 PMCID: PMC9992882 DOI: 10.3389/fnins.2023.1049609] [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] [Received: 09/20/2022] [Accepted: 02/06/2023] [Indexed: 02/24/2023] Open
Abstract
The influence of the apolipoprotein E ε4 allele (APOE4) on brain microstructure of cognitively normal older adults remains incompletely understood, in part due to heterogeneity within study populations. In this study, we examined white-matter microstructural integrity in cognitively normal older adults as a function of APOE4 carrier status using conventional diffusion-tensor imaging (DTI) and the novel orthogonal-tensor decomposition (DT-DOME), accounting for the effects of age and sex. Age associations with white-matter microstructure did not significantly depend on APOE4 status, but did differ between sexes, emphasizing the importance of accounting for sex differences in APOE research. Moreover, we found the DT-DOME to be more sensitive than conventional DTI metrics to such age-related and sex effects, especially in crossing WM fiber regions, and suggest their use in further investigation of white matter microstructure across the life span in health and disease.
Collapse
Affiliation(s)
- Patcharaporn Srisaikaew
- Ph.D. Program in Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Department of Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Jordan A. Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Pasuk Mahakkanukrauh
- Department of Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Excellence in Osteology Research and Training Center, Chiang Mai University, Chiang Mai, Thailand
| | - Nicole D. Anderson
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - J. Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
11
|
Taha HT, Chad JA, Chen JJ. DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants. Neurobiol Aging 2022; 115:39-49. [PMID: 35468551 DOI: 10.1016/j.neurobiolaging.2022.03.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/09/2022] [Accepted: 03/12/2022] [Indexed: 12/25/2022]
Abstract
Studies of healthy brain aging traditionally report diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at typical b-values (approximately 1000 s/mm2) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental processes by incorporating additional data at a higher b-value. In this study, using diffusion data (b-values of 1000 and 2000 s/mm2) from 700 UK Biobank participants aged 46-80, we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We establish a pattern of lower kurtosis alongside higher diffusivity among older adults, with kurtosis generally being more sensitive to age than diffusivity. We also find discrepancies between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion when interpreting age-related diffusivity patterns.
Collapse
Affiliation(s)
- Hiba T Taha
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
| |
Collapse
|