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Barisano G, Lynch KM, Sibilia F, Lan H, Shih NC, Sepehrband F, Choupan J. Imaging perivascular space structure and function using brain MRI. Neuroimage 2022; 257:119329. [PMID: 35609770 PMCID: PMC9233116 DOI: 10.1016/j.neuroimage.2022.119329] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/04/2022] [Accepted: 05/19/2022] [Indexed: 12/03/2022] Open
Abstract
In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.
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Affiliation(s)
- Giuseppe Barisano
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA.
| | - Kirsten M Lynch
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Francesca Sibilia
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Haoyu Lan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
| | - Nien-Chu Shih
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
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Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain. Neuroimage 2022; 255:119199. [PMID: 35417754 PMCID: PMC9195912 DOI: 10.1016/j.neuroimage.2022.119199] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 04/05/2022] [Accepted: 04/07/2022] [Indexed: 12/24/2022] Open
Abstract
Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 μm isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 μm isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 μm to 200 μm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.
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Cotter DL, Azad A, Cabeen RP, Kim MS, Geffner ME, Sepehrband F, Herting MM. White Matter Microstructural Differences in Youth With Classical Congenital Adrenal Hyperplasia. J Clin Endocrinol Metab 2021; 106:3196-3212. [PMID: 34272858 PMCID: PMC8530716 DOI: 10.1210/clinem/dgab520] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Gray matter morphology in the prefrontal cortex and subcortical regions, including the hippocampus and amygdala, are affected in youth with classical congenital adrenal hyperplasia (CAH). It remains unclear if white matter connecting these aforementioned brain regions is compromised in youth with CAH. OBJECTIVE To examine brain white matter microstructure in youth with CAH compared to controls. DESIGN A cross-sectional sample of 23 youths with CAH due to 21-hydroxylase deficiency (12.9 ± 3.5 year; 61% female) and 33 healthy controls (13.1 ± 2.8 year; 61% female) with 3T multishell diffusion-weighted magnetic resonance brain scans. MAIN OUTCOME MEASURES Complementary modeling approaches, including diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to examine in vivo white matter microstructure in six white matter tracts that innervate the prefrontal and subcortical regions. RESULTS DTI showed CAH youth had lower fractional anisotropy in both the fornix and stria terminalis and higher mean diffusivity in the fornix compared to controls. NODDI modeling revealed that CAH youth have a significantly higher orientation dispersion index in the stria terminalis compared to controls. White matter microstructural integrity was associated with smaller hippocampal and amygdala volumes in CAH youth. CONCLUSIONS These patterns of microstructure reflect less restricted water diffusion likely due to less coherency in oriented microstructure. These results suggest that white matter microstructural integrity in the fornix and stria terminalis is compromised and may be an additional related brain phenotype alongside affected hippocampus and amygdala neurocircuitry in individuals with CAH.
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Affiliation(s)
- Devyn L Cotter
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Anisa Azad
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mimi S Kim
- Center for Endocrinology, Diabetes, and Metabolism, and The Saban Research Institute at Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mitchell E Geffner
- Center for Endocrinology, Diabetes, and Metabolism, and The Saban Research Institute at Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Endocrinology, Diabetes, and Metabolism, and The Saban Research Institute at Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Microstructural properties within the amygdala and affiliated white matter tracts across adolescence. Neuroimage 2021; 243:118489. [PMID: 34450260 PMCID: PMC8574981 DOI: 10.1016/j.neuroimage.2021.118489] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 07/16/2021] [Accepted: 08/19/2021] [Indexed: 11/22/2022] Open
Abstract
The amygdala is a heterogenous set of nuclei with widespread cortical connections that continues to develop postnatally with vital implications for emotional regulation. Using high-resolution anatomical and multi-shell diffusion MRI in conjunction with novel amygdala segmentation, cutting-edge tractography, and Neurite Orientation Dispersion and Density (NODDI) methods, the goal of the current study was to characterize age associations with microstructural properties of amygdala subnuclei and amygdala-related white matter connections across adolescence (N = 61, 26 males; ages of 8-22 years). We found age-related increases in the Neurite Density Index (NDI) in the lateral nucleus (LA), dorsal and intermediate divisions of the basolateral nucleus (BLDI), and ventral division of the basolateral nucleus and paralaminar nucleus (BLVPL). Additionally, there were age-related increases in the NDI of the anterior commissure, ventral amygdalofugal pathway, cingulum, and uncinate fasciculus, with the strongest age associations in the frontal and temporal regions of these white matter tracts. This is the first study to utilize NODDI to show neurite density of basolateral amygdala subnuclei to relate to age across adolescence. Moreover, age-related differences were also notable in white matter microstructural properties along the anterior commissure and ventral amydalofugal tracts, suggesting increased bilateral amygdalae to diencephalon structural connectivity. As these basolateral regions and the ventral amygdalofugal pathways have been involved in associative emotional conditioning, future research is needed to determine if age-related and/or individual differences in the development of these microstructural properties link to socio-emotional functioning and/or risk for psychopathology.
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Lan H, Toga AW, Sepehrband F. Three-dimensional self-attention conditional GAN with spectral normalization for multimodal neuroimaging synthesis. Magn Reson Med 2021; 86:1718-1733. [PMID: 33961321 DOI: 10.1002/mrm.28819] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE To develop a new 3D generative adversarial network that is designed and optimized for the application of multimodal 3D neuroimaging synthesis. METHODS We present a 3D conditional generative adversarial network (GAN) that uses spectral normalization and feature matching to stabilize the training process and ensure optimization convergence (called SC-GAN). A self-attention module was also added to model the relationships between widely separated image voxels. The performance of the network was evaluated on the data set from ADNI-3, in which the proposed network was used to predict PET images, fractional anisotropy, and mean diffusivity maps from multimodal MRI. Then, SC-GAN was applied on a multidimensional diffusion MRI experiment for superresolution application. Experiment results were evaluated by normalized RMS error, peak SNR, and structural similarity. RESULTS In general, SC-GAN outperformed other state-of-the-art GAN networks including 3D conditional GAN in all three tasks across all evaluation metrics. Prediction error of the SC-GAN was 18%, 24% and 29% lower compared to 2D conditional GAN for fractional anisotropy, PET and mean diffusivity tasks, respectively. The ablation experiment showed that the major contributors to the improved performance of SC-GAN are the adversarial learning and the self-attention module, followed by the spectral normalization module. In the superresolution multidimensional diffusion experiment, SC-GAN provided superior predication in comparison to 3D Unet and 3D conditional GAN. CONCLUSION In this work, an efficient end-to-end framework for multimodal 3D medical image synthesis (SC-GAN) is presented. The source code is also made available at https://github.com/Haoyulance/SC-GAN.
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Affiliation(s)
- Haoyu Lan
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | | | - Arthur W Toga
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.,Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Farshid Sepehrband
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.,Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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Abstract
Magnetic resonance (MR) imaging is a crucial tool for evaluation of the skull base, enabling characterization of complex anatomy by utilizing multiple image contrasts. Recent technical MR advances have greatly enhanced radiologists' capability to diagnose skull base pathology and help direct management. In this paper, we will summarize cutting-edge clinical and emerging research MR techniques for the skull base, including high-resolution, phase-contrast, diffusion, perfusion, vascular, zero echo-time, elastography, spectroscopy, chemical exchange saturation transfer, PET/MR, ultra-high-field, and 3D visualization. For each imaging technique, we provide a high-level summary of underlying technical principles accompanied by relevant literature review and clinical imaging examples.
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Affiliation(s)
- Claudia F Kirsch
- Division Chief, Neuroradiology, Professor of Neuroradiology and Otolaryngology, Department of Radiology, Northwell Health, Zucker Hofstra School of Medicine at Northwell, North Shore University Hospital, Manhasset, NY
| | - Mai-Lan Ho
- Associate Professor of Radiology, Director of Research, Department of Radiology, Director, Advanced Neuroimaging Core, Chair, Asian Pacific American Network, Secretary, Association for Staff and Faculty Women, Nationwide Children's Hospital and The Ohio State University, Columbus, OH; Division Chief, Neuroradiology, Professor of Neuroradiology and Otolaryngology, Department of Radiology, Northwell Health, Zucker Hofstra School of Medicine at Northwell, North Shore University Hospital, Manhasset, NY.
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Bienkowski MS, Sepehrband F, Kurniawan ND, Stanis J, Korobkova L, Khanjani N, Clark K, Hintiryan H, Miller CA, Dong HW. Homologous laminar organization of the mouse and human subiculum. Sci Rep 2021; 11:3729. [PMID: 33580088 PMCID: PMC7881248 DOI: 10.1038/s41598-021-81362-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 08/10/2020] [Indexed: 11/09/2022] Open
Abstract
The subiculum is the major output component of the hippocampal formation and one of the major brain structures most affected by Alzheimer's disease. Our previous work revealed a hidden laminar architecture within the mouse subiculum. However, the rotation of the hippocampal longitudinal axis across species makes it unclear how the laminar organization is represented in human subiculum. Using in situ hybridization data from the Allen Human Brain Atlas, we demonstrate that the human subiculum also contains complementary laminar gene expression patterns similar to the mouse. In addition, we provide evidence that the molecular domain boundaries in human subiculum correspond to microstructural differences observed in high resolution MRI and fiber density imaging. Finally, we show both similarities and differences in the gene expression profile of subiculum pyramidal cells within homologous lamina. Overall, we present a new 3D model of the anatomical organization of human subiculum and its evolution from the mouse.
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Affiliation(s)
- Michael S Bienkowski
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA. .,Zilkha Neurogenetic Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA.
| | - Farshid Sepehrband
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA.,Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Nyoman D Kurniawan
- Center for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Jim Stanis
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Laura Korobkova
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Neda Khanjani
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Kristi Clark
- Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Houri Hintiryan
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA.,Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Carol A Miller
- Department of Pathology, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA
| | - Hong-Wei Dong
- USC Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging (LONI), Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA. .,Zilkha Neurogenetic Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA. .,Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA. .,Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
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Barisano G, Law M, Custer RM, Toga AW, Sepehrband F. Perivascular Space Imaging at Ultrahigh Field MR Imaging. Magn Reson Imaging Clin N Am 2020; 29:67-75. [PMID: 33237016 DOI: 10.1016/j.mric.2020.09.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The recent Food and Drug Administration approval of 7 T MR imaging scanners for clinical use has introduced the possibility to study the brain not only in physiologic but also in pathologic conditions at ultrahigh field (UHF). Because UHF MR imaging offers higher signal-to-noise ratio and spatial resolution compared with lower field clinical scanners, the benefits of UHF MR imaging are particularly evident for imaging small anatomic structures, such as the cerebral perivascular spaces (PVS). In this article, the authors describe the application of UHF MR imaging for the investigation of PVS.
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Affiliation(s)
- Giuseppe Barisano
- Neuroscience Graduate Program, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA.
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, The Alfred Health, Level 6, 99 Commercial Road, Melbourne, Victoria 3004, Australia
| | - Rachel M Custer
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
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Sepehrband F, Cabeen RP, Choupan J, Barisano G, Law M, Toga AW. Perivascular space fluid contributes to diffusion tensor imaging changes in white matter. Neuroimage 2019; 197:243-254. [PMID: 31051291 DOI: 10.1016/j.neuroimage.2019.04.070] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/16/2019] [Accepted: 04/26/2019] [Indexed: 10/26/2022] Open
Abstract
Diffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from non-parenchymal fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.
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Affiliation(s)
- Farshid Sepehrband
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA.
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Department of Psychology, University of Southern California, Los Angeles, USA
| | - Giuseppe Barisano
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, USA
| | - Meng Law
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Radiology and Nuclear Medicine, Alfred Health, Melbourne, Australia
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
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Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:348-354. [PMID: 31049392 PMCID: PMC6479267 DOI: 10.1016/j.dadm.2019.03.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction Although increased mean diffusivity of the white matter has been repeatedly linked to Alzheimer’s disease pathology, the underlying mechanism is not known. Methods Here, we used ADNI-3 multishell diffusion magnetic resonance imaging data to separate the diffusion signal of the parenchyma from less hindered fluid pools within the white matter such as perivascular space fluid and fluid-filled cavities. Results We found that the source of the pathological increase of the mean diffusivity is the increased nonparenchymal fluid, often found in lacunes and perivascular spaces. In this cohort, the cognitive decline was significantly associated with the fluid increase and not with the microstructural changes of the white matter parenchyma itself. The white matter fluid increase was dominantly observed in the sagittal stratum and anterior thalamic radiation. Discussion These findings are positive steps toward understanding the pathophysiology of white matter alteration and its role in the cognitive decline.
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11
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Wang N, Zhang J, Cofer G, Qi Y, Anderson RJ, White LE, Allan Johnson G. Neurite orientation dispersion and density imaging of mouse brain microstructure. Brain Struct Funct 2019; 224:1797-1813. [PMID: 31006072 DOI: 10.1007/s00429-019-01877-x] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 04/11/2019] [Indexed: 12/14/2022]
Abstract
Advanced biophysical models like neurite orientation dispersion and density imaging (NODDI) have been developed to estimate the microstructural complexity of voxels enriched in dendrites and axons for both in vivo and ex vivo studies. NODDI metrics derived from high spatial and angular resolution diffusion MRI using the fixed mouse brain as a reference template have not yet been reported due in part to the extremely long scan time required. In this study, we modified the three-dimensional diffusion-weighted spin-echo pulse sequence for multi-shell and undersampling acquisition to reduce the scan time. This allowed us to acquire several exhaustive datasets that would otherwise not be attainable. NODDI metrics were derived from a complex 8-shell diffusion (1000-8000 s/mm2) dataset with 384 diffusion gradient-encoding directions at 50 µm isotropic resolution. These provided a foundation for exploration of tradeoffs among acquisition parameters. A three-shell acquisition strategy covering low, medium, and high b values with at least angular resolution of 64 is essential for ex vivo NODDI experiments. The good agreement between neurite density index (NDI) and the orientation dispersion index (ODI) with the subsequent histochemical analysis of myelin and neuronal density highlights that NODDI could provide new insight into the microstructure of the brain. Furthermore, we found that NDI is sensitive to microstructural variations in the corpus callosum using a well-established demyelination cuprizone model. The study lays the ground work for developing protocols for routine use of high-resolution NODDI method in characterizing brain microstructure in mouse models.
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Affiliation(s)
- Nian Wang
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA.
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA.
| | - Jieying Zhang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Gary Cofer
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Yi Qi
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Robert J Anderson
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Leonard E White
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - G Allan Johnson
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA.
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
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12
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Cao Y, Zhang Y, Wang Y, Liu W, Han D. Improved stimulated echo in diffusion magnetic resonance imaging: introducing a π pulse for SNR enhancement. Magn Reson Med 2019; 81:2905-2914. [PMID: 30693971 DOI: 10.1002/mrm.27653] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Revised: 12/11/2018] [Accepted: 12/12/2018] [Indexed: 12/22/2022]
Abstract
PURPOSE Anomalous diffusion in biological tissues can be examined by diffusion MRI for various applications, including tumor diagnosis and measurement of brain fiber pathways. However, the measurement of anomalous diffusion requires high b-values for the diffusion gradient in MRI, and current MRI methods cannot provide a high SNR. This study aimed to improve on the standard stimulated echo (STE) to enhance the SNR in diffusion MRI with high b-values. METHODS Because of hardware limitations and human safety considerations, prolonging the diffusion time (Δ) is 1 of the few methods available to realize high b-values. Here, we propose a new echo mechanism for diffusion MRI to enhance SNRs under long Δ. By introducing a π pulse at the midpoint between 2nd and 3rd π/2 pulses of STE, we refocus the magnetic moment vectors in the longitudinal plane before the third π/2 pulse is applied, which preserves the full echo signals. This sequence was compared with STE and spin echo (SE). Nine Δs were tested in a phantom. Multi b-values with 2 Δs were tested in a mouse liver, brain, and tumor. RESULTS Compared with STE and SE, the proposed improved STE (ISTE) exhibited an improved SNR in the phantom experiment and improved performance in the in vivo experiments. CONCLUSION By using the proposed echo mechanism in diffusion MRI, we enhanced the SNR of the images, which enables us to investigate diffusion behavior at higher b-values and further facilitates the development of quantitative diffusion MRI and radiomics.
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Affiliation(s)
- Yupeng Cao
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China.,School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Yan Zhang
- State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China
| | - Yuqing Wang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Wentao Liu
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Dong Han
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China.,School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
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Filipiak P, Fick R, Petiet A, Santin M, Philippe AC, Lehericy S, Ciuciu P, Deriche R, Wassermann D. Reducing the number of samples in spatiotemporal dMRI acquisition design. Magn Reson Med 2018; 81:3218-3233. [DOI: 10.1002/mrm.27601] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 10/17/2018] [Accepted: 10/18/2018] [Indexed: 12/21/2022]
Affiliation(s)
- Patryk Filipiak
- Université Côte d'Azur-Inria Sophia Antipolis-Méditerranée; France
| | - Rutger Fick
- Université Côte d'Azur-Inria Sophia Antipolis-Méditerranée; France
| | - Alexandra Petiet
- CENIR-Center for NeuroImaging Research, ICM-Brain and Spine Institute; Paris France
| | - Mathieu Santin
- CENIR-Center for NeuroImaging Research, ICM-Brain and Spine Institute; Paris France
| | | | - Stephane Lehericy
- CENIR-Center for NeuroImaging Research, ICM-Brain and Spine Institute; Paris France
| | | | - Rachid Deriche
- Université Côte d'Azur-Inria Sophia Antipolis-Méditerranée; France
| | - Demian Wassermann
- Université Côte d'Azur-Inria Sophia Antipolis-Méditerranée; France
- Inria, CEA, Université Paris-Saclay; France
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Barisano G, Sepehrband F, Ma S, Jann K, Cabeen R, Wang DJ, Toga AW, Law M. Clinical 7 T MRI: Are we there yet? A review about magnetic resonance imaging at ultra-high field. Br J Radiol 2018; 92:20180492. [PMID: 30359093 DOI: 10.1259/bjr.20180492] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
In recent years, ultra-high field MRI (7 T and above) has received more interest for clinical imaging. Indeed, a number of studies have shown the benefits from the application of this powerful tool not only for research purposes, but also in realms of improved diagnostics and patient management. The increased signal-to-noise ratio and higher spatial resolution compared with conventional and high-field clinical scanners allow imaging of small anatomical detail and subtle pathological findings. Furthermore, greater spectral resolution achieved at ultra-high field allows the resolution of metabolites for MR spectroscopic imaging. All these advantages have a significant impact on many neurological diseases, including multiple sclerosis, cerebrovascular disease, brain tumors, epilepsy and neurodegenerative diseases, in part because the pathology can be subtle and lesions small in these diseases, therefore having higher signal and resolution will help lesion detection. In this review, we discuss the main clinical neurological applications and some technical challenges which remain with ultra-high field MRI.
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Affiliation(s)
- Giuseppe Barisano
- 1 Department of Radiology, Keck Medical Center of University of Southern California , Los Angeles, CA , USA.,2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Farshid Sepehrband
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Samantha Ma
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Kay Jann
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Ryan Cabeen
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Danny J Wang
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Arthur W Toga
- 2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
| | - Meng Law
- 1 Department of Radiology, Keck Medical Center of University of Southern California , Los Angeles, CA , USA.,2 Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA , USA
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