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Julian A, Ruthotto L. PyHySCO: GPU-enabled susceptibility artifact distortion correction in seconds. Front Neurosci 2024; 18:1406821. [PMID: 38863882 PMCID: PMC11165994 DOI: 10.3389/fnins.2024.1406821] [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: 03/25/2024] [Accepted: 04/25/2024] [Indexed: 06/13/2024] Open
Abstract
Over the past decade, reversed gradient polarity (RGP) methods have become a popular approach for correcting susceptibility artifacts in echo-planar imaging (EPI). Although several post-processing tools for RGP are available, their implementations do not fully leverage recent hardware, algorithmic, and computational advances, leading to correction times of several minutes per image volume. To enable 3D RGP correction in seconds, we introduce PyTorch Hyperelastic Susceptibility Correction (PyHySCO), a user-friendly EPI distortion correction tool implemented in PyTorch that enables multi-threading and efficient use of graphics processing units (GPUs). PyHySCO uses a time-tested physical distortion model and mathematical formulation and is, therefore, reliable without training. An algorithmic improvement in PyHySCO is its use of the one-dimensional distortion correction method by Chang and Fitzpatrick to initialize the non-linear optimization. PyHySCO is published under the GNU public license and can be used from the command line or its Python interface. Our extensive numerical validation using 3T and 7T data from the Human Connectome Project suggests that PyHySCO can achieve accuracy comparable to that of leading RGP tools at a fraction of the cost. We also validate the new initialization scheme, compare different optimization algorithms, and test the algorithm on different hardware and arithmetic precisions.
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Affiliation(s)
- Abigail Julian
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Lars Ruthotto
- Department of Computer Science, Emory University, Atlanta, GA, United States
- Department of Mathematics, Emory University, Atlanta, GA, United States
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2
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Han G, Jiao B, Zhang Y, Wang Z, Liang C, Li Y, Hsu YC, Bai R. Arterial pulsation dependence of perivascular cerebrospinal fluid flow measured by dynamic diffusion tensor imaging in the human brain. Neuroimage 2024:120653. [PMID: 38795798 DOI: 10.1016/j.neuroimage.2024.120653] [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: 03/13/2024] [Revised: 05/14/2024] [Accepted: 05/23/2024] [Indexed: 05/28/2024] Open
Abstract
Perivascular cerebrospinal fluid (pCSF) flow is a key component of the glymphatic system. Arterial pulsation has been proposed as the main driving force of pCSF influx along the superficial and penetrating arteries; however, evidence of this mechanism in humans is limited. We proposed an experimental framework of dynamic diffusion tensor imaging with low b-values and ultra-long echo time (dynDTIlow-b) to capture pCSF flow properties during the cardiac cycle in human brains. Healthy adult volunteers (aged 17-28 years; seven men, one woman) underwent dynDTIlow-b using a clinical 3T scanner (MAGNETOM Prisma, Siemens Healthcare, Erlangen, Germany) with simultaneously recorded cardiac output. The results showed that diffusion tensors reconstructed from pCSF were mainly oriented in the direction of the neighboring arterial flow. When switching from vasoconstriction to vasodilation, the axial and radial diffusivities of the pCSF increased by 5.7% and 4.94%, respectively, suggesting that arterial pulsation alters the pCSF flow both parallel and perpendicular to the arterial wall. DynDTIlow-b signal intensity at b=0 s/mm2 (i.e., T2-weighted, [S(b=0 s/mm2)]) decreased in systole, but this change was ∼7.5% of a cardiac cycle slower than the changes in apparent diffusivity, suggesting that changes in S(b=0 s/mm2) and apparent diffusivity arise from distinct physiological processes and potential biomarkers associated with perivascular space volume and pCSF flow, respectively. Additionally, the mean diffusivities of white matter showed cardiac-cycle dependencies similar to pCSF, although a delay relative to the peak time of S(b=0 s/mm2) was present, suggesting that dynDTIlow-b could potentially reveal the dynamics of magnetic resonance imaging-invisible pCSF surrounding small arteries and arterioles in white matter; this delay may result from pulse wave propagation along penetrating arteries. In conclusion, the vasodilation-induced increases in axial and radial diffusivities of pCSF and mean diffusivities of white matter are consistent with the notion that arterial pulsation can accelerate pCSF flow in human brain. Furthermore, the proposed dynDTIlow-b technique can capture various pCSF dynamics in artery pulsation.
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Affiliation(s)
- Guangxu Han
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China; Nanhu Brain-computer Interface Institute, Hangzhou, 311100, China; Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, China
| | - Bingjie Jiao
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China; Lingang Laboratory, Shanghai, 200031, China; Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, China
| | - Yifan Zhang
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zejun Wang
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Chunjing Liang
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yong Li
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yi-Cheng Hsu
- MR Research Collaboration Team, Siemens Healthineers Ltd., Shanghai, China
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China.
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3
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Schilling KG, Combes AJE, Ramadass K, Rheault F, Sweeney G, Prock L, Sriram S, Cohen-Adad J, Gore JC, Landman BA, Smith SA, O'Grady KP. Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord. Magn Reson Imaging 2024; 108:11-21. [PMID: 38309376 DOI: 10.1016/j.mri.2024.01.008] [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: 09/25/2023] [Revised: 01/04/2024] [Accepted: 01/14/2024] [Indexed: 02/05/2024]
Abstract
Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Anna J E Combes
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Francois Rheault
- Medical Imaging and Neuroinformatic (MINi) Lab, Department of Computer Science, University of Sherbrooke, Canada
| | - Grace Sweeney
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Logan Prock
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Subramaniam Sriram
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada; Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Seth A Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kristin P O'Grady
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
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Johnson JTE, Irfanoglu MO, Manninen E, Ross TJ, Yang Y, Laun FB, Martin J, Topgaard D, Benjamini D. In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI. Hum Brain Mapp 2024; 45:e26697. [PMID: 38726888 PMCID: PMC11082920 DOI: 10.1002/hbm.26697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/28/2024] [Accepted: 04/12/2024] [Indexed: 05/13/2024] Open
Abstract
Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency,ω $$ \omega $$ , in addition to the diffusion tensor,D $$ \mathbf{D} $$ , and relaxation,R 1 $$ {R}_1 $$ ,R 2 $$ {R}_2 $$ , correlations. AD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on theirD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.
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Affiliation(s)
- Jessica T. E. Johnson
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
| | - M. Okan Irfanoglu
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of HealthBethesdaMarylandUSA
| | - Eppu Manninen
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of HealthBaltimoreMarylandUSA
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of HealthBaltimoreMarylandUSA
| | - Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Jan Martin
- Department of ChemistryLund UniversityLundSweden
| | | | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
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Magondo N, Meintjes EM, Warton FL, Little F, van der Kouwe AJW, Laughton B, Jankiewicz M, Holmes MJ. Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected. Sci Rep 2024; 14:8822. [PMID: 38627570 PMCID: PMC11021525 DOI: 10.1038/s41598-024-58339-6] [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: 07/11/2023] [Accepted: 03/27/2024] [Indexed: 04/19/2024] Open
Abstract
HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to HIV uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.
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Affiliation(s)
- Ndivhuwo Magondo
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Ernesta M Meintjes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa.
| | - Fleur L Warton
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andre J W van der Kouwe
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MI, USA
| | - Barbara Laughton
- Department of Paediatrics and Child Health and Tygerberg Children's Hospital, Faculty of Medicine and Health Sciences, Family Centre for Research with Ubuntu, Stellenbosch University, Stellenbosch, South Africa
| | - Marcin Jankiewicz
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
- ImageTech, Simon Fraser University, Surrey, BC, Canada
| | - Martha J Holmes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
- ImageTech, Simon Fraser University, Surrey, BC, Canada
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6
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Ciceri T, De Luca A, Agarwal N, Arrigoni F, Peruzzo D. A framework for optimizing the acquisition protocol multishell diffusion-weighted imaging for multimodel assessment. NMR IN BIOMEDICINE 2024:e5141. [PMID: 38520215 DOI: 10.1002/nbm.5141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/22/2023] [Accepted: 02/15/2024] [Indexed: 03/25/2024]
Abstract
Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2 = 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.
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Affiliation(s)
- Tommaso Ciceri
- Neuroimaging Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Alberto De Luca
- Image Sciences Institute, Division Imaging and Oncology, UMC Utrecht, Utrecht, The Netherlands
- Neurology Department, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, The Netherlands
| | - Nivedita Agarwal
- Diagnostic Imaging and Neuroradiology Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Filippo Arrigoni
- Pediatric Radiology and Neuroradiology Department, V. Buzzi Children's Hospital, Milan, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
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Zhang Y, Shen SX, Bibic A, Wang X. Evolutionary continuity and divergence of auditory dorsal and ventral pathways in primates revealed by ultra-high field diffusion MRI. Proc Natl Acad Sci U S A 2024; 121:e2313831121. [PMID: 38377216 PMCID: PMC10907247 DOI: 10.1073/pnas.2313831121] [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: 08/10/2023] [Accepted: 01/22/2024] [Indexed: 02/22/2024] Open
Abstract
Auditory dorsal and ventral pathways in the human brain play important roles in supporting speech and language processing. However, the evolutionary root of the dual auditory pathways in the primate brain is unclear. By parcellating the auditory cortex of marmosets (a New World monkey species), macaques (an Old World monkey species), and humans using the same individual-based analysis method and tracking the pathways from the auditory cortex based on multi-shell diffusion-weighted MRI (dMRI), homologous auditory dorsal and ventral fiber tracks were identified in these primate species. The ventral pathway was found to be well conserved in all three primate species analyzed but extend to more anterior temporal regions in humans. In contrast, the dorsal pathway showed a divergence between monkey and human brains. First, frontal regions in the human brain have stronger connections to the higher-level auditory regions than to the lower-level auditory regions along the dorsal pathway, while frontal regions in the monkey brain show opposite connection patterns along the dorsal pathway. Second, the left lateralization of the dorsal pathway is only found in humans. Moreover, the connectivity strength of the dorsal pathway in marmosets is more similar to that of humans than macaques. These results demonstrate the continuity and divergence of the dual auditory pathways in the primate brains along the evolutionary path, suggesting that the putative neural networks supporting human speech and language processing might have emerged early in primate evolution.
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Affiliation(s)
- Yang Zhang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
| | - Sherry Xinyi Shen
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
| | - Adnan Bibic
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD21205
- Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, F. M. Kirby Center, Baltimore, MD21205
| | - Xiaoqin Wang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
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8
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Wade RG, Tam W, Perumal A, Pepple S, Griffiths TT, Flather R, Haroon HA, Shelley D, Plein S, Bourke G, Teh I. Comparison of distortion correction preprocessing pipelines for DTI in the upper limb. Magn Reson Med 2024; 91:773-783. [PMID: 37831659 PMCID: PMC10952179 DOI: 10.1002/mrm.29881] [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: 04/08/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 10/15/2023]
Abstract
PURPOSE DTI characterizes tissue microstructure and provides proxy measures of nerve health. Echo-planar imaging is a popular method of acquiring DTI but is susceptible to various artifacts (e.g., susceptibility, motion, and eddy currents), which may be ameliorated via preprocessing. There are many pipelines available but limited data comparing their performance, which provides the rationale for this study. METHODS DTI was acquired from the upper limb of heathy volunteers at 3T in blip-up and blip-down directions. Data were independently corrected using (i) FSL's TOPUP & eddy, (ii) FSL's TOPUP, (iii) DSI Studio, and (iv) TORTOISE. DTI metrics were extracted from the median, radial, and ulnar nerves and compared (between pipelines) using mixed-effects linear regression. The geometric similarity of corrected b = 0 images and the slice matched T1-weighted (T1w) images were computed using the Sörenson-Dice coefficient. RESULTS Without preprocessing, the similarity coefficient of the blip-up and blip-down datasets to the T1w was 0·80 and 0·79, respectively. Preprocessing improved the geometric similarity by 1% with no difference between pipelines. Compared to TOPUP & eddy, DSI Studio and TORTOISE generated 2% and 6% lower estimates of fractional anisotropy, and 6% and 13% higher estimates of radial diffusivity, respectively. Estimates of anisotropy from TOPUP & eddy versus TOPUP were not different but TOPUP reduced radial diffusivity by 3%. The agreement of DTI metrics between pipelines was poor. CONCLUSIONS Preprocessing DTI from the upper limb improves geometric similarity but the choice of the pipeline introduces clinically important variability in diffusion parameter estimates from peripheral nerves.
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Affiliation(s)
- Ryckie G. Wade
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
- Department of Plastic, Reconstructive and Hand SurgeryLeeds Teaching Hospitals TrustLeedsUK
| | - Winnie Tam
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
| | - Antonia Perumal
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
| | - Sophanit Pepple
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
| | - Timothy T. Griffiths
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
- Department of Plastic, Reconstructive and Hand SurgeryLeeds Teaching Hospitals TrustLeedsUK
| | - Robert Flather
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
- Department of Plastic, Reconstructive and Hand SurgeryLeeds Teaching Hospitals TrustLeedsUK
| | - Hamied A. Haroon
- Division of Psychology, Communication & Human NeuroscienceThe University of ManchesterManchesterUK
| | | | - Sven Plein
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of LeedsLeedsUK
| | - Grainne Bourke
- Leeds Institute for Medical Research, University of Leeds
LeedsUK
- Department of Plastic, Reconstructive and Hand SurgeryLeeds Teaching Hospitals TrustLeedsUK
| | - Irvin Teh
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of LeedsLeedsUK
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9
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Hendrikse C, Lückhoff HK, Fouché JP, van den Heuvel LL, Emsley R, Seedat S, du Plessis S. Fronto-limbic white matter microstructural changes in psychiatrically healthy adults with childhood trauma. J Neurosci Res 2024; 102:e25308. [PMID: 38361421 DOI: 10.1002/jnr.25308] [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: 08/24/2023] [Revised: 01/19/2024] [Accepted: 01/31/2024] [Indexed: 02/17/2024]
Abstract
Childhood trauma (CT) may influence brain white matter microstructure; however, few studies have examined the differential impact of distinct CT types on white matter microstructure in psychiatrically healthy adults living in a developing country. In adults without significant medical or psychiatric disorders, we investigated the association(s) between CT, including abuse and neglect, and fractional anisotropy (FA) of limbic tracts previously shown to be associated with CT. Participants underwent diffusion tensor imaging and completed the Childhood Trauma Questionnaire. Multivariate analysis of variance models were used to test the effects of total overall CT, as well as CT subtypes, on FA in six fronto-limbic tracts, adjusting for age, sex, and educational level. The final sample included 69 adults (age 47 ± 17 years; 70% female). Overall, CT had a significant main effect on FA for tracts of interest (p < .001). Greater CT severity was associated with lower FA for the bilateral and left stria terminalis (uncorrected) as well as the bilateral, left, and right anterior limb of the internal capsule (ALIC; corrected). Exposure to total non-violent/deprivational trauma specifically was associated with lower FA of the bilateral, left, and right ALIC, suggesting that distinct types of CT are associated with differential white matter changes in apparently healthy adults. The ALIC predominantly carries fibers connecting the thalamus with prefrontal cortical regions. Microstructural alterations in the ALIC may be associated with functional brain changes, which may be adaptive or increase the risk of accelerated age-related cognitive decline, maladaptive behaviors, and subsyndromal psychiatric symptoms.
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Affiliation(s)
- Chanellé Hendrikse
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | | | - Jean-Paul Fouché
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Genomics of Brain Disorders Research Unit, South African Medical Research Council/Stellenbosch University, Cape Town, South Africa
| | - Leigh L van den Heuvel
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Genomics of Brain Disorders Research Unit, South African Medical Research Council/Stellenbosch University, Cape Town, South Africa
| | - Robin Emsley
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Genomics of Brain Disorders Research Unit, South African Medical Research Council/Stellenbosch University, Cape Town, South Africa
| | - Stefan du Plessis
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Genomics of Brain Disorders Research Unit, South African Medical Research Council/Stellenbosch University, Cape Town, South Africa
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10
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Travers BG, Surgent O, Guerrero-Gonzalez J, Dean DC, Adluru N, Kecskemeti SR, Kirk GR, Alexander AL, Zhu J, Skaletski EC, Naik S, Duran M. Role of autonomic, nociceptive, and limbic brainstem nuclei in core autism features. Autism Res 2024; 17:266-279. [PMID: 38278763 PMCID: PMC10922575 DOI: 10.1002/aur.3096] [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: 10/20/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024]
Abstract
Although multiple theories have speculated about the brainstem reticular formation's involvement in autistic behaviors, the in vivo imaging of brainstem nuclei needed to test these theories has proven technologically challenging. Using methods to improve brainstem imaging in children, this study set out to elucidate the role of the autonomic, nociceptive, and limbic brainstem nuclei in the autism features of 145 children (74 autistic children, 6.0-10.9 years). Participants completed an assessment of core autism features and diffusion- and T1-weighted imaging optimized to improve brainstem images. After data reduction via principal component analysis, correlational analyses examined associations among autism features and the microstructural properties of brainstem clusters. Independent replication was performed in 43 adolescents (24 autistic, 13.0-17.9 years). We found specific nuclei, most robustly the parvicellular reticular formation-alpha (PCRtA) and to a lesser degree the lateral parabrachial nucleus (LPB) and ventral tegmental parabrachial pigmented complex (VTA-PBP), to be associated with autism features. The PCRtA and some of the LPB associations were independently found in the replication sample, but the VTA-PBP associations were not. Consistent with theoretical perspectives, the findings suggest that individual differences in pontine reticular formation nuclei contribute to the prominence of autistic features. Specifically, the PCRtA, a nucleus involved in mastication, digestion, and cardio-respiration in animal models, was associated with social communication in children, while the LPB, a pain-network nucleus, was associated with repetitive behaviors. These findings highlight the contributions of key autonomic brainstem nuclei to the expression of core autism features.
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Affiliation(s)
- Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Kinesiology, Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Jun Zhu
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Emily C. Skaletski
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Kinesiology, Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Sonali Naik
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Monica Duran
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
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11
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Hafiz R, Irfanoglu MO, Nayak A, Pierpaoli C. "Pscore": A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics. J Magn Reson Imaging 2024. [PMID: 38291798 DOI: 10.1002/jmri.29248] [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: 12/06/2023] [Revised: 01/08/2024] [Accepted: 01/09/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Quantitative magnetic resonance imaging (MRI) metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed. PURPOSE To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, "Pscore" to address this issue. STUDY TYPE Retrospective cohort. POPULATION Nine hundred and sixty-one healthy young adults (age: 22-35 years, females: 53%) from the Human Connectome Project. FIELD STRENGTH/SEQUENCE 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE. ASSESSMENT The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate "Pscores"-which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values. STATISTICAL TESTS ROI-wise distributions were assessed using log transformations, Zscore, and the "Pscore" methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV>95 (%), PEV<5 (%)) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (N = 100) using 100 iterations. RESULTS The dMRI metric distributions were systematically non-Gaussian, including positively skewed (eg, mean and radial diffusivity) and negatively skewed (eg, fractional and propagator anisotropy) metrics. This resulted in unbalanced tails in Zscore distributions (PEV>95 ≠ 5%, PEV<5 ≠ 5%) whereas "Pscore" distributions were symmetric and balanced (PEV>95 = PEV<5 = 5%); even for small bootstrapped samples (averagePEV > 95 ¯ = PEV < 5 ¯ = 5 ± 0 % $$ \overline{{\mathrm{PEV}}_{>95}}=\overline{{\mathrm{PEV}}_{<5}}=5\pm 0\% $$ [SD]). DATA CONCLUSION The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed "Pscore" method may help estimating individual deviations more accurately in skewed normative data, even from small datasets. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rakibul Hafiz
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
| | - M Okan Irfanoglu
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
| | - Amritha Nayak
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
- Military Traumatic Brain Injury Initiative (MTBI2-formerly known as the Center for Neuroscience and Regenerative Medicine [CNRM]), Bethesda, Maryland, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Carlo Pierpaoli
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
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12
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Magondo N, Meintjes EM, Warton FL, Little F, van der Kouwe AJ, Laughton B, Jankiewicz M, Holmes MJ. Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575169. [PMID: 38260347 PMCID: PMC10802593 DOI: 10.1101/2024.01.11.575169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.
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Affiliation(s)
- Ndivhuwo Magondo
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ernesta M. Meintjes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Fleur L. Warton
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andre J.W. van der Kouwe
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA,USA
- Department of Radiology, Harvard Medical School, Boston, MI, USA
| | - Barbara Laughton
- Family Centre for Research with Ubuntu, Department of Paediatrics and Child Health and Tygerberg Children’s Hospital, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch,South Africa
| | - Marcin Jankiewicz
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
- ImageTech, Simon Fraser University, Surrey, BC, Canada
| | - Martha J. Holmes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
- ImageTech, Simon Fraser University, Surrey, BC, Canada
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13
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Singh K, Barsoum S, Schilling KG, An Y, Ferrucci L, Benjamini D. Neuronal microstructural changes in the human brain are associated with neurocognitive aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575206. [PMID: 38260525 PMCID: PMC10802615 DOI: 10.1101/2024.01.11.575206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
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Affiliation(s)
- Kavita Singh
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yang An
- Brain Aging and Behavior Section, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
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14
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Hafiz R, Irfanoglu MO, Nayak A, Pierpaoli C. 'Pscore' - A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.10.571016. [PMID: 38105995 PMCID: PMC10723480 DOI: 10.1101/2023.12.10.571016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
BACKGROUND Quantitative MRI metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed. PURPOSE To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, 'Pscore' to address this issue. STUDY TYPE Retrospective cohort. POPULATION 961 healthy young-adults (age:22-35 years, Females:53%) from the Human Connectome Project. FIELD STRENGTH/SEQUENCE 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE. ASSESSMENT The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU-atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate 'Pscores'- which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values. STATISTICAL TESTS ROI-wise distributions were assessed using Log transformations, Zscore, and the 'Pscore' methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV < 5 ( % ) ,PEV < 5 ( % ) ) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (n=100) using 100 iterations. RESULTS The dMRI metric distributions were systematically non-Gaussian, including positively skewed (e.g., mean and radial distributions P E V > 95 ≠ 5 % , P E V < 5 ≠ 5 % whereas 'Pscore' distributions were symmetric and balanced P E V > 95 = P E V < 5 = 5 % ; even for small bootstrapped samples (average P E V > 95 ¯ = P E V < 5 ¯ = 5 ± 0 % S D ). DATA CONCLUSION The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed 'Pscore' method may help estimating individual deviations more accurately in skewed normative data, even from small datasets.
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Affiliation(s)
- Rakibul Hafiz
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
| | - M. Okan Irfanoglu
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
| | - Amritha Nayak
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
- Military Traumatic Brain Injury Initiative (MTBI2 – formerly known as the Center for Neuroscience and Regenerative Medicine [CNRM]) Bethesda, MD
- The Henry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Carlo Pierpaoli
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
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15
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Zaid Alkilani A, Çukur T, Saritas EU. FD-Net: An unsupervised deep forward-distortion model for susceptibility artifact correction in EPI. Magn Reson Med 2024; 91:280-296. [PMID: 37811681 DOI: 10.1002/mrm.29851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/18/2023] [Accepted: 08/15/2023] [Indexed: 10/10/2023]
Abstract
PURPOSE To introduce an unsupervised deep-learning method for fast and effective correction of susceptibility artifacts in reversed phase-encode (PE) image pairs acquired with echo planar imaging (EPI). METHODS Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, neglecting consistency to the acquired EPI images. This work introduces a novel unsupervised deep Forward-Distortion Network (FD-Net) that predicts both the susceptibility-induced displacement field and the underlying anatomically correct image. Unlike previous methods, FD-Net enforces the forward-distortions of the correct image in both PE directions to be consistent with the acquired reversed-PE image pair. FD-Net further leverages a multiresolution architecture to maintain high local and global performance. RESULTS FD-Net performs competitively with a gold-standard reference method (TOPUP) in image quality, while enabling a leap in computational efficiency. Furthermore, FD-Net outperforms recent unwarping-based methods for unsupervised correction in terms of both image and field quality. CONCLUSION The unsupervised FD-Net method introduces a deep forward-distortion approach to enable fast, high-fidelity correction of susceptibility artifacts in EPI by maintaining consistency to measured data. Therefore, it holds great promise for improving the anatomical accuracy of EPI imaging.
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Affiliation(s)
- Abdallah Zaid Alkilani
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
| | - Tolga Çukur
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
- Neuroscience Graduate Program, Bilkent University, Ankara, Turkey
| | - Emine Ulku Saritas
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
- Neuroscience Graduate Program, Bilkent University, Ankara, Turkey
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16
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Withers CP, Diamond JM, Yang B, Snyder K, Abdollahi S, Sarlls J, Chapeton JI, Theodore WH, Zaghloul KA, Inati SK. Identifying sources of human interictal discharges with travelling wave and white matter propagation. Brain 2023; 146:5168-5181. [PMID: 37527460 PMCID: PMC11046055 DOI: 10.1093/brain/awad259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/30/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023] Open
Abstract
Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.
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Affiliation(s)
- C Price Withers
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joshua M Diamond
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Braden Yang
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kathryn Snyder
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shervin Abdollahi
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joelle Sarlls
- NIH MRI Research Facility, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio I Chapeton
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - William H Theodore
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sara K Inati
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
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17
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Numamoto H, Fujimoto K, Miyake KK, Fushimi Y, Okuchi S, Imai R, Kondo H, Saga T, Nakamoto Y. Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC). Magn Reson Med Sci 2023:mp.2023-0102. [PMID: 37952942 DOI: 10.2463/mrms.mp.2023-0102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023] Open
Abstract
PURPOSE To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers. METHODS This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63-83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant. RESULTS In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177). CONCLUSION In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.
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Affiliation(s)
- Hitomi Numamoto
- Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Koji Fujimoto
- Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Kanae Kawai Miyake
- Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Rimika Imai
- Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Hiroki Kondo
- Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Tsuneo Saga
- Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
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18
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Johnson JT, Irfanoglu MO, Manninen E, Ross TJ, Yang Y, Laun FB, Martin J, Topgaard D, Benjamini D. In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.10.561702. [PMID: 37987005 PMCID: PMC10659440 DOI: 10.1101/2023.10.10.561702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω , in addition to the diffusion tensor, D , and relaxation, R 1 , R 2 , correlations. A D ( ω ) - R 1 - R 2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ( ω ) - R 1 - R 2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.
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Affiliation(s)
- Jessica T.E. Johnson
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - M. Okan Irfanoglu
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | - Eppu Manninen
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA
| | - Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jan Martin
- Department of Chemistry, Lund University, Lund, Sweden
| | | | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
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19
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Berry DB, Galinsky VL, Hutchinson EB, Galons JP, Ward SR, Frank LR. Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure. Magn Reson Med 2023; 90:1582-1593. [PMID: 37392410 DOI: 10.1002/mrm.29751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/28/2023] [Accepted: 05/21/2023] [Indexed: 07/03/2023]
Abstract
PURPOSE Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function. METHODS The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure. RESULTS Excellent agreement between SA and muscle fiber area (r2 = 0.71; p < 0.0001), fiber diameter (r2 = 0.83; p < 0.0001), and surface area to volume ratio (r2 = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow. CONCLUSIONS This study demonstrates that SA-a scalar value from diffusion tensor subspace imaging analysis-is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure.
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Affiliation(s)
- D B Berry
- Department of Orthopedic Surgery, University of California, San Diego, California, USA
- Department of Nanoengineering, University of California, San Diego, San Diego, California, USA
| | - V L Galinsky
- Center for Scientific Computation in Imaging, University of California, San Diego, San Diego, California, USA
| | - E B Hutchinson
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
| | - J P Galons
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
| | - S R Ward
- Department of Orthopedic Surgery, University of California, San Diego, California, USA
- Department of Radiology, University of California, San Diego, California, USA
- Department of Bioengineering, University of California, San Diego, California, USA
| | - L R Frank
- Center for Scientific Computation in Imaging, University of California, San Diego, San Diego, California, USA
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20
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Li Z, Miller KL, Andersson JLR, Zhang J, Liu S, Guo H, Wu W. Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high-resolution 3D diffusion MRI. Magn Reson Med 2023; 90:1484-1501. [PMID: 37317708 PMCID: PMC10952965 DOI: 10.1002/mrm.29741] [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: 01/11/2023] [Revised: 04/14/2023] [Accepted: 05/17/2023] [Indexed: 06/16/2023]
Abstract
PURPOSE To develop a new method for high-fidelity, high-resolution 3D multi-slab diffusion MRI with minimal distortion and boundary slice aliasing. METHODS Our method modifies 3D multi-slab imaging to integrate blip-reversed acquisitions for distortion correction and oversampling in the slice direction (kz ) for reducing boundary slice aliasing. Our aim is to achieve robust acceleration to keep the scan time the same as conventional 3D multi-slab acquisitions, in which data are acquired with a single direction of blip traversal and without kz -oversampling. We employ a two-stage reconstruction. In the first stage, the blip-up/down images are respectively reconstructed and analyzed to produce a field map for each diffusion direction. In the second stage, the blip-reversed data and the field map are incorporated into a joint reconstruction to produce images that are corrected for distortion and boundary slice aliasing. RESULTS We conducted experiments at 7T in six healthy subjects. Stage 1 reconstruction produces images from highly under-sampled data (R = 7.2) with sufficient quality to provide accurate field map estimation. Stage 2 joint reconstruction substantially reduces distortion artifacts with comparable quality to fully-sampled blip-reversed results (2.4× scan time). Whole-brain in-vivo results acquired at 1.22 mm and 1.05 mm isotropic resolutions demonstrate improved anatomical fidelity compared to conventional 3D multi-slab imaging. Data demonstrate good reliability and reproducibility of the proposed method over multiple subjects. CONCLUSION The proposed acquisition and reconstruction framework provide major reductions in distortion and boundary slice aliasing for 3D multi-slab diffusion MRI without increasing the scan time, which can potentially produce high-quality, high-resolution diffusion MRI.
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Affiliation(s)
- Ziyu Li
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Jesper L. R. Andersson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Jieying Zhang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of MedicineTsinghua UniversityBeijingChina
| | - Simin Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of MedicineTsinghua UniversityBeijingChina
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of MedicineTsinghua UniversityBeijingChina
| | - Wenchuan Wu
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
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21
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Wang S, Guertler CA, Okamoto RJ, Johnson CL, McGarry MDJ, Bayly PV. Mechanical stiffness and anisotropy measured by MRE during brain development in the minipig. Neuroimage 2023; 277:120234. [PMID: 37369255 PMCID: PMC11081136 DOI: 10.1016/j.neuroimage.2023.120234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023] Open
Abstract
The relationship between brain development and mechanical properties of brain tissue is important, but remains incompletely understood, in part due to the challenges in measuring these properties longitudinally over time. In addition, white matter, which is composed of aligned, myelinated, axonal fibers, may be mechanically anisotropic. Here we use data from magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI) to estimate anisotropic mechanical properties in six female Yucatan minipigs at ages from 3 to 6 months. Fiber direction was estimated from the principal axis of the diffusion tensor in each voxel. Harmonic shear waves in the brain were excited by three different configurations of a jaw actuator and measured using a motion-sensitive MR imaging sequence. Anisotropic mechanical properties are estimated from displacement field and fiber direction data with a finite element- based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. TI-NLI finds spatially resolved TI material properties that minimize the error between measured and simulated displacement fields. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal at all four ages. These maps show that white matter is more dissipative and anisotropic than gray matter, and reveal significant effects of brain development on brain stiffness and structural anisotropy. Changes in brain mechanical properties may be a fundamental biophysical signature of brain development.
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Affiliation(s)
- Shuaihu Wang
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | - Charlotte A Guertler
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | - Ruth J Okamoto
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States
| | | | | | - Philip V Bayly
- Mechanical Engineering and Material Science, Washington University in St. Louis, United States; Biomedical Engineering, Washington University in St. Louis, United States.
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22
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Slaby RJ, Arrington CN, Malins J, Sevcik RA, Pugh KR, Morris R. Properties of white matter tract diffusivity in children with developmental dyslexia and comorbid attention deficit/hyperactivity disorder. J Neurodev Disord 2023; 15:25. [PMID: 37550628 PMCID: PMC10408076 DOI: 10.1186/s11689-023-09495-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 07/11/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Developmental dyslexia (DD) and attention deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders. Individuals with DD or ADHD have both been shown to have deficits in white matter tracts associated with reading and attentional control networks. However, white matter diffusivity in individuals comorbid with both DD and ADHD (DD + ADHD) has not been specifically explored. METHODS Participants were 3rd and 4th graders (age range = 7 to 11 years; SD = 0.69) from three diagnostic groups ((DD (n = 40), DD + ADHD (n = 22), and typical developing (TD) (n = 20)). Behavioral measures of reading and attention alongside measures of white matter diffusivity were collected for all participants. RESULTS DD + ADHD and TD groups differed in mean fractional anisotropy (FA) for the left and right Superior Longitudinal Fasciculus (SLF)-Parietal Terminations and SLF-Temporal Terminations. Mean FA for the DD group across these SLF tracts fell between the lower DD + ADHD and higher TD averages. No differences in mean diffusivity nor significant brain-behavior relations were found. CONCLUSIONS Findings suggest that WM diffusivity in the SLF increases along a continuum across DD + ADHD, DD, and TD.
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Affiliation(s)
- Ryan J Slaby
- Department of Psychology, Georgia State University, 140 Decatur St SE, Atlanta, GA, 30303, USA
- GSU/Georgia Tech Center for Advanced Brain Imaging, 831 Marietta St NW, Atlanta, GA, 30318, USA
- Department of Psychology, University of Milano-Bicocca, Piazza Dell' Ateneo Nuovo,1, 20126, Milan, Italy
| | - C Nikki Arrington
- Department of Psychology, Georgia State University, 140 Decatur St SE, Atlanta, GA, 30303, USA.
- GSU/Georgia Tech Center for Advanced Brain Imaging, 831 Marietta St NW, Atlanta, GA, 30318, USA.
- Georgia State University, Center for Translational Research in Neuroimaging and Data Science, 55 Park Place, 18th Floor, Atlanta, GA, 30303, USA.
| | - Jeffrey Malins
- Department of Psychology, Georgia State University, 140 Decatur St SE, Atlanta, GA, 30303, USA
- GSU/Georgia Tech Center for Advanced Brain Imaging, 831 Marietta St NW, Atlanta, GA, 30318, USA
| | - Rose A Sevcik
- Department of Psychology, Georgia State University, 140 Decatur St SE, Atlanta, GA, 30303, USA
| | - Kenneth R Pugh
- Yale University, Haskins Laboratories, 300 George Street, Suite 900, New Haven, CT, 06511, USA
| | - Robin Morris
- Department of Psychology, Georgia State University, 140 Decatur St SE, Atlanta, GA, 30303, USA
- GSU/Georgia Tech Center for Advanced Brain Imaging, 831 Marietta St NW, Atlanta, GA, 30318, USA
- Georgia State University, Center for Translational Research in Neuroimaging and Data Science, 55 Park Place, 18th Floor, Atlanta, GA, 30303, USA
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23
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Mueller C, Szaflarski JP. White matter microstructure and serum biomarkers of inflammation in psychogenic non-epileptic seizures. Neuroimage Clin 2023; 39:103462. [PMID: 37413772 PMCID: PMC10509528 DOI: 10.1016/j.nicl.2023.103462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/14/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
BACKGROUND Neuroinflammation may contribute to the pathophysiology of psychogenic non-epileptic seizures (PNES). However, it is unclear whether and to what degree comorbid psychiatric symptoms explain this association. In this study, we investigated the neuroinflammatory signature of PNES and how it compares to that of people with psychiatric conditions (PwPCs). METHODS We prospectively assessed differences in neurite density (NDI), orientation dispersion (ODI), and isotropic diffusion (F-ISO) in 23 participants with PNES and 27 PwPCs, and their relationships to serum levels of tumor necrosis factor (TNF)-α, TNF receptor 1 (TNF-R1), TNF-related apoptosis-inducing ligand (TRAIL), interleukin (IL)-6, intercellular adhesion molecule (ICAM)-1, and monocyte chemoattractant protein (MCP)-1 using voxelwise multiple linear regressions. Pearson correlations between serum biomarkers and clinical symptoms were also obtained. RESULTS There were no white matter (WM) microstructural differences between groups. In PNES, TNF-R1 was negatively associated with NDI in the right uncinate fasciculus (UF) and positively associated with F-ISO in the left UF. IL-6 was positively associated with NDI and negatively with F-ISO in the left UF. ICAM-1 was positively associated with ODI in the left UF. TNF-α was negatively associated with ODI in the left cingulum bundle. The opposite relationships were observed in PwPCs. Higher TNF-R1 was associated with higher depression, anxiety, lower emotional quality of life, and higher levels of disability in PNES. CONCLUSIONS For the first time, we report relationships between peripheral inflammatory biomarkers and WM integrity in PNES, including abnormalities in the UF and cingulum bundle. Our results suggest that serum biomarkers of inflammation may, with additional studies, become a useful aid to PNES diagnosis, especially in settings where video-EEG is not available. The lack of group differences in WM microstructure suggests that previously identified WM abnormalities in PNES versus healthy controls may be related to psychological comorbidities of PNES.
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Affiliation(s)
- Christina Mueller
- Department of Neurology, University of Alabama at Birmingham (UAB), Heersink School of Medicine, Birmingham, AL, USA.
| | - Jerzy P Szaflarski
- Department of Neurology, University of Alabama at Birmingham (UAB), Heersink School of Medicine, Birmingham, AL, USA; Departments of Neurobiology and Neurosurgery, University of Alabama at Birmingham (UAB), Heersink School of Medicine, Birmingham, AL, USA.
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24
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Nair AK, Van Hulle CA, Bendlin BB, Zetterberg H, Blennow K, Wild N, Kollmorgen G, Suridjan I, Busse WW, Dean DC, Rosenkranz MA. Impact of asthma on the brain: evidence from diffusion MRI, CSF biomarkers and cognitive decline. Brain Commun 2023; 5:fcad180. [PMID: 37377978 PMCID: PMC10292933 DOI: 10.1093/braincomms/fcad180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 04/27/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
Chronic systemic inflammation increases the risk of neurodegeneration, but the mechanisms remain unclear. Part of the challenge in reaching a nuanced understanding is the presence of multiple risk factors that interact to potentiate adverse consequences. To address modifiable risk factors and mitigate downstream effects, it is necessary, although difficult, to tease apart the contribution of an individual risk factor by accounting for concurrent factors such as advanced age, cardiovascular risk, and genetic predisposition. Using a case-control design, we investigated the influence of asthma, a highly prevalent chronic inflammatory disease of the airways, on brain health in participants recruited to the Wisconsin Alzheimer's Disease Research Center (31 asthma patients, 186 non-asthma controls, aged 45-90 years, 62.2% female, 92.2% cognitively unimpaired), a sample enriched for parental history of Alzheimer's disease. Asthma status was determined using detailed prescription information. We employed multi-shell diffusion weighted imaging scans and the three-compartment neurite orientation dispersion and density imaging model to assess white and gray matter microstructure. We used cerebrospinal fluid biomarkers to examine evidence of Alzheimer's disease pathology, glial activation, neuroinflammation and neurodegeneration. We evaluated cognitive changes over time using a preclinical Alzheimer cognitive composite. Using permutation analysis of linear models, we examined the moderating influence of asthma on relationships between diffusion imaging metrics, CSF biomarkers, and cognitive decline, controlling for age, sex, and cognitive status. We ran additional models controlling for cardiovascular risk and genetic risk of Alzheimer's disease, defined as a carrier of at least one apolipoprotein E (APOE) ε4 allele. Relative to controls, greater Alzheimer's disease pathology (lower amyloid-β42/amyloid-β40, higher phosphorylated-tau-181) and synaptic degeneration (neurogranin) biomarker concentrations were associated with more adverse white matter metrics (e.g. lower neurite density, higher mean diffusivity) in patients with asthma. Higher concentrations of the pleiotropic cytokine IL-6 and the glial marker S100B were associated with more salubrious white matter metrics in asthma, but not in controls. The adverse effects of age on white matter integrity were accelerated in asthma. Finally, we found evidence that in asthma, relative to controls, deterioration in white and gray matter microstructure was associated with accelerated cognitive decline. Taken together, our findings suggest that asthma accelerates white and gray matter microstructural changes associated with aging and increasing neuropathology, that in turn, are associated with more rapid cognitive decline. Effective asthma control, on the other hand, may be protective and slow progression of cognitive symptoms.
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Affiliation(s)
- Ajay Kumar Nair
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53703, USA
| | - Carol A Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, S-431 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 30 Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WCIE 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, Clear Water Bay, Hong Kong SAR, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, S-431 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 30 Mölndal, Sweden
| | - Norbert Wild
- Roche Diagnostics GmbH, Core Lab RED, 82377 Penzberg, Germany
| | | | - Ivonne Suridjan
- CDMA Clinical Development, Roche Diagnostics International Ltd, CH-6346, Rotkreuz, Switzerland
| | - William W Busse
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Douglas C Dean
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53703, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA
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25
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Han G, Zhou Y, Zhang K, Jiao B, Hu J, Zhang Y, Wang Z, Lou M, Bai R. Age- and time-of-day dependence of glymphatic function in the human brain measured via two diffusion MRI methods. Front Aging Neurosci 2023; 15:1173221. [PMID: 37284019 PMCID: PMC10239807 DOI: 10.3389/fnagi.2023.1173221] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 05/04/2023] [Indexed: 06/08/2023] Open
Abstract
Advanced age, accompanied by impaired glymphatic function, is a key risk factor for many neurodegenerative diseases. To study age-related differences in the human glymphatic system, we measured the influx and efflux activities of the glymphatic system via two non-invasive diffusion magnetic resonance imaging (MRI) methods, ultra-long echo time and low-b diffusion tensor imaging (DTIlow-b) measuring the subarachnoid space (SAS) flow along the middle cerebral artery and DTI analysis along the perivascular space (DTI-ALPS) along medullary veins in 22 healthy volunteers (aged 21-75 years). We first evaluated the circadian rhythm dependence of the glymphatic activity by repeating the MRI measurements at five time points from 8:00 to 23:00 and found no time-of-day dependence in the awake state under the current sensitivity of MRI measurements. Further test-retest analysis demonstrated high repeatability of both diffusion MRI measurements, suggesting their reliability. Additionally, the influx rate of the glymphatic system was significantly higher in participants aged >45 years than in participants aged 21-38, while the efflux rate was significantly lower in those aged >45 years. The mismatched influx and efflux activities in the glymphatic system might be due to age-related changes in arterial pulsation and aquaporin-4 polarization.
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Affiliation(s)
- Guangxu Han
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, School of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Kemeng Zhang
- Department of Neurology, School of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Bingjie Jiao
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Junwen Hu
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Clinical Research Center for Neurological Diseases of Zhejiang Province, Hangzhou, China
| | - Yifan Zhang
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zejun Wang
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Min Lou
- Department of Neurology, School of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Ruiliang Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
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26
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Lei D, Qin K, Li W, Zhu Z, Tallman MJ, Patino LR, Fleck DE, Aghera V, Gong Q, Sweeney JA, DelBello MP, McNamara RK. Regional microstructural differences in ADHD youth with and without a family history of bipolar I disorder. J Affect Disord 2023; 334:238-245. [PMID: 37149051 DOI: 10.1016/j.jad.2023.04.125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/21/2023] [Accepted: 04/29/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Having a first-degree relative with bipolar I disorder (BD) in conjunction with prodromal attention deficit/hyperactivity disorder (ADHD) may represent a unique phenotype that confers greater risk for developing BD than ADHD alone. However, underlying neuropathoetiological mechanisms remain poorly understood. This cross-sectional study compared regional microstructure in psychostimulant-free ADHD youth with ('high-risk', HR) and without ('low-risk', LR) a first-degree relative with BD, and healthy controls (HC). METHODS A total of 140 (high-risk, n = 44; low-risk, n = 49; and HC, n = 47) youth (mean age: 14.1 ± 2.5 years, 65 % male) were included in the analysis. Diffusion tensor images were collected and fractional anisotropy (FA) and mean diffusivity (MD) maps calculated. Both tract-based and voxel-based analyses were performed. Correlations between clinical ratings and microstructural metrics that differed among groups were examined. RESULTS No significant group differences in major long-distance fiber tracts were observed. The high-risk ADHD group exhibited predominantly higher FA and lower MD in frontal, limbic, and striatal subregions compared with the low-risk ADHD group. Both low-risk and high-risk ADHD groups exhibited higher FA in unique and overlapping regions compared with HC subjects. Significant correlations between regional microstructural metrics and clinical ratings were observed in ADHD groups. LIMITATIONS Prospective longitudinal studies will be required to determine the relevance of these findings to BD risk progression. CONCLUSIONS Psychostimulant-free ADHD youth with a BD family history exhibit different microstructure alterations in frontal, limbic, and striatal regions compared with ADHD youth without a BD family history, and may therefore represent unique phenotypes relevant to BD risk progression.
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Affiliation(s)
- Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA.
| | - Kun Qin
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ziyu Zhu
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Veronica Aghera
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China.
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
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27
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Gangolli M, Wang WT, Gai ND, Pham DL, Butman JA. Simultaneous Acquisition of Diffusion Tensor and Dynamic Diffusion MRI. J Magn Reson Imaging 2023; 57:1079-1092. [PMID: 36056625 PMCID: PMC9981815 DOI: 10.1002/jmri.28407] [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: 09/16/2021] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Dynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application. PURPOSE To determine whether a diffusion gradient table can simultaneously acquire data to estimate dynamic and diffusion tensor imaging (DTI) metrics. STUDY TYPE Prospective. SUBJECTS Seven healthy subjects, 39 epilepsy patients (15 female, 31 male, age ± 15). FIELD STRENGTH/SEQUENCE Two-dimensional diffusion MRI (b = 1000 s/mm2 ) at a field strength of 3 T. Sessions in healthy subjects-standard ddMRI (30 directions), standard DTI (15 and 30 directions), and nested cubes scans (15 and 30 directions). Sessions in epilepsy patients-two 30 direction (standard ddMRI, 10 nested cubes) or two 15 direction scans (standard DTI, 5 nested cubes). ASSESSMENT Fifteen direction DTI was repeated twice for within-session test-retest measurements in healthy subjects. Bland-Altman analysis computed bias and limits of agreement for DTI metrics using test-retest scans and standard 15 direction vs. 5 nested cubes scans. Intraclass correlation (ICC) analysis compared tensor metrics between 15 direction DTI scans (standard vs. 5 nested cubes) and the coefficients of variation (CoV) of trace and apparent diffusion coefficient (ADC) between 30 direction ddMRI scans (standard vs. 10 nested cubes). STATISTICAL TESTS Bland-Altman and ICC analysis using a P-value of 0.05 for statistical significance. RESULTS Correlations of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were strong and significant in gray (ICC > 0.95) and white matter (ICC > 0.95) between standard vs. nested cubes DTI acquisitions. Correlation of white matter fractional anisotropy was also strong (ICC > 0.95) and significant. ICCs of the CoV of dynamic ADC measured using repeated cubes and nested cubes acquisitions were modest (ICC >0.60), but significant in gray matter. CONCLUSION A nested cubes diffusion gradient table produces tensor-based and dynamic diffusion measurements in a single acquisition. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Mihika Gangolli
- Center for Neuroscience and Regenerative Medicine
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc
| | - Wen-Tung Wang
- National Institutes of Health, Radiology and Imaging Sciences
| | - Neville D. Gai
- National Institutes of Health, National Heart Lung and Blood Institute
| | - Dzung L. Pham
- Center for Neuroscience and Regenerative Medicine
- Uniformed Services University, Radiology and Radiological Sciences
| | - John A. Butman
- Center for Neuroscience and Regenerative Medicine
- National Institutes of Health, Radiology and Imaging Sciences
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Xie W, Cappiello M, Yassa MA, Ester E, Zaghloul KA, Zhang W. The entorhinal-DG/CA3 pathway in the medial temporal lobe retains visual working memory of a simple surface feature. eLife 2023; 12:83365. [PMID: 36861959 PMCID: PMC10019891 DOI: 10.7554/elife.83365] [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: 09/09/2022] [Accepted: 03/01/2023] [Indexed: 03/03/2023] Open
Abstract
Classic models consider working memory (WM) and long-term memory as distinct mental faculties that are supported by different neural mechanisms. Yet, there are significant parallels in the computation that both types of memory require. For instance, the representation of precise item-specific memory requires the separation of overlapping neural representations of similar information. This computation has been referred to as pattern separation, which can be mediated by the entorhinal-DG/CA3 pathway of the medial temporal lobe (MTL) in service of long-term episodic memory. However, although recent evidence has suggested that the MTL is involved in WM, the extent to which the entorhinal-DG/CA3 pathway supports precise item-specific WM has remained elusive. Here, we combine an established orientation WM task with high-resolution fMRI to test the hypothesis that the entorhinal-DG/CA3 pathway retains visual WM of a simple surface feature. Participants were retrospectively cued to retain one of the two studied orientation gratings during a brief delay period and then tried to reproduce the cued orientation as precisely as possible. By modeling the delay-period activity to reconstruct the retained WM content, we found that the anterior-lateral entorhinal cortex (aLEC) and the hippocampal DG/CA3 subfield both contain item-specific WM information that is associated with subsequent recall fidelity. Together, these results highlight the contribution of MTL circuitry to item-specific WM representation.
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Affiliation(s)
- Weizhen Xie
- Surgical Neurology Branch, National Institute of Neurological Disorders and StrokeBethesdaUnited States
- Department of Psychology, University of California, RiversideRiversideUnited States
- Department of Psychology, University of MarylandCollege ParkUnited States
| | - Marcus Cappiello
- Department of Psychology, University of California, RiversideRiversideUnited States
| | - Michael A Yassa
- Center for the Neurobiology of Learning and Memory, School of Biological Sciences, University of California, IrvineIrvineUnited States
| | - Edward Ester
- Department of Psychology, University of NevadaRenoUnited States
| | - Kareem A Zaghloul
- Surgical Neurology Branch, National Institute of Neurological Disorders and StrokeBethesdaUnited States
| | - Weiwei Zhang
- Department of Psychology, University of California, RiversideRiversideUnited States
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DACO: Distortion/artefact correction for diffusion MRI data. Neuroimage 2022; 262:119571. [PMID: 35985619 DOI: 10.1016/j.neuroimage.2022.119571] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 08/12/2022] [Accepted: 08/15/2022] [Indexed: 01/14/2023] Open
Abstract
In this paper, we propose a registration-based algorithm to correct various distortions or artefacts (DACO) commonly observed in diffusion-weighted (DW) magnetic resonance images (MRI). The registration in DACO is accomplished by means of a pseudo b0 image, which is synthesized from the anatomical images such as T1-weighted image or T2-weighted image, and a pseudo diffusion MRI (dMRI) data, which is derived from the Gaussian model of diffusion tensor imaging (DTI) or the Hermite model of mean apparent propagator (MAP)-MRI. DACO corrects (1) the susceptibility-induced distortions and (2) the misalignment between the dMRI data and anatomical images by registering the real b0 image to the pseudo b0 image, and corrects (3) the eddy current-induced distortions and (4) the head motions by registering each image in the real dMRI data to the corresponding image in the pseudo dMRI data. DACO estimates the models of artefacts simultaneously in an iterative and interleaved manner. The mathematical formulation of the models and the estimation procedures are detailed in this paper. Using the human connectome project (HCP) data the evaluation shows that DACO could estimate the model parameters accurately. Furthermore, the evaluation conducted on the real human data acquired from clinical MRI scanners reveals that the method could reduce the artefacts effectively. The DACO method leverages the anatomical image, which is routinely acquired in clinical practice, to correct the artefacts, omitting the additional acquisitions needed to conduct the algorithm. Therefore, our method should be beneficial to most dMRI data, particularly to those acquired without field maps or reverse phase-encoding images.
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Yang JYM, Chen J, Alexander B, Schilling K, Kean M, Wray A, Seal M, Maixner W, Beare R. Assessment of intraoperative diffusion EPI distortion and its impact on estimation of supratentorial white matter tract positions in pediatric epilepsy surgery. Neuroimage Clin 2022; 35:103097. [PMID: 35759887 PMCID: PMC9250069 DOI: 10.1016/j.nicl.2022.103097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/18/2022] [Accepted: 06/20/2022] [Indexed: 10/26/2022]
Abstract
The effectiveness of correcting diffusion Echo Planar Imaging (EPI) distortion and its impact on tractography reconstruction have not been adequately investigated in the intraoperative MRI setting, particularly for High Angular Resolution Diffusion Imaging (HARDI) acquisition. In this study, we evaluated the effectiveness of EPI distortion correction using 27 legacy intraoperative HARDI datasets over two consecutive surgical time points, acquired without reverse phase-encoded data, from 17 children who underwent epilepsy surgery at our institution. The data was processed with EPI distortion correction using the Synb0-Disco technique (Schilling et al., 2019) and without distortion correction. The corrected and uncorrected b0 diffusion-weighted images (DWI) were first compared visually. The mutual information indices between the original T1-weighted images and the fractional anisotropy images derived from corrected and uncorrected DWI were used to quantify the effect of distortion correction. Sixty-four white matter tracts were segmented from each dataset, using a deep-learning based automated tractography algorithm for the purpose of a standardized and unbiased evaluation. Displacement was calculated between tracts generated before and after distortion correction. The tracts were grouped based on their principal morphological orientations to investigate whether the effects of EPI distortion vary with tract orientation. Group differences in tract distortion were investigated both globally, and regionally with respect to proximity to the resecting lesion in the operative hemisphere. Qualitatively, we observed notable improvement in the corrected diffusion images, over the typically affected brain regions near skull-base air sinuses, and correction of additional distortion unique to intraoperative open cranium images, particularly over the resection site. This improvement was supported quantitatively, as mutual information indices between the FA and T1-weighted images were significantly greater after the correction, compared to before the correction. Maximum tract displacement between the corrected and uncorrected data, was in the range of 7.5 to 10.0 mm, a magnitude that would challenge the safety resection margin typically tolerated for tractography-informed surgical guidance. This was particularly relevant for tracts oriented partially or fully in-line with the acquired diffusion phase-encoded direction. Portions of these tracts passing close to the resection site demonstrated significantly greater magnitude of displacement, compared to portions of tracts remote from the resection site in the operative hemisphere. Our findings have direct clinical implication on the accuracy of intraoperative tractography-informed image guidance and emphasize the need to develop a distortion correction technique with feasible intraoperative processing time.
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Affiliation(s)
- Joseph Yuan-Mou Yang
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia.
| | - Jian Chen
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Bonnie Alexander
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Kurt Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Centre, Nashville, USA
| | - Michael Kean
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia; Medical Imaging, The Royal Children's Hospital, Melbourne, Australia
| | - Alison Wray
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia
| | - Marc Seal
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Wirginia Maixner
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia
| | - Richard Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Peninsula Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia
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Performance Comparison of Different Neuroimaging Methods for Predicting Upper Limb Motor Outcomes in Patients after Stroke. Neural Plast 2022; 2022:4203698. [PMID: 35707519 PMCID: PMC9192322 DOI: 10.1155/2022/4203698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 03/17/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022] Open
Abstract
Several neuroimaging methods have been proposed to assess the integrity of the corticospinal tract (CST) for predicting recovery of motor function after stroke, including conventional structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). In this study, we aimed to compare the predicative performance of these methods using different neuroimaging modalities and optimize the prediction protocol for upper limb motor function after stroke in a clinical environment. We assessed 28 first-ever stroke patients with upper limb motor impairment. We used the upper extremity module of the Fugl-Meyer assessment (UE-FM) within 1 month of onset (baseline) and again 3 months poststroke. sMRI (T1- and T2-based) was used to measure CST-weighted lesion load (CST-wLL), and DTI was used to measure the fractional anisotropy asymmetry index (FAAI) and the ratio of fractional anisotropy (rFA). The CST-wLL within 1 month poststroke was closely correlated with upper limb motor outcomes and recovery potential. CST‐wLL ≥ 2.068 cc indicated serious CST damage and a poor outcome (100%). CST‐wLL < 1.799 cc was correlated with a considerable rate (>70%) of upper limb motor function recovery. CST-wLL showed a comparable area under the curve (AUC) to that of the CST-FAAI (p = 0.71). Inclusion of extra-CST-FAAI did not significantly increase the AUC (p = 0.58). Our findings suggest that sMRI-derived CST-wLL is a precise predictor of upper limb motor outcomes 3 months poststroke. We recommend this parameter as a predictive imaging biomarker for classifying patients' recovery prognosis in clinical practice. Conversely, including DTI appeared to induce no significant benefits.
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Ly MT, Scarneo-Miller SE, Lepley AS, Coleman K, Hirschhorn R, Yeargin S, Casa DJ, Chen CM. Combining MRI and cognitive evaluation to classify concussion in university athletes. Brain Imaging Behav 2022; 16:2175-2187. [PMID: 35639240 DOI: 10.1007/s11682-022-00687-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/09/2022] [Indexed: 11/26/2022]
Abstract
Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R2 = 0.32, p < .001), and performed worse on tests of concentration (∆R2 = 0.07, p < .05) and delayed memory (∆R2 = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.
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Affiliation(s)
- Monica T Ly
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA.
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
- Department of Psychiatry, University of California San Diego, School of Medicine, San Diego, CA, USA.
| | - Samantha E Scarneo-Miller
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- Division of Athletic Training, School of Medicine, West Virginia University, Morgantown, WV, USA
| | - Adam S Lepley
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- School of Kinesiology, Exercise and Sport Science Initiative, University of Michigan, Ann Arbor, MI, USA
| | - Kelly Coleman
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- Department of Health & Movement Sciences, Southern Connecticut State University, New Haven, CT, USA
| | - Rebecca Hirschhorn
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
- School of Kinesiology, Louisiana State University, Baton Rouge, LA, USA
| | - Susan Yeargin
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Douglas J Casa
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
| | - Chi-Ming Chen
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
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33
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Qiao Y, Shi Y. Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1165-1175. [PMID: 34882551 PMCID: PMC9177803 DOI: 10.1109/tmi.2021.3134496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Susceptibility induced distortion is a major artifact that affects the diffusion MRI (dMRI) data analysis. In the Human Connectome Project (HCP), the state-of-the-art method adopted to correct this kind of distortion is to exploit the displacement field from the B0 image in the reversed phase encoding images. However, both the traditional and learning-based approaches have limitations in achieving high correction accuracy in certain brain regions, such as brainstem. By utilizing the fiber orientation distribution (FOD) computed from the dMRI, we propose a novel deep learning framework named DistoRtion Correction Net (DrC-Net), which consists of the U-Net to capture the latent information from the 4D FOD images and the spatial transformer network to propagate the displacement field and back propagate the losses between the deformed FOD images. The experiments are performed on two datasets acquired with different phase encoding (PE) directions including the HCP and the Human Connectome Low Vision (HCLV) dataset. Compared to two traditional methods topup and FODReg and two deep learning methods S-Net and flow-net, the proposed method achieves significant improvements in terms of the mean squared difference (MSD) of fractional anisotropy (FA) images and minimum angular difference between two PEs in white matter and also brainstem regions. In the meantime, the proposed DrC-Net takes only several seconds to predict a displacement field, which is much faster than the FODReg method.
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34
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Begnoche JP, Schilling KG, Boyd BD, Cai LY, Taylor WD, Landman BA. EPI susceptibility correction introduces significant differences far from local areas of high distortion. Magn Reson Imaging 2022; 92:1-9. [DOI: 10.1016/j.mri.2022.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 05/01/2022] [Accepted: 05/22/2022] [Indexed: 11/16/2022]
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Wang J, Nasr S, Roe AW, Polimeni JR. Critical factors in achieving fine-scale functional MRI: Removing sources of inadvertent spatial smoothing. Hum Brain Mapp 2022; 43:3311-3331. [PMID: 35417073 PMCID: PMC9248309 DOI: 10.1002/hbm.25867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 11/09/2022] Open
Abstract
Ultra‐high Field (≥7T) functional magnetic resonance imaging (UHF‐fMRI) provides opportunities to resolve fine‐scale features of functional architecture such as cerebral cortical columns and layers, in vivo. While the nominal resolution of modern fMRI acquisitions may appear to be sufficient to resolve these features, several common data preprocessing steps can introduce unwanted spatial blurring, especially those that require interpolation of the data. These resolution losses can impede the detection of the fine‐scale features of interest. To examine quantitatively and systematically the sources of spatial resolution losses occurring during preprocessing, we used synthetic fMRI data and real fMRI data from the human visual cortex—the spatially interdigitated human V2 “thin” and “thick” stripes. The pattern of these cortical columns lies along the cortical surface and thus can be best appreciated using surface‐based fMRI analysis. We used this as a testbed for evaluating strategies that can reduce spatial blurring of fMRI data. Our results show that resolution losses can be mitigated at multiple points in preprocessing pathway. We show that unwanted blur is introduced at each step of volume transformation and surface projection, and can be ameliorated by replacing multi‐step transformations with equivalent single‐step transformations. Surprisingly, the simple approaches of volume upsampling and of cortical mesh refinement also helped to reduce resolution losses caused by interpolation. Volume upsampling also serves to improve motion estimation accuracy, which helps to reduce blur. Moreover, we demonstrate that the level of spatial blurring is nonuniform over the brain—knowledge which is critical for interpreting data in high‐resolution fMRI studies. Importantly, our study provides recommendations for reducing unwanted blurring during preprocessing as well as methods that enable quantitative comparisons between preprocessing strategies. These findings highlight several underappreciated sources of a spatial blur. Individually, the factors that contribute to spatial blur may appear to be minor, but in combination, the cumulative effects can hinder the interpretation of fine‐scale fMRI and the detectability of these fine‐scale features of functional architecture.
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Affiliation(s)
- Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Shahin Nasr
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Guerrero-Gonzalez J, Surgent O, Adluru N, Kirk GR, Dean III DC, Kecskemeti SR, Alexander AL, Travers BG. Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem. Front Integr Neurosci 2022; 16:804743. [PMID: 35310466 PMCID: PMC8928227 DOI: 10.3389/fnint.2022.804743] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/31/2022] [Indexed: 11/24/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging. Here, we implement a method for achieving increased apparent spatial resolution in pediatric dMRI that hinges on accurate geometric distortion correction and on high fidelity within subject image registration between dMRI and magnetization prepared rapid acquisition gradient echo (MPnRAGE) images. We call this post-processing pipeline T1 weighted-diffusion fused, or "TiDi-Fused". Data used in this work consists of dMRI data (2.4 mm resolution, corrected using FSL's Topup) and T1-weighted (T1w) MPnRAGE anatomical data (1 mm resolution) acquired from 128 autistic and non-autistic children (ages 6-10 years old). Accurate correction of geometric distortion permitted for a further increase in apparent resolution of the dMRI scan via boundary-based registration to the MPnRAGE T1w. Estimation of fiber orientation distributions and further analyses were carried out in the T1w space. Data processed with the TiDi-Fused method were qualitatively and quantitatively compared to data processed with conventional dMRI processing methods. Results show the advantages of the TiDi-Fused pipeline including sharper brainstem gray-white matter tissue contrast, improved inter-subject spatial alignment for group analyses of dMRI based measures, accurate spatial alignment with histology-based imaging of the brainstem, reduced variability in brainstem-cerebellar white matter tracts, and more robust biologically plausible relationships between age and brainstem-cerebellar white matter tracts. Overall, this work identifies a promising pipeline for achieving high-resolution imaging of brainstem structures in pediatric and clinical populations who may not be able to endure long scan times. This pipeline may serve as a gateway for feasibly elucidating brainstem contributions to autism and other conditions.
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Affiliation(s)
- Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean III
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Occupational Therapy Program in the Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
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Wu H, Sun C, Huang X, Wei R, Li Z, Ke D, Bai R, Liang H. Short-Range Structural Connections Are More Severely Damaged in Early-Stage MS. AJNR Am J Neuroradiol 2022; 43:361-367. [PMID: 35177546 PMCID: PMC8910797 DOI: 10.3174/ajnr.a7425] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 12/11/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Long-range connections are more severely damaged and relevant for cognition in long-standing MS. However, the evolution of such coordinated network damage in patients with MS is unclear. We investigated whether short- and long-range structural connections sustained equal damage in early-stage MS. MATERIALS AND METHODS Sixteen patients with early-stage MS and 17 healthy controls were scanned by high-resolution, multishell diffusion imaging on 7T MR imaging and assessed cognitively. We investigated macrostructural properties in short- and long-range fibers and of microstructural metrics derived from 2 quantitative diffusion MR imaging models: DTI and neurite orientation dispersion and density imaging. RESULTS Patients had significant WM integrity damage-that is, higher radial diffusivity and a lower intracellular volume fraction in the focal WM lesions. Compared with the healthy controls, the patients had noticeable microstructure changes in both short- and long-range fibers, including increased radial diffusivity, mean diffusivity, and axial diffusivity. Z scores further indicated greater damage in the short-range fibers than in the long-range fibers. CONCLUSIONS Our findings demonstrate that more severe demyelination preceding axonal degeneration occurs in short-range connections but not in long-range connections in early-stage MS, suggesting the possibility that there are cortical lesions that are undetectable by current MR imaging.
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Affiliation(s)
- H. Wu
- Frpm the Department of Neurology (H.W., X.H., R.W., D.K., H.L.), First Affiliated Hospital
| | - C. Sun
- Key Laboratory of Biomedical Engineering of Ministry of Education (C.S., Z.L.), College of Biomedical Engineering and Instrument Science
| | - X. Huang
- Frpm the Department of Neurology (H.W., X.H., R.W., D.K., H.L.), First Affiliated Hospital
| | - R. Wei
- Frpm the Department of Neurology (H.W., X.H., R.W., D.K., H.L.), First Affiliated Hospital
| | - Z. Li
- Key Laboratory of Biomedical Engineering of Ministry of Education (C.S., Z.L.), College of Biomedical Engineering and Instrument Science
| | - D. Ke
- Frpm the Department of Neurology (H.W., X.H., R.W., D.K., H.L.), First Affiliated Hospital
| | - R. Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology (R.B.), School of Medicine, Zhejiang University, Hangzhou, China
| | - H. Liang
- Frpm the Department of Neurology (H.W., X.H., R.W., D.K., H.L.), First Affiliated Hospital
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Hutchinson EB, Romero-Lozano A, Johnson HR, Knutsen AK, Bosomtwi A, Korotcov A, Shunmugavel A, King SG, Schwerin SC, Juliano SL, Dardzinski BJ, Pierpaoli C. Translationally Relevant Magnetic Resonance Imaging Markers in a Ferret Model of Closed Head Injury. Front Neurosci 2022; 15:779533. [PMID: 35280340 PMCID: PMC8904401 DOI: 10.3389/fnins.2021.779533] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 12/17/2021] [Indexed: 11/13/2022] Open
Abstract
Pre-clinical models of traumatic brain injury (TBI) have been the primary experimental tool for understanding the potential mechanisms and cellular alterations that follow brain injury, but the human relevance and translational value of these models are often called into question. Efforts to better recapitulate injury biomechanics and the use of non-rodent species with neuroanatomical similarities to humans may address these concerns and promise to advance experimental studies toward clinical impact. In addition to improving translational aspects of animal models, it is also advantageous to establish pre-clinical outcomes that can be directly compared with the same outcomes in humans. Non-invasive imaging and particularly MRI is promising for this purpose given that MRI is a primary tool for clinical diagnosis and at the same time increasingly available at the pre-clinical level. The objective of this study was to identify which commonly used radiologic markers of TBI outcomes can be found also in a translationally relevant pre-clinical model of TBI. The ferret was selected as a human relevant species for this study with folded cortical geometry and relatively high white matter content and the closed head injury model of engineered rotation and acceleration (CHIMERA) TBI model was selected for biomechanical similarities to human injury. A comprehensive battery of MRI protocols based on common data elements (CDEs) for human TBI was collected longitudinally for the identification of MRI markers and voxelwise analysis of T2, contrast enhancement and diffusion tensor MRI values. The most prominent MRI findings were consistent with focal hemorrhage and edema in the brain stem region following high severity injury as well as vascular and meningeal injury evident by contrast enhancement. While conventional MRI outcomes were not highly conspicuous in less severe cases, quantitative voxelwise analysis indicated diffusivity and anisotropy alterations in the acute and chronic periods after TBI. The main conclusions of this study support the translational relevance of closed head TBI models in intermediate species and identify brain stem and meningeal vulnerability. Additionally, the MRI findings highlight a subset of CDEs with promise to bridge pre-clinical studies with human TBI outcomes.
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Affiliation(s)
- Elizabeth B. Hutchinson
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States
- *Correspondence: Elizabeth B. Hutchinson,
| | | | - Hannah R. Johnson
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States
| | - Andrew K. Knutsen
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Asamoah Bosomtwi
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Alexandru Korotcov
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Anandakumar Shunmugavel
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, United States
| | - Sarah G. King
- National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, United States
| | - Susan C. Schwerin
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Sharon L. Juliano
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Bernard J. Dardzinski
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Carlo Pierpaoli
- National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, United States
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Prenatal depression exposure alters white matter integrity and neurodevelopment in early childhood. Brain Imaging Behav 2022; 16:1324-1336. [PMID: 35000066 PMCID: PMC9107412 DOI: 10.1007/s11682-021-00616-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2021] [Indexed: 11/02/2022]
Abstract
Prenatal exposure to maternal depression increases the risk for onset of emotional and behavioral disorders in children. We investigated the effects of exposure to prenatal depression on white matter microstructural integrity at birth and at 2-3 years, and associated neurodevelopment. Diffusion-weighted images were acquired for children of the Drakenstein Child Health Study at 2-4 weeks postpartum (n=70, 47% boys) and at 2-3 years of age (n=60, 58% boys). Tract-Based Spatial Statistics was used to compare, using an ROI based approach, diffusion tensor metrics across groups defined by presence (>19 on Beck's Depression Inventory and/or >12 on the Edinburgh Postnatal Depression Scale) or absence (below depression thresholds) of depression, and associations with neurodevelopmental measures at age 2-3 years were determined. We did not detect group differences in white matter integrity at neonatal age, but at 2-3 years, children in the exposed group demonstrated higher fractional anisotropy, and lower mean and radial diffusivity in association tracts compared to controls. This was notable in the sagittal stratum (radial diffusivity: p<0.01). Altered white matter integrity metrics were also observed in projection tracts, including the corona radiata, which associated with cognitive and motor outcomes in exposed 2-3-year-olds (p<0.05). Our findings of widespread white matter alterations in 2-3-year-old children with prenatal exposure to depression are consistent with previous findings, as well as with neuroimaging findings in adults with major depression. Further, we identified novel associations of altered white matter integrity with cognitive development in depression-exposed children, suggesting that these neuroimaging findings may have early functional impact.
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Coll-Font J, Chen S, Eder R, Fang Y, Han QJ, van den Boomen M, Sosnovik DE, Mekkaoui C, Nguyen CT. Manifold-based respiratory phase estimation enables motion and distortion correction of free-breathing cardiac diffusion tensor MRI. Magn Reson Med 2022; 87:474-487. [PMID: 34390021 PMCID: PMC8616783 DOI: 10.1002/mrm.28972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 07/22/2021] [Accepted: 07/25/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE For in vivo cardiac DTI, breathing motion and B0 field inhomogeneities produce misalignment and geometric distortion in diffusion-weighted (DW) images acquired with conventional single-shot EPI. We propose using a dimensionality reduction method to retrospectively estimate the respiratory phase of DW images and facilitate both distortion correction (DisCo) and motion compensation. METHODS Free-breathing electrocardiogram-triggered whole left-ventricular cardiac DTI using a second-order motion-compensated spin echo EPI sequence and alternating directionality of phase encoding blips was performed on 11 healthy volunteers. The respiratory phase of each DW image was estimated after projecting the DW images into a 2D space with Laplacian eigenmaps. DisCo and motion compensation were applied to the respiratory sorted DW images. The results were compared against conventional breath-held T2 half-Fourier single shot turbo spin echo. Cardiac DTI parameters including fractional anisotropy, mean diffusivity, and helix angle transmurality were compared with and without DisCo. RESULTS The left-ventricular geometries after DisCo and motion compensation resulted in significantly improved alignment of DW images with T2 reference. DisCo reduced the distance between the left-ventricular contours by 13.2% ± 19.2%, P < .05 (2.0 ± 0.4 for DisCo and 2.4 ± 0.5 mm for uncorrected). DisCo DTI parameter maps yielded no significant differences (mean diffusivity: 1.55 ± 0.13 × 10-3 mm2 /s and 1.53 ± 0.13 × 10-3 mm2 /s, P = .09; fractional anisotropy: 0.375 ± 0.041 and 0.379 ± 0.045, P = .11; helix angle transmurality: 1.00% ± 0.10°/% and 0.99% ± 0.12°/%, P = .44), although the orientation of individual tensors differed. CONCLUSION Retrospective respiratory phase estimation with LE-based DisCo and motion compensation in free-breathing cardiac DTI resulting in significantly reduced geometric distortion and improved alignment within and across slices.
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Affiliation(s)
- Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Shi Chen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA
| | - Robert Eder
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA
| | - Yiling Fang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, (MA), USA
| | - Qiao Joyce Han
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Maaike van den Boomen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA,Department of Radiology, University Medical Center Groningen, Groningen, Netherlands
| | - David E. Sosnovik
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Choukri Mekkaoui
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Christopher T. Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
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41
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What's New and What's Next in Diffusion MRI Preprocessing. Neuroimage 2021; 249:118830. [PMID: 34965454 PMCID: PMC9379864 DOI: 10.1016/j.neuroimage.2021.118830] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/26/2021] [Accepted: 12/15/2021] [Indexed: 02/07/2023] Open
Abstract
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropriately accounted for. This review will cover dMRI artifacts and preprocessing steps, some of which have not typically been considered in existing pipelines or reviews, or have only gained attention in recent years: brain/skull extraction, B-matrix incompatibilities w.r.t the imaging data, signal drift, Gibbs ringing, noise distribution bias, denoising, between- and within-volumes motion, eddy currents, outliers, susceptibility distortions, EPI Nyquist ghosts, gradient deviations, B1 bias fields, and spatial normalization. The focus will be on “what’s new” since the notable advances prior to and brought by the Human Connectome Project (HCP), as presented in the predecessing issue on “Mapping the Connectome” in 2013. In addition to the development of novel strategies for dMRI preprocessing, exciting progress has been made in the availability of open source tools and reproducible pipelines, databases and simulation tools for the evaluation of preprocessing steps, and automated quality control frameworks, amongst others. Finally, this review will consider practical considerations and our view on “what’s next” in dMRI preprocessing.
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Bayly PV, Alshareef A, Knutsen AK, Upadhyay K, Okamoto RJ, Carass A, Butman JA, Pham DL, Prince JL, Ramesh KT, Johnson CL. MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury. Ann Biomed Eng 2021; 49:2677-2692. [PMID: 34212235 PMCID: PMC8516723 DOI: 10.1007/s10439-021-02820-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/22/2021] [Indexed: 01/04/2023]
Abstract
Computational models of the brain and its biomechanical response to skull accelerations are important tools for understanding and predicting traumatic brain injuries (TBIs). However, most models have been developed using experimental data collected on animal models and cadaveric specimens, both of which differ from the living human brain. Here we describe efforts to noninvasively measure the biomechanical response of the human brain with MRI-at non-injurious strain levels-and generate data that can be used to develop, calibrate, and evaluate computational brain biomechanics models. Specifically, this paper reports on a project supported by the National Institute of Neurological Disorders and Stroke to comprehensively image brain anatomy and geometry, mechanical properties, and brain deformations that arise from impulsive and harmonic skull loadings. The outcome of this work will be a publicly available dataset ( http://www.nitrc.org/projects/bbir ) that includes measurements on both males and females across an age range from adolescence to older adulthood. This article describes the rationale and approach for this study, the data available, and how these data may be used to develop new computational models and augment existing approaches; it will serve as a reference to researchers interested in using these data.
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Affiliation(s)
- Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO, USA.
| | - Ahmed Alshareef
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Andrew K Knutsen
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Kshitiz Upadhyay
- Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Ruth J Okamoto
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO, USA
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - John A Butman
- Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Dzung L Pham
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - K T Ramesh
- Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, USA
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, Newark, DE, USA.
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Li W, Wei Q, Hou Y, Lei D, Ai Y, Qin K, Yang J, Kemp GJ, Shang H, Gong Q. Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis. Transl Neurodegener 2021; 10:35. [PMID: 34511130 PMCID: PMC8436442 DOI: 10.1186/s40035-021-00255-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 08/01/2021] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVE There is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate. METHODS Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms. RESULTS Compared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small-worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%. CONCLUSION Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.
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Affiliation(s)
- Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Qianqian Wei
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Yanbing Hou
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Yuan Ai
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Graham J Kemp
- Department of Musculoskeletal and Ageing Science and MRC - Versus Arthritis Centre for Integrated Research Into Musculoskeletal Ageing, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
| | - Huifang Shang
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610000, China.
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Kraguljac NV, Anthony T, Morgan CJ, Jindal RD, Burger MS, Lahti AC. White matter integrity, duration of untreated psychosis, and antipsychotic treatment response in medication-naïve first-episode psychosis patients. Mol Psychiatry 2021; 26:5347-5356. [PMID: 32398721 PMCID: PMC7658031 DOI: 10.1038/s41380-020-0765-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 04/24/2020] [Accepted: 04/27/2020] [Indexed: 01/10/2023]
Abstract
It is becoming increasingly clear that longer duration of untreated psychosis (DUP) is associated with adverse clinical outcomes in patients with psychosis spectrum disorders. Because this association is often cited when justifying early intervention efforts, it is imperative to better understand underlying biological mechanisms. We enrolled 66 antipsychotic-naïve first-episode psychosis (FEP) patients and 45 matched healthy controls in this trial. At baseline, we used a human connectome style diffusion-weighted imaging (DWI) sequence to quantify white matter integrity in both groups. Patients then received 16 weeks of treatment with risperidone, 51 FEP completed the trial. We compared whole-brain fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), and radial diffusivity between groups. To test if structural white matter integrity mediates the relationship between longer DUP and poorer treatment response, we fit a mediator model and estimated indirect effects. We found decreased whole-brain FA and AD in medication-naive FEP compared with controls. In patients, lower FA was correlated with longer DUP (r = -0.32; p = 0.03) and poorer subsequent response to antipsychotic treatment (r = 0.40; p = 0.01). Importantly, we found a significant mediation effect for FA (indirect effect: -2.70; p = 0.03), indicating that DUP exerts its effects on treatment response through affecting white matter integrity. Our data provide empirical support to the idea the DUP may have fundamental pathogenic effects on the natural history of psychosis, suggest a biological mechanism underlying this phenomenon, and underscore the importance of early intervention efforts in this disabling neuropsychiatric syndrome.
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Affiliation(s)
- Nina Vanessa Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Thomas Anthony
- Department of Electrical and Computer Engineering/ IT Research Computing, University of Alabama at Birmingham
| | | | - Ripu Daman Jindal
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham,Department of Neurology, Birmingham VA Medical Center
| | - Mark Steven Burger
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham
| | - Adrienne Carol Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham
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Clark IA, Callaghan MF, Weiskopf N, Maguire EA, Mohammadi S. Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data. Front Neurosci 2021; 15:706473. [PMID: 34421526 PMCID: PMC8376472 DOI: 10.3389/fnins.2021.706473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022] Open
Abstract
Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.
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Affiliation(s)
- Ian A. Clark
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Eleanor A. Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Institute of Systems Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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Roos A, Wedderburn CJ, Fouche JP, Subramoney S, Joshi SH, Woods RP, Zar HJ, Narr KL, Stein DJ, Donald KA. Central white matter integrity alterations in 2-3-year-old children following prenatal alcohol exposure. Drug Alcohol Depend 2021; 225:108826. [PMID: 34182371 PMCID: PMC8299546 DOI: 10.1016/j.drugalcdep.2021.108826] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 05/05/2021] [Accepted: 05/06/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) remains a potentially preventable, but pervasive risk factor to neurodevelopment. Yet, evidence is lacking on the impact of alcohol on brain development in toddlers. This study aimed to investigate the impact of PAE on brain white matter integrity in 2-3-year-old children. METHODS Children (n = 83, 30-37 months old) of the Drakenstein Child Health Study birth cohort, underwent diffusion MRI on a 3 T Siemens scanner during natural sleep. Parameters were extracted in children with PAE (n = 25, 56 % boys) and unexposed controls (n = 58, 62 % boys) using Tract-based Spatial Statistics, and compared by group. The contribution of maternal tobacco smoking to white matter differences was also explored. RESULTS Children with PAE had altered fractional anisotropy, radial diffusivity and axial diffusivity in brain stem, limbic and association tracts compared to unexposed controls. Notably lower fractional anisotropy was found in the uncinate fasciculus, and lower mean and radial diffusivity were found in the fornix stria terminalis and corticospinal tract (FDR corrected p < 0.05). There was a significant interaction effect of PAE and prenatal tobacco exposure which lowered mean, radial and axial diffusivity in the corticospinal tract significantly in the PAE group but not controls. CONCLUSION Widespread altered white matter microstructural integrity at 2-3 years of age is consistent with findings in neonates in the same and other cohorts, indicating persistence of effects of PAE through early life. Findings also highlight that prenatal tobacco exposure impacts the association of PAE on white matter alterations, amplifying effects in tracts underlying motor function.
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Affiliation(s)
- Annerine Roos
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, South Africa; Department of Pediatrics and Child Health, University of Cape Town, South Africa; Neuroscience Institute, University of Cape Town, South Africa.
| | - Catherine J. Wedderburn
- Department of Pediatrics and Child Health, University of Cape Town, South Africa,Neuroscience Institute, University of Cape Town, South Africa,Department of Clinical Research, London School of Hygiene & Tropical Medicine, United Kingdom
| | - Jean-Paul Fouche
- Neuroscience Institute, University of Cape Town, South Africa,Department of Psychiatry and Mental Health, University of Cape Town, South Africa
| | - Sivenesi Subramoney
- Department of Pediatrics and Child Health, University of Cape Town, South Africa
| | - Shantanu H. Joshi
- Departments of Neurology and of Bioengineering, University of California, Los Angeles, USA
| | - Roger P. Woods
- Departments of Neurology and of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, USA
| | - Heather J. Zar
- Department of Pediatrics and Child Health, University of Cape Town, South Africa
| | - Katherine L. Narr
- Departments of Neurology and of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, USA
| | - Dan J. Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, South Africa,Neuroscience Institute, University of Cape Town, South Africa,Department of Psychiatry and Mental Health, University of Cape Town, South Africa
| | - Kirsten A. Donald
- Department of Pediatrics and Child Health, University of Cape Town, South Africa,Neuroscience Institute, University of Cape Town, South Africa
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Cai LY, Yang Q, Hansen CB, Nath V, Ramadass K, Johnson GW, Conrad BN, Boyd BD, Begnoche JP, Beason-Held LL, Shafer AT, Resnick SM, Taylor WD, Price GR, Morgan VL, Rogers BP, Schilling KG, Landman BA. PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images. Magn Reson Med 2021; 86:456-470. [PMID: 33533094 PMCID: PMC8387107 DOI: 10.1002/mrm.28678] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/19/2020] [Accepted: 12/22/2020] [Indexed: 12/31/2022]
Abstract
PURPOSE Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document. METHODS The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses. RESULTS Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets. CONCLUSIONS The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.
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Affiliation(s)
- Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Qi Yang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Colin B. Hansen
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Vishwesh Nath
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Benjamin N. Conrad
- Neuroscience Graduate Program, Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN, USA
| | - Brian D. Boyd
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Cognitive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John P. Begnoche
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Cognitive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lori L. Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Andrea T. Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Warren D. Taylor
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Cognitive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gavin R. Price
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN, USA
| | - Victoria L. Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Baxter P. Rogers
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Kurt G. Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Bennett A. Landman
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
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Freedberg M, Cunningham CA, Fioriti CM, Murillo J, Reeves JA, Taylor PA, Sarlls JE, Wassermann EM. Multiple parietal pathways are associated with rTMS-induced hippocampal network enhancement and episodic memory changes. Neuroimage 2021; 237:118199. [PMID: 34033914 DOI: 10.1016/j.neuroimage.2021.118199] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 05/19/2021] [Accepted: 05/21/2021] [Indexed: 11/29/2022] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) of the inferior parietal cortex (IPC) increases resting-state functional connectivity (rsFC) of the hippocampus with the precuneus and other posterior cortical areas and causes proportional improvement of episodic memory. The anatomical pathway(s) responsible for the propagation of these effects from the IPC is unknown and may not be direct. In order to assess the relative contributions of candidate pathways from the IPC to the MTL via the parahippocampal cortex and precuneus, to the effects of rTMS on rsFC and memory improvement, we used diffusion tensor imaging to measure the extent to which individual differences in fractional anisotropy (FA) in these pathways accounted for individual differences in response. FA in the IPC-parahippocampal pathway and several MTL pathways predicted changes in rsFC. FA in both parahippocampal and hippocampal pathways was related to changes in episodic, but not procedural, memory. These results implicate pathways to the MTL in the enhancing effect of parietal rTMS on hippocampal rsFC and memory.
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Affiliation(s)
- Michael Freedberg
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA.
| | - Catherine A Cunningham
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA
| | - Cynthia M Fioriti
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA.
| | - Jorge Murillo
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA.
| | - Jack A Reeves
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA.
| | - Paul A Taylor
- Scientific and Statistical Computing Core, NIMH, NIH, Bethesda, MD, USA.
| | | | - Eric M Wassermann
- Behavioral Neurology Unit, NINDS, 9000 Rockville Pike, 10 Center Drive, Rm. 7-5659, Bethesda 20892, MD, USA.
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Irfanoglu MO, Sadeghi N, Sarlls J, Pierpaoli C. Improved reproducibility of diffusion MRI of the human brain with a four-way blip-up and down phase-encoding acquisition approach. Magn Reson Med 2021; 85:2696-2708. [PMID: 33331068 PMCID: PMC7898925 DOI: 10.1002/mrm.28624] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 10/13/2020] [Accepted: 11/08/2020] [Indexed: 12/31/2022]
Abstract
PURPOSE To assess the effects of blip-up and -down echo planar imaging (EPI) acquisition designs, with different choices of phase-encoding directions (PEDs) on the reproducibility of diffusion MRI (dMRI)-derived metrics in the human brain. METHODS Diffusion MRI data in seven subjects were acquired five times, each with five different protocols. The base design included 64 diffusion directions acquired with anterior-posterior (AP) PED, the first and second protocols added reverse phase-encoded b = 0 s / mm 2 posterior-anterior (PA) PED images. The third one included 32 directions all with PED acquisitions with opposite polarity (AP and PA). The fourth protocol, also with 32 unique directions used four PEDs (AP, PA, right-left (RL), and left-right (LR)). The scan time was virtually identical for all protocols. The variability of diffusion MRI metrics for each subject and each protocol was computed across the different sessions. RESULTS The highest reproducibility for all dMRI metrics was obtained with protocol four (AP/PA-RL/LR, ie, four-way PED). Protocols that used only b = 0 s / mm 2 for distortion correction, which are the most widely used designs, had the lowest reproducibility. CONCLUSIONS An acquisition design with four PEDs, including all DWIs in addition to b = 0 s / mm 2 images should be used to achieve high reproducibility in diffusion MRI studies.
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Affiliation(s)
- M. Okan Irfanoglu
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthBethesdaMDUSA
| | - Neda Sadeghi
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthBethesdaMDUSA
| | - Joelle Sarlls
- NIH MRI Research Facility, National Institute of Neurological Disorders and StrokeNational Institutes of HealthBethesdaMDUSA
| | - Carlo Pierpaoli
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthBethesdaMDUSA
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Correcting Susceptibility Artifacts of MRI Sensors in Brain Scanning: A 3D Anatomy-Guided Deep Learning Approach. SENSORS 2021; 21:s21072314. [PMID: 33810289 PMCID: PMC8037307 DOI: 10.3390/s21072314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 01/02/2023]
Abstract
Echo planar imaging (EPI), a fast magnetic resonance imaging technique, is a powerful tool in functional neuroimaging studies. However, susceptibility artifacts, which cause misinterpretations of brain functions, are unavoidable distortions in EPI. This paper proposes an end-to-end deep learning framework, named TS-Net, for susceptibility artifact correction (SAC) in a pair of 3D EPI images with reversed phase-encoding directions. The proposed TS-Net comprises a deep convolutional network to predict a displacement field in three dimensions to overcome the limitation of existing methods, which only estimate the displacement field along the dominant-distortion direction. In the training phase, anatomical T1-weighted images are leveraged to regularize the correction, but they are not required during the inference phase to make TS-Net more flexible for general use. The experimental results show that TS-Net achieves favorable accuracy and speed trade-off when compared with the state-of-the-art SAC methods, i.e., TOPUP, TISAC, and S-Net. The fast inference speed (less than a second) of TS-Net makes real-time SAC during EPI image acquisition feasible and accelerates the medical image-processing pipelines.
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