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Kim J, Barcus R, Lipford ME, Yuan H, Ririe DG, Jung Y, Vlasova RM, Styner M, Nader MA, Whitlow CT. Effects of multiple anesthetic exposures on rhesus macaque brain development: a longitudinal structural MRI analysis. Cereb Cortex 2024; 34:bhad463. [PMID: 38142289 PMCID: PMC10793576 DOI: 10.1093/cercor/bhad463] [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: 03/06/2023] [Revised: 11/10/2023] [Accepted: 11/13/2023] [Indexed: 12/25/2023] Open
Abstract
Concerns about the potential neurotoxic effects of anesthetics on developing brain exist. When making clinical decisions, the timing and dosage of anesthetic exposure are critical factors to consider due to their associated risks. In our study, we investigated the impact of repeated anesthetic exposures on the brain development trajectory of a cohort of rhesus monkeys (n = 26) over their first 2 yr of life, utilizing longitudinal magnetic resonance imaging data. We hypothesized that early or high-dose anesthesia exposure could negatively influence structural brain development. By employing the generalized additive mixed model, we traced the longitudinal trajectories of brain volume, cortical thickness, and white matter integrity. The interaction analysis revealed that age and cumulative anesthetic dose were variably linked to white matter integrity but not to morphometric measures. Early high-dose exposure was associated with increased mean, axial, and radial diffusivities across all white matter regions, compared to late-low-dose exposure. Our findings indicate that early or high-dose anesthesia exposure during infancy disrupts structural brain development in rhesus monkeys. Consequently, the timing of elective surgeries and procedures that require anesthesia for children and pregnant women should be strategically planned to account for the cumulative dose of volatile anesthetics, aiming to minimize the potential risks to brain development.
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Affiliation(s)
- Jeongchul Kim
- Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- School of Biomedical Engineering and Sciences, Virginia Tech-Wake Forest University, Winston-Salem, NC, United States
| | - Richard Barcus
- Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Megan E Lipford
- Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- School of Biomedical Engineering and Sciences, Virginia Tech-Wake Forest University, Winston-Salem, NC, United States
| | - Hongyu Yuan
- Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Douglas G Ririe
- Pain Mechanisms Lab, Department of Anesthesiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Youngkyoo Jung
- Department of Biomedical Engineering, University of California Davis, Davis, CA, United States
| | - Roza M Vlasova
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Michael A Nader
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Center for Research on Substance Use and Addiction, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Christopher T Whitlow
- Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- School of Biomedical Engineering and Sciences, Virginia Tech-Wake Forest University, Winston-Salem, NC, United States
- Center for Research on Substance Use and Addiction, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, United States
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Tounekti S, Alizadeh M, Middleton D, Harrop JS, Hiba B, Krisa L, Mekkaoui C, Mohamed FB. Metal artifact reduction around cervical spine implant using diffusion tensor imaging at 3T: A phantom study. Magn Reson Imaging 2024; 105:57-66. [PMID: 37939969 PMCID: PMC10841892 DOI: 10.1016/j.mri.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of patients with metal implants results in severe geometric distortion. We propose and demonstrate a method to alleviate the technical challenges facing the acquisition of DTI on post-operative cases and longitudinal evaluation of therapeutics. MATERIAL AND METHODS The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented EPI, termed rFOV-PS-EPI. A custom-built phantom based on a cervical spine model with metal implants was used to collect DTI data at 3 Tesla scanner using: rFOV-PS-EPI, reduced Field-Of-View single-shot EPI (rFOV-SS-EPI), and conventional full FOV techniques including SS-EPI, PS-EPI, and readout-segmented EPI (RS-EPI). Geometric distortion, SNR, and signal void were assessed to evaluate images and compare the sequences. A two-sample t-test was performed with p-value of 0.05 or less to indicate statistical significance. RESULTS The reduced FOV techniques showed better capability to reduce distortions compared to the Full FOV techniques. The rFOV-PS-EPI method provided DTI images of the phantom at the level of the hardware whereas the conventional rFOV-SS-EPI is useful only when the metal is approximately 20 mm away. In addition, compared to the rFOV-SS-EPI technique, the suggested approach produced smaller signal voids area as well as significantly reduced geometric distortion in Circularity (p < 0.005) and Eccentricity (p < 0.005) measurements. No statistically significant differences were found for these geometric distortion measurements between the rFOV-PS-EPI DTI sequence and conventional structural T2 images (p > 0.05). CONCLUSION The combination of rFOV and a phase-segmented acquisition approach is effective for reducing metal-induced distortions in DTI scan on spinal cord with metal hardware at 3 T.
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Affiliation(s)
- Slimane Tounekti
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA.
| | - Mahdi Alizadeh
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Devon Middleton
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - James S Harrop
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Bassem Hiba
- Institut des Sciences Cognitives, CNRS UMR 5229, Université Lyon 1, Lyon, France
| | - Laura Krisa
- Department of Physical Therapy, Thomas Jefferson University, Philadelphia, PA, USA
| | - Choukri Mekkaoui
- Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; A.A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Feroze B Mohamed
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
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Valcourt Caron A, Shmuel A, Hao Z, Descoteaux M. versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database. Front Neuroinform 2023; 17:1191200. [PMID: 37637471 PMCID: PMC10449583 DOI: 10.3389/fninf.2023.1191200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/27/2023] [Indexed: 08/29/2023] Open
Abstract
The lack of "gold standards" in Diffusion Weighted Imaging (DWI) makes validation cumbersome. To tackle this task, studies use translational analysis where results in humans are benchmarked against findings in other species. Non-Human Primates (NHP) are particularly interesting for this, as their cytoarchitecture is closely related to humans. However, tools used for processing and analysis must be adapted and finely tuned to work well on NHP images. Here, we propose versaFlow, a modular pipeline implemented in Nextflow, designed for robustness and scalability. The pipeline is tailored to in vivo NHP DWI at any spatial resolution; it allows for maintainability and customization. Processes and workflows are implemented using cutting-edge and state-of-the-art Magnetic Resonance Imaging (MRI) processing technologies and diffusion modeling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD), and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND). Using versaFlow, we provide an in-depth study of the variability of diffusion metrics computed on 32 subjects from 3 sites of the Primate Data Exchange (PRIME-DE), which contains anatomical T1-weighted (T1w) and T2-weighted (T2w) images, functional MRI (fMRI), and DWI of NHP brains. This dataset includes images acquired over a range of resolutions, using single and multi-shell gradient samplings, on multiple scanner vendors. We perform a reproducibility study of the processing of versaFlow using the Aix-Marseilles site's data, to ensure that our implementation has minimal impact on the variability observed in subsequent analyses. We report very high reproducibility for the majority of metrics; only gamma distribution parameters of DIAMOND display less reproducible behaviors, due to the absence of a mechanism to enforce a random number seed in the software we used. This should be taken into consideration when future applications are performed. We show that the PRIME-DE diffusion data exhibits a great level of variability, similar or greater than results obtained in human studies. Its usage should be done carefully to prevent instilling uncertainty in statistical analyses. This hints at a need for sufficient harmonization in acquisition protocols and for the development of robust algorithms capable of managing the variability induced in imaging due to differences in scanner models and/or vendors.
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Affiliation(s)
- Alex Valcourt Caron
- Sherbrooke Connectivity Imaging Laboratory, Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Amir Shmuel
- Brain Imaging Signals Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ziqi Hao
- Brain Imaging Signals Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory, Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
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Tounekti S, Alizadeh M, Middleton D, Harrop JS, Bassem H, Krisa L, Mekkaoui C, Mohamed FB. Metal Artifact Reduction Around Cervical Spine Implant Using Diffusion Tensor Imaging at 3T: A Phantom Study. RESEARCH SQUARE 2023:rs.3.rs-2665952. [PMID: 36993535 PMCID: PMC10055636 DOI: 10.21203/rs.3.rs-2665952/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of a patient with a metal implant results in severe geometric image distortion. A method has been proposed here to alleviate the technical challenges facing the acquisition of DTI in post-operative cases and to evaluate longitudinal therapeutics. The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented acquisition scheme (rFOV-PS-EPI) for significantly mitigating metal-induced distortions. A custom-built phantom based on spine model with metal implant was used to collect high-resolution DTI data at 3 Tesla scanner using a home-grown diffusion MRI pulse sequence, rFOV-PS-EPI, single-shot (rFOV-SS-EPI), and the conventional full FOV techniques including SS-EPI, PS-EPI, and the readout-segmented (RS-EPI). This newly developed method provides high-resolution images with significant reduced metal-induced artifacts. In contrast to the other techniques, the rFOV-PS-EPI allows DTI measurement at the level of the metal hardware whereas the current rFOV-SS-EPI is useful when the metal is approximately 20 mm away. The developed approach enables high-resolution DTI in patients with metal implant.
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Grier MD, Yacoub E, Adriany G, Lagore RL, Harel N, Zhang RY, Lenglet C, Uğurbil K, Zimmermann J, Heilbronner SR. Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain. Neuroimage 2022; 255:119200. [PMID: 35427769 PMCID: PMC9446284 DOI: 10.1016/j.neuroimage.2022.119200] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/08/2022] [Accepted: 04/07/2022] [Indexed: 11/26/2022] Open
Abstract
Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.
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Affiliation(s)
- Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Gregor Adriany
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Russell L Lagore
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States
| | - Ru-Yuan Zhang
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, P.R. China; Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, P.R. China; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States.
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High B-value diffusion tensor imaging for early detection of hippocampal microstructural alteration in a mouse model of multiple sclerosis. Sci Rep 2022; 12:12008. [PMID: 35835801 PMCID: PMC9283448 DOI: 10.1038/s41598-022-15511-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 06/24/2022] [Indexed: 11/23/2022] Open
Abstract
Several studies have highlighted the value of diffusion tensor imaging (DTI) with strong diffusion weighting to reveal white matter microstructural lesions, but data in gray matter (GM) remains scarce. Herein, the effects of b-values combined with different numbers of diffusion-encoding directions (NDIRs) on DTI metrics to capture the normal hippocampal microstructure and its early alterations were investigated in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis [EAE]). Two initial DTI datasets (B2700-43Dir acquired with b = 2700 s.mm−2 and NDIR = 43; B1000-22Dir acquired with b = 1000 s.mm−2 and NDIR = 22) were collected from 18 normal and 18 EAE mice at 4.7 T. Three additional datasets (B2700-22Dir, B2700-12Dir and B1000-12Dir) were extracted from the initial datasets. In healthy mice, we found a significant influence of b-values and NDIR on all DTI metrics. Confronting unsupervised hippocampal layers classification to the true anatomical classification highlighted the remarkable discrimination of the molecular layer with B2700-43Dir compared with the other datasets. Only DTI from the B2700 datasets captured the dendritic loss occurring in the molecular layer of EAE mice. Our findings stress the needs for both high b-values and sufficient NDIR to achieve a GM DTI with more biologically meaningful correlations, though DTI-metrics should be interpreted with caution in these settings.
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Zhang J, Liu S, Dai E, Ye X, Shi D, Wu Y, Lu J, Guo H. Slab boundary artifact correction in multislab imaging using convolutional-neural-network-enabled inversion for slab profile encoding. Magn Reson Med 2021; 87:1546-1560. [PMID: 34655095 DOI: 10.1002/mrm.29047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 09/23/2021] [Accepted: 09/25/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE This study aims to propose a novel algorithm for slab boundary artifact correction in both single-band multislab imaging and simultaneous multislab (SMSlab) imaging. THEORY AND METHODS In image domain, the formation of slab boundary artifacts can be regarded as modulating the artifact-free images using the slab profiles and introducing aliasing along the slice direction. Slab boundary artifact correction is the inverse problem of this process. An iterative algorithm based on convolutional neural networks (CNNs) is proposed to solve the problem, termed CNN-enabled inversion for slab profile encoding (CPEN). Diffusion-weighted SMSlab images and reference images without slab boundary artifacts were acquired in 7 healthy subjects for training. Images of 5 healthy subjects were acquired for testing, including single-band multislab and SMSlab images with 1.3-mm or 1-mm isotropic resolution. CNN-enabled inversion for slab profile encoding was compared with a previously reported method (i.e., nonlinear inversion for slab profile encoding [NPEN]). RESULTS CNN-enabled inversion for slab profile encoding reduces the slab boundary artifacts in both single-band multislab and SMSlab images. It also suppresses the slab boundary artifacts in the diffusion metric maps. Compared with NPEN, CPEN shows fewer residual artifacts in different acquisition protocols and more significant improvements in quantitative assessment, and it also accelerates the computation by more than 35 times. CONCLUSION CNN-enabled inversion for slab profile encoding can reduce the slab boundary artifacts in multislab acquisitions. It shows better slab boundary artifact correction capacity, higher robustness, and computation efficiency when compared with NPEN. It has the potential to improve the accuracy of multislab acquisitions in high-resolution DWI and functional MRI.
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Affiliation(s)
- Jieying Zhang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China
| | - Simin Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China
| | - Erpeng Dai
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China.,Department of Radiology, Stanford University, Stanford, California, USA
| | - Xinyu Ye
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China
| | - Diwei Shi
- Center for Nano and Micro Mechanics, Tsinghua University, Beijing, People's Republic of China
| | - Yuhsuan Wu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China
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Zhang X, Li CX, Yan Y, Nair G, Rilling JK, Herndon JG, Preuss TM, Hu X, Li L. In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T. Magn Reson Imaging 2020; 77:194-203. [PMID: 33359631 DOI: 10.1016/j.mri.2020.12.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 10/30/2020] [Accepted: 12/20/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Diffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. METHODS A multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. RESULTS The SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. CONCLUSION The single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.
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Affiliation(s)
- Xiaodong Zhang
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America; Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America.
| | - Chun-Xia Li
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Yumei Yan
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Govind Nair
- qMRI Core Facility, NINDS, NIH, Bethesda, MD 20892, United States of America
| | - James K Rilling
- Department of Anthropology, Emory University, Atlanta, GA, United States of America; Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - James G Herndon
- Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Todd M Preuss
- Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Xiaoping Hu
- Dept of Bioengineering, University of California, Riverside, CA, United States of America
| | - Longchuan Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, United States of America.
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Wang P, Wang D, Zhang J, Bai R, Qian M, Sun Y, Lu Y, Zhang X. Evaluation of Submillimeter Diffusion Imaging of the Macaque Brain Using Readout-Segmented EPI at 7 T. IEEE Trans Biomed Eng 2019; 66:2945-2951. [PMID: 30762524 DOI: 10.1109/tbme.2019.2899132] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The purpose of the present study was to achieve submillimeter-level diffusion tensor imaging (DTI) of the macaque brain by using diffusion weighted (DW) readout-segmented echo planar imaging (rsEPI) with an optimized protocol at 7 T MRI. METHODS Three anesthetized macaques were included in this study. Under different scan settings, we compared the signal-to-noise ratio (SNR) and geometric distortion of DW images, implemented an optimized protocol for submillimeter-level DTI acquisition, and evaluated its performance. RESULTS The parallel-imaging-enabled (in GRAPPA mode) monopolar or monopolar+ diffusion scheme has higher SNR versus bipolar scheme, whereas trivial differences in SNR and image geometric distortion occurred when using increased readout segments with monopolar and monopolar+ that did not reach statistical significance. Submillimeter-level (0.8 mm isotropic) DTI data provide a sharper delineation of white matter contour than the 1 mm level. CONCLUSION The rsEPI technique with parallel imaging enabled, and with the shortest readout segments in conjunction with monopolar/monopolar+ diffusion encoding scheme, may be optimal for submillimeter-level diffusion imaging over macaque brains in vivo. SIGNIFICANCE rsEPI could effectively merit high-resolution DTI for in vivo macaque brain submillimeter structural architecture investigations at ultrahigh fields.
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