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Milotta G, Corbin N, Lambert C, Lutti A, Mohammadi S, Callaghan MF. Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling. Magn Reson Med 2023; 89:128-143. [PMID: 36161672 PMCID: PMC9827921 DOI: 10.1002/mrm.29428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/08/2022] [Accepted: 08/08/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. METHODS We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically. RESULTS R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity. CONCLUSION We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.
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Affiliation(s)
- Giorgia Milotta
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
| | - Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536CNRS/University BordeauxBordeauxFrance
| | - Christian Lambert
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department for Clinical NeuroscienceLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Siawoosh Mohammadi
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
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Uddin MN, Figley TD, Kornelsen J, Mazerolle EL, Helmick CA, O'Grady CB, Pirzada S, Patel R, Carter S, Wong K, Essig MR, Graff LA, Bolton JM, Marriott JJ, Bernstein CN, Fisk JD, Marrie RA, Figley CR. The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines. FRONTIERS IN NEUROIMAGING 2022; 1:970385. [PMID: 37555178 PMCID: PMC10406313 DOI: 10.3389/fnimg.2022.970385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 08/10/2023]
Abstract
The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.
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Affiliation(s)
- Md Nasir Uddin
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Teresa D. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Erin L. Mazerolle
- Department of Psychology, St. Francis Xavier University, Antigonish, NS, Canada
| | - Carl A. Helmick
- Division of Geriatric Medicine, Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Christopher B. O'Grady
- Department of Anesthesia and Biomedical Translational Imaging Centre, Dalhousie University, Halifax, NS, Canada
| | - Salina Pirzada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ronak Patel
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sean Carter
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Kaihim Wong
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Marco R. Essig
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Lesley A. Graff
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James M. Bolton
- Department of Psychiatry, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James J. Marriott
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Charles N. Bernstein
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - John D. Fisk
- Nova Scotia Health Authority and the Departments of Psychiatry, Psychology and Neuroscience, and Medicine, Dalhousie University, Halifax, NS, Canada
| | - Ruth Ann Marrie
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chase R. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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Marrie RA, Patel R, Figley CR, Kornelsen J, Bolton JM, Graff LA, Mazerolle EL, Helmick C, Uddin MN, Figley TD, Marriott JJ, Bernstein CN, Fisk JD. Effects of Vascular Comorbidity on Cognition in Multiple Sclerosis Are Partially Mediated by Changes in Brain Structure. Front Neurol 2022; 13:910014. [PMID: 35685743 PMCID: PMC9170886 DOI: 10.3389/fneur.2022.910014] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/03/2022] [Indexed: 01/09/2023] Open
Abstract
ObjectiveVascular comorbidities are associated with reduced cognitive performance and with changes in brain structure in people with multiple sclerosis (MS). Understanding causal pathways is necessary to support the design of interventions to mitigate the impacts of comorbidities, and to monitor their effectiveness. We assessed the inter-relationships among vascular comorbidity, cognition and brain structure in people with MS.MethodsAdults with neurologist-confirmed MS reported comorbidities, and underwent assessment of their blood pressure, HbA1c, and cognitive functioning (i.e., Symbol Digit Modalities Test, California Verbal Learning Test, Brief Visuospatial Memory Test-Revised, and verbal fluency). Test scores were converted to age-, sex-, and education-adjusted z-scores. Whole brain magnetic resonance imaging (MRI) was completed, from which measures of thalamic and hippocampal volumes, and mean diffusivity of gray matter and normal-appearing white matter were converted to age and sex-adjusted z-scores. Canonical correlation analysis was used to identify linear combinations of cognitive measures (cognitive variate) and MRI measures (MRI variate) that accounted for the most correlation between the cognitive and MRI measures. Regression analyses were used to test whether MRI measures mediated the relationships between the number of vascular comorbidities and cognition measures.ResultsOf 105 participants, most were women (84.8%) with a mean (SD) age of 51.8 (12.8) years and age of symptom onset of 29.4 (10.5) years. Vascular comorbidity was common, with 35.2% of participants reporting one, 15.2% reporting two, and 8.6% reporting three or more. Canonical correlation analysis of the cognitive and MRI variables identified one pair of variates (Pillai's trace = 0.45, p = 0.0035). The biggest contributors to the cognitive variate were the SDMT and CVLT-II, and to the MRI variate were gray matter MD and thalamic volume. The correlation between cognitive and MRI variates was 0.50; these variates were used in regression analyses. On regression analysis, vascular comorbidity was associated with the MRI variate, and with the cognitive variate. After adjusting for the MRI variate, vascular comorbidity was not associated with the cognitive variate.ConclusionVascular comorbidity is associated with lower cognitive function in people with MS and this association is partially mediated via changes in brain macrostructure and microstructure.
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Affiliation(s)
- Ruth Ann Marrie
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Ruth Ann Marrie
| | - Ronak Patel
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chase R. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
| | - James M. Bolton
- Department of Psychiatry, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Lesley A. Graff
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Erin L. Mazerolle
- Department of Psychology, St. Francis Xavier University, Antigonish, NS, Canada
| | - Carl Helmick
- Department of Psychiatry and Division of Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
| | - Md Nasir Uddin
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, New York, NY, United States
| | - Teresa D. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James J. Marriott
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Charles N. Bernstein
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - John D. Fisk
- Nova Scotia Health and the Departments of Psychiatry, Psychology & Neuroscience, and Medicine, Dalhousie University, Halifax, NS, Canada
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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: 29] [Impact Index Per Article: 9.7] [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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Dauleac C, Bannier E, Cotton F, Frindel C. Effect of distortion corrections on the tractography quality in spinal cord diffusion-weighted imaging. Magn Reson Med 2021; 85:3241-3255. [PMID: 33475180 DOI: 10.1002/mrm.28665] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/03/2020] [Accepted: 12/10/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE To assess the impact of a different distortion correction (DC) method and patient geometry (sagittal balance) on the quality of spinal cord tractography rendering according to different tractography approaches. METHODS Forty-four adults free of spinal cord diseases underwent cervical diffusion-weighted imaging. The phase-encoding direction was head→foot. Sequence with opposed polarities (foot→head) was acquired to perform DC. Eddy-current, motion effects, and susceptibility artifact correction methods were used for DC, and two deterministic and one probabilistic tractography approaches were evaluated using MRtrix and DSI Studio tractography software. Fiber length and number of fibers were extracted to evaluate the quality of the tractography rendering. For each subject, cervical lordosis was measured to assess patient geometry. The angle between the main direction of the spinal cord and the orientation of the acquisition box were computed at each spine level to assess acquisition geometry and define an angle threshold for which a tractography of good quality is no longer possible. RESULTS There was a significant improvement in tractography quality after performing DC with susceptibility artifact correction using a deterministic approach based on tensor. Before DC, the angle threshold was defined at C6 (15.2°) compared with C7 (21.9°) after corrections, demonstrating the importance of spinal cord angulation for DC. CONCLUSION The impact of DC on tractography quality is greatly impacted by acquisition geometry. To obtain a good-quality tractography, we propose as a future perspective to adapt the acquisition geometry to that of the patient by automatically adjusting the acquisition box.
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Affiliation(s)
- Corentin Dauleac
- Department of Neurosurgery, Hôpital neurologique et neurochirurgical Pierre Wertheimer, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France
| | - Elise Bannier
- Université de Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn, France.,Department of Radiology, CHU de Rennes, Rennes, France
| | - François Cotton
- Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France.,Department of Radiology, Centre Hospitalier de Lyon Sud, Hospices Civils de Lyon, Lyon, France
| | - Carole Frindel
- Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France
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Longitudinal changes in DTI parameters of specific spinal white matter tracts correlate with behavior following spinal cord injury in monkeys. Sci Rep 2020; 10:17316. [PMID: 33057016 PMCID: PMC7560889 DOI: 10.1038/s41598-020-74234-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 09/23/2020] [Indexed: 12/27/2022] Open
Abstract
This study aims to evaluate how parameters derived from diffusion tensor imaging reflect axonal disruption and demyelination in specific white matter tracts within the spinal cord of squirrel monkeys following traumatic injuries, and their relationships to function and behavior. After a unilateral section of the dorsal white matter tract of the cervical spinal cord, we found that both lesioned dorsal and intact lateral tracts on the lesion side exhibited prominent disruptions in fiber orientation, integrity and myelination. The degrees of pathological changes were significantly more severe in segments below the lesion than above. The lateral tract on the opposite (non-injured) side was minimally affected by the injury. Over time, RD, FA, and AD values of the dorsal and lateral tracts on the injured side closely tracked measurements of the behavioral recovery. This unilateral section of the dorsal spinal tract provides a realistic model in which axonal disruption and demyelination occur together in the cord. Our data show that specific tract and segmental FA and RD values are sensitive to the effects of injury and reflect specific behavioral changes, indicating their potential as relevant indicators of recovery or for assessing treatment outcomes. These observations have translational value for guiding future studies of human subjects with spinal cord injuries.
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The ansa peduncularis in the human brain: A tractography and fiber dissection study. Brain Res 2020; 1746:146978. [PMID: 32535175 DOI: 10.1016/j.brainres.2020.146978] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/08/2020] [Accepted: 06/09/2020] [Indexed: 11/21/2022]
Abstract
INTRODUCTION The ansa peduncularis is a composite of white matter fiber bundles closely packed together that sweeps around the cerebral peduncle. The exact components of the ansa peduncularis and their anatomical trajectories are still not established firmly in the literature. OBJECTIVE The aim of this study was to examine the topographical anatomy of the ansa peduncularis and its subcomponents using the fiber dissection and tractography techniques. METHODS Ten formalin-fixed brains were prepared according to Klingler's method and dissected by the fiber dissection technique from the lateral, medial and inferior surfaces. The ansa peduncularis was also traced using high definition fiber tracking (HDFT) from the MRI data of twenty healthy adults and a 1021-subject template from the Human Connectome Project. RESULTS The ventral amygdalofugal pathway system includes white matter fiber bundles with a topographically close relation as they sweep around the cerebral peduncle and contribute to form the ansa peduncularis: amygdaloseptal fibers connect the amygdala and anterior temporal cortex to the septal region and amygdalohypothalamic fibers project from the amygdala to the hypothalamus. Additionally, from the amygdala and anterior temporal cortex, amygdalothalamic fibers project to the medial thalamic region. The ansa lenticularis, which connects the globus pallidus to the thalamus, was not shown in our study. CONCLUSION The study demonstrated the trajectory of the ansa peduncularis and its subcomponents, based on fiber dissection and tractography, improving our understanding of human brain anatomical connectivity.
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Tong Q, He H, Gong T, Li C, Liang P, Qian T, Sun Y, Ding Q, Li K, Zhong J. Reproducibility of multi-shell diffusion tractography on traveling subjects: A multicenter study prospective. Magn Reson Imaging 2019; 59:1-9. [PMID: 30797888 DOI: 10.1016/j.mri.2019.02.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 02/20/2019] [Accepted: 02/20/2019] [Indexed: 01/06/2023]
Abstract
Reproducibility of multicenter diffusion magnetic resonance imaging has drawn more attention recently due to rapidly increasing need for large-size brain imaging studies. Advanced multi-shell diffusion models are recommended for their potentials to provide variety of physio-pathological information. While previous studies have investigated the consistency of single-shell diffusion acquisition from various hardware and protocols, a well-controlled study with multi-shell acquisition would be necessary to understand the inherent factors of reproducibility from new complexity of such acquisition protocol. In this study, three traveling subjects were scanned at eight imaging centers equipped with the same type of scanners using the same multi-shell diffusion imaging protocol. Track density imaging and structure connectomes were investigated in local-scale distribution and in distal-scale connectivity, respectively. With evaluations of the coefficient of variation and the intra-class correlation coefficient, our results indicated: 1) similar to single-shell schemes, the intra-center reproducibility of multi-shell is higher than inter-center; 2) multi-shell schemes produce higher reproducibility and precision among centers compared to the single-shell schemes; and 3) in addition to the diffusion schemes, image quality and the presence of complex fiber structure could also associated with multicenter reproducibility.
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Affiliation(s)
- Qiqi Tong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Ting Gong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Chen Li
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Peipeng Liang
- School of Psychology, Capital Normal University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
| | - Tianyi Qian
- MR Collaboration NE Asia, Siemens Healthcare, Beijing, China.
| | - Yi Sun
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China.
| | - Qiuping Ding
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Kuncheng Li
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China; Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China; Department of Imaging Sciences, University of Rochester, Rochester, NY, USA.
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Huber E, David G, Thompson AJ, Weiskopf N, Mohammadi S, Freund P. Dorsal and ventral horn atrophy is associated with clinical outcome after spinal cord injury. Neurology 2018; 90:e1510-e1522. [PMID: 29592888 PMCID: PMC5921039 DOI: 10.1212/wnl.0000000000005361] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Accepted: 01/24/2018] [Indexed: 01/24/2023] Open
Abstract
OBJECTIVE To investigate whether gray matter pathology above the level of injury, alongside white matter changes, also contributes to sensorimotor impairments after spinal cord injury. METHODS A 3T MRI protocol was acquired in 17 tetraplegic patients and 21 controls. A sagittal T2-weighted sequence was used to characterize lesion severity. At the C2-3 level, a high-resolution T2*-weighted sequence was used to assess cross-sectional areas of gray and white matter, including their subcompartments; a diffusion-weighted sequence was used to compute voxel-based diffusion indices. Regression models determined associations between lesion severity and tissue-specific neurodegeneration and associations between the latter with neurophysiologic and clinical outcome. RESULTS Neurodegeneration was evident within the dorsal and ventral horns and white matter above the level of injury. Tract-specific neurodegeneration was associated with prolonged conduction of appropriate electrophysiologic recordings. Dorsal horn atrophy was associated with sensory outcome, while ventral horn atrophy was associated with motor outcome. White matter integrity of dorsal columns and corticospinal tracts was associated with daily-life independence. CONCLUSION Our results suggest that, next to anterograde and retrograde degeneration of white matter tracts, neuronal circuits within the spinal cord far above the level of injury undergo transsynaptic neurodegeneration, resulting in specific gray matter changes. Such improved understanding of tissue-specific cord pathology offers potential biomarkers with more efficient targeting and monitoring of neuroregenerative (i.e., white matter) and neuroprotective (i.e., gray matter) agents.
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Affiliation(s)
- Eveline Huber
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany
| | - Gergely David
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany
| | - Alan J Thompson
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany
| | - Nikolaus Weiskopf
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany
| | - Siawoosh Mohammadi
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany
| | - Patrick Freund
- From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany.
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10
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Shatil AS, Uddin MN, Matsuda KM, Figley CR. Quantitative Ex Vivo MRI Changes due to Progressive Formalin Fixation in Whole Human Brain Specimens: Longitudinal Characterization of Diffusion, Relaxometry, and Myelin Water Fraction Measurements at 3T. Front Med (Lausanne) 2018. [PMID: 29515998 PMCID: PMC5826187 DOI: 10.3389/fmed.2018.00031] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Purpose Postmortem MRI can be used to reveal important pathologies and establish radiology-pathology correlations. However, quantitative MRI values are altered by tissue fixation. Therefore, the purpose of this study was to investigate time-dependent effects of formalin fixation on MRI relaxometry (T1 and T2), diffusion tensor imaging (fractional anisotropy, FA; and mean diffusivity, MD), and myelin water fraction (MWF) measurements throughout intact human brain specimens. Methods Two whole, neurologically-healthy human brains were immersed in 10% formalin solution and scanned at 13 time points between 0 and 1,032 h. Whole-brain maps of longitudinal (T1) and transverse (T2) relaxation times, FA, MD, and MWF were generated at each time point to illustrate spatiotemporal changes, and region-of-interest analyses were then performed in eight brain structures to quantify temporal changes with progressive fixation. Results Although neither of the diffusion measures (FA nor MD) showed significant changes as a function of formalin fixation time, both T1 and T2-relaxation times significantly decreased, and MWF estimates significantly increased with progressive fixation until (and likely beyond) our final measurements were taken at 1,032 h. Conclusion These results suggest that T1-relaxation, T2-relaxation and MWF estimates must be performed quite early in the fixation process to avoid formalin-induced changes compared to in vivo values; and furthermore, that different ex vivo scans within an experiment must be acquired at consistent (albeit still early) fixation intervals to avoid fixative-related differences between samples. Conversely, ex vivo diffusion measures (FA and MD) appear to depend more on other factors (e.g., pulse sequence optimization, sample temperature, etc.).
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Affiliation(s)
- Anwar S Shatil
- Biomedical Engineering Graduate Program, University of Manitoba, Winnipeg, MB, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
| | - Md Nasir Uddin
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada.,Department of Radiology, University of Manitoba, Winnipeg, MB, Canada.,Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
| | - Kant M Matsuda
- Biomedical Engineering Graduate Program, University of Manitoba, Winnipeg, MB, Canada.,Department of Pathology, University of Manitoba, Winnipeg, MB, Canada
| | - Chase R Figley
- Biomedical Engineering Graduate Program, University of Manitoba, Winnipeg, MB, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada.,Department of Radiology, University of Manitoba, Winnipeg, MB, Canada.,Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada.,Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
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11
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Ellerbrock I, Mohammadi S. Four in vivo g-ratio-weighted imaging methods: Comparability and repeatability at the group level. Hum Brain Mapp 2018; 39:24-41. [PMID: 29091341 PMCID: PMC6866374 DOI: 10.1002/hbm.23858] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 10/11/2017] [Accepted: 10/16/2017] [Indexed: 12/18/2022] Open
Abstract
A recent method, denoted in vivo g-ratio-weighted imaging, has related the microscopic g-ratio, only accessible by ex vivo histology, to noninvasive MRI markers for the fiber volume fraction (FVF) and myelin volume fraction (MVF). Different MRI markers have been proposed for g-ratio weighted imaging, leaving open the question which combination of imaging markers is optimal. To address this question, the repeatability and comparability of four g-ratio methods based on different combinations of, respectively, two imaging markers for FVF (tract-fiber density, TFD, and neurite orientation dispersion and density imaging, NODDI) and two imaging markers for MVF (magnetization transfer saturation rate, MT, and, from proton density maps, macromolecular tissue volume, MTV) were tested in a scan-rescan experiment in two groups. Moreover, it was tested how the repeatability and comparability were affected by two key processing steps, namely the masking of unreliable voxels (e.g., due to partial volume effects) at the group level and the calibration value used to link MRI markers to MVF (and FVF). Our data showed that repeatability and comparability depend largely on the marker for the FVF (NODDI outperformed TFD), and that they were improved by masking. Overall, the g-ratio method based on NODDI and MT showed the highest repeatability (90%) and lowest variability between groups (3.5%). Finally, our results indicate that the calibration procedure is crucial, for example, calibration to a lower g-ratio value (g = 0.6) than the commonly used one (g = 0.7) can change not only repeatability and comparability but also the reported dependency on the FVF imaging marker. Hum Brain Mapp 39:24-41, 2018. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Isabel Ellerbrock
- Department of Systems NeuroscienceUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Siawoosh Mohammadi
- Department of Systems NeuroscienceUniversity Medical Center Hamburg‐EppendorfHamburgGermany
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12
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Bao Y, Wang Y, Wang W, Wang Y. The Superior Fronto-Occipital Fasciculus in the Human Brain Revealed by Diffusion Spectrum Imaging Tractography: An Anatomical Reality or a Methodological Artifact? Front Neuroanat 2017; 11:119. [PMID: 29321729 PMCID: PMC5733543 DOI: 10.3389/fnana.2017.00119] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Accepted: 11/27/2017] [Indexed: 12/23/2022] Open
Abstract
The existence of the superior fronto-occipital fasciculus (SFOF) in the human brain remains controversial. The aim of the present study was to clarify the existence, course, and terminations of the SFOF. High angular diffusion spectrum imaging (DSI) analysis was performed on six healthy adults and on a template of 842 subjects from the Human Connectome Project. To verify tractography results, we performed fiber microdissections of four post-mortem human brains. Based on DSI tractography, we reconstructed the SFOF in the subjects and the template from the Human Connectome Project that originated from the rostral and medial parts of the superior and middle frontal gyri. By tractography, we found that the fibers formed a compact fascicle at the level of the anterior horn of the lateral ventricle coursing above the head of caudate nucleus, medial to the corona radiate and under the corpus callosum (CC), and terminated at the parietal region via the lower part of the caudate nucleus. We consider that this fiber bundle observed by tractography is the SFOF, although it terminates mainly at the parietal region, rather than occipital lobe. By contrast, we were unable to identify a fiber bundle corresponding to the SFOF in our fiber dissection study. Although we did not provide definite evidence of the SFOF in the human brain, these findings may be useful for future studies in this field.
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Affiliation(s)
- Yue Bao
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yong Wang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Wei Wang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yibao Wang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China
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13
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Mohammadi S, Weiskopf N. [Computational neuroanatomy and microstructure imaging using magnetic resonance imaging]. DER NERVENARZT 2017; 88:839-849. [PMID: 28721539 DOI: 10.1007/s00115-017-0373-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Current computational neuroanatomy focuses on morphological measurements of the brain using standard magnetic resonance imaging (MRI) techniques. In comparison quantitative MRI (qMRI) typically provides a better tissue contrast and also greatly improves the sensitivity and specificity with respect to the microstructural characteristics of tissue. OBJECTIVE Current methodological developments in qMRI are presented, which go beyond morphology because this provides standardized measurements of the microstructure of the brain. The concept of in-vivo histology is introduced, based on biophysical modelling of qMRI data (hMRI) for determination of quantitative histology-like markers of the microstructure. RESULTS The qMRI metrics can be used as direct biomarkers of the microstructural mechanisms driving observed morphological findings. The hMRI metrics utilize biophysical models of the MRI signal in order to determine 3‑dimensional maps of histology-like measurements in the white matter. CONCLUSION Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both scientific and clinical applications. Both approaches improve the comparability across sites and time points, facilitate multicenter and longitudinal studies as well as standardized diagnostics. The hMRI is expected to shed new light on the relationship between brain microstructure, function and behavior both in health and disease. In the future hMRI will play an indispensable role in the field of computational neuroanatomy.
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Affiliation(s)
- S Mohammadi
- Institut für systemische Neurowissenschaften, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Deutschland
- Max-Planck-Institut für Kognitions- und Neurowissenschaften, Stephanstr. 1a, 04103, Leipzig, Deutschland
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, Großbritannien
| | - N Weiskopf
- Max-Planck-Institut für Kognitions- und Neurowissenschaften, Stephanstr. 1a, 04103, Leipzig, Deutschland.
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, Großbritannien.
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14
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Denoise diffusion-weighted images using higher-order singular value decomposition. Neuroimage 2017; 156:128-145. [PMID: 28416450 DOI: 10.1016/j.neuroimage.2017.04.017] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2016] [Revised: 02/22/2017] [Accepted: 04/06/2017] [Indexed: 11/21/2022] Open
Abstract
Noise usually affects the reliability of quantitative analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI), especially at high b-values and/or high spatial resolution. Higher-order singular value decomposition (HOSVD) has recently emerged as a simple, effective, and adaptive transform to exploit sparseness within multidimensional data. In particular, the patch-based HOSVD denoising has demonstrated superb performance when applied to T1-, T2-, and proton density-weighted MRI data. In this study, we aim to investigate the feasibility of denoising DW data using the HOSVD transform. With the low signal-to-noise ratio in typical DW data, the patch-based HOSVD denoising suffers from stripe artifacts in homogeneous regions because of the HOSVD bases learned from the noisy patches. To address this problem, we propose a novel denoising method. It first introduces a global HOSVD-based denoising as a prefiltering stage to guide the subsequent patch-based HOSVD denoising stage. The HOSVD bases from the patch groups in prefiltered images are then used to transform the noisy patch groups in original DW data. Experiments were performed using simulated and in vivo DW data. Results show that the proposed method significantly reduces stripe artifacts compared with conventional patch-based HOSVD denoising methods, and outperforms two state-of-the-art denoising methods in terms of denoising quality and diffusion parameters estimation.
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15
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Andersson JLR, Graham MS, Zsoldos E, Sotiropoulos SN. Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images. Neuroimage 2016; 141:556-572. [PMID: 27393418 DOI: 10.1016/j.neuroimage.2016.06.058] [Citation(s) in RCA: 430] [Impact Index Per Article: 53.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Revised: 05/25/2016] [Accepted: 06/30/2016] [Indexed: 12/13/2022] Open
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16
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Voxel-based analysis of grey and white matter degeneration in cervical spondylotic myelopathy. Sci Rep 2016; 6:24636. [PMID: 27095134 PMCID: PMC4837346 DOI: 10.1038/srep24636] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Accepted: 04/04/2016] [Indexed: 12/21/2022] Open
Abstract
In this prospective study, we made an unbiased voxel-based analysis to investigate above-stenosis spinal degeneration and its relation to impairment in patients with cervical spondylotic myelopathy (CSM). Twenty patients and 18 controls were assessed with high-resolution MRI protocols above the level of stenosis. Cross-sectional areas of grey matter (GM), white matter (WM), and posterior columns (PC) were measured to determine atrophy. Diffusion indices assessed tract-specific integrity of PC and lateral corticospinal tracts (CST). Regression analysis was used to reveal relationships between MRI measures and clinical impairment. Patients showed mainly sensory impairment. Atrophy was prominent within the cervical WM (13.9%, p = 0.004), GM (7.2%, p = 0.043), and PC (16.1%, p = 0.005). Fractional anisotropy (FA) was reduced in the PC (−11.98%, p = 0.006) and lateral CST (−12.96%, p = 0.014). In addition, radial (+28.47%, p = 0.014), axial (+14.72%, p = 0.005), and mean (+16.50%, p = 0.001) diffusivities were increased in the PC. Light-touch score was associated with atrophy (R2 = 0.3559, p = 0.020) and FA (z score 3.74, p = 0.003) in the PC, as was functional independence and FA in the lateral CST (z score 3.68, p = 0.020). This study demonstrates voxel-based degeneration far above the stenosis at a level not directly affected by the compression and provides unbiased readouts of tract-specific changes that relate to impairment.
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17
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Abstract
PURPOSE OF REVIEW Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.
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18
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Mohammadi S, Carey D, Dick F, Diedrichsen J, Sereno MI, Reisert M, Callaghan MF, Weiskopf N. Whole-Brain In-vivo Measurements of the Axonal G-Ratio in a Group of 37 Healthy Volunteers. Front Neurosci 2015; 9:441. [PMID: 26640427 PMCID: PMC4661323 DOI: 10.3389/fnins.2015.00441] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 11/03/2015] [Indexed: 12/13/2022] Open
Abstract
The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brain's prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf Hamburg, Germany ; Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, UK
| | - Daniel Carey
- Birkbeck/UCL Centre for NeuroImaging, Birkbeck College London, UK
| | - Fred Dick
- Birkbeck/UCL Centre for NeuroImaging, Birkbeck College London, UK
| | - Joern Diedrichsen
- UCL Institute of Cognitive Neurology, University College London London, UK
| | - Martin I Sereno
- Birkbeck/UCL Centre for NeuroImaging, Birkbeck College London, UK
| | - Marco Reisert
- Medical Physics, Department of Radiology, University Medical Center Freiburg Freiburg, Germany
| | - Martina F Callaghan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, UK
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, UK ; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
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19
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Kochunov P, Thompson PM, Winkler A, Morrissey M, Fu M, Coyle TR, Du X, Muellerklein F, Savransky A, Gaudiot C, Sampath H, Eskandar G, Jahanshad N, Patel B, Rowland L, Nichols TE, O'Connell JR, Shuldiner AR, Mitchell BD, Hong LE. The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects. Neuroimage 2015; 125:189-197. [PMID: 26499807 DOI: 10.1016/j.neuroimage.2015.10.050] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Revised: 10/16/2015] [Accepted: 10/18/2015] [Indexed: 01/01/2023] Open
Abstract
Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Paul M Thompson
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | | | - Mary Morrissey
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mao Fu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Thomas R Coyle
- Department of Psychology, University of Texas at San Antonio, San Antonio, TX, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Florian Muellerklein
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anya Savransky
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Christopher Gaudiot
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hemalatha Sampath
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - George Eskandar
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Binish Patel
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Laura Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan R Shuldiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD 21201, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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Abstract
We present an implementation of a recently developed noise reduction algorithm for dMRI data, called multi-shell position orientation adaptive smoothing (msPOAS), as a toolbox for SPM. The method intrinsically adapts to the structures of different size and shape in dMRI and hence avoids blurring typically observed in non-adaptive smoothing. We give examples for the usage of the toolbox and explain the determination of experiment-dependent parameters for an optimal performance of msPOAS.
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21
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Bianciardi M, Toschi N, Edlow BL, Eichner C, Setsompop K, Polimeni JR, Brown EN, Kinney HC, Rosen BR, Wald LL. Toward an In Vivo Neuroimaging Template of Human Brainstem Nuclei of the Ascending Arousal, Autonomic, and Motor Systems. Brain Connect 2015; 5:597-607. [PMID: 26066023 DOI: 10.1089/brain.2015.0347] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Brainstem nuclei (Bn) in humans play a crucial role in vital functions, such as arousal, autonomic homeostasis, sensory and motor relay, nociception, sleep, and cranial nerve function, and they have been implicated in a vast array of brain pathologies. However, an in vivo delineation of most human Bn has been elusive because of limited sensitivity and contrast for detecting these small regions using standard neuroimaging methods. To precisely identify several human Bn in vivo, we employed a 7 Tesla scanner equipped with multi-channel receive-coil array, which provided high magnetic resonance imaging sensitivity, and a multi-contrast (diffusion fractional anisotropy and T2-weighted) echo-planar-imaging approach, which provided complementary contrasts for Bn anatomy with matched geometric distortions and resolution. Through a combined examination of 1.3 mm(3) multi-contrast anatomical images acquired in healthy human adults, we semi-automatically generated in vivo probabilistic Bn labels of the ascending arousal (median and dorsal raphe), autonomic (raphe magnus, periaqueductal gray), and motor (inferior olivary nuclei, two subregions of the substantia nigra compatible with pars compacta and pars reticulata, two subregions of the red nucleus, and, in the diencephalon, two subregions of the subthalamic nucleus) systems. These labels constitute a first step toward the development of an in vivo neuroimaging template of Bn in standard space to facilitate future clinical and research investigations of human brainstem function and pathology. Proof-of-concept clinical use of this template is demonstrated in a minimally conscious patient with traumatic brainstem hemorrhages precisely localized to the raphe Bn involved in arousal.
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Affiliation(s)
- Marta Bianciardi
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Nicola Toschi
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
- 2 Medical Physics Section, Department of Biomedicine and Prevention, Faculty of Medicine, University of Rome "Tor Vergata ," Rome, Italy
| | - Brian L Edlow
- 3 Department of Neurology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Cornelius Eichner
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Kawin Setsompop
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Jonathan R Polimeni
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Emery N Brown
- 4 Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital , Boston, Massachusetts
| | - Hannah C Kinney
- 5 Department of Pathology, Boston Children's Hospital , Harvard Medical School, Boston, Massachusetts
| | - Bruce R Rosen
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
| | - Lawrence L Wald
- 1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging , Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, Massachusetts
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Mohammadi S, Tabelow K, Ruthotto L, Feiweier T, Polzehl J, Weiskopf N. High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing. Front Neurosci 2015; 8:427. [PMID: 25620906 PMCID: PMC4285740 DOI: 10.3389/fnins.2014.00427] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Accepted: 12/05/2014] [Indexed: 12/13/2022] Open
Abstract
Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g., intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2–3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1 mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view (rFoV) imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e., produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.
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Affiliation(s)
- Siawoosh Mohammadi
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK ; Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf Hamburg, Germany
| | - Karsten Tabelow
- Stochastic Algorithms and Nonparametric Statistics, Weierstrass Institute for Applied Analysis and Stochastics Berlin, Germany
| | - Lars Ruthotto
- Department of Earth, Ocean and Atmospheric Sciences, The University of British Columbia Vancouver, BC, Canada
| | | | - Jörg Polzehl
- Stochastic Algorithms and Nonparametric Statistics, Weierstrass Institute for Applied Analysis and Stochastics Berlin, Germany
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK
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Brain structural correlates of risk-taking behavior and effects of peer influence in adolescents. PLoS One 2014; 9:e112780. [PMID: 25389976 PMCID: PMC4229230 DOI: 10.1371/journal.pone.0112780] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 10/15/2014] [Indexed: 11/19/2022] Open
Abstract
Adolescents are characterized by impulsive risky behavior, particularly in the presence of peers. We discriminated high and low risk-taking male adolescents aged 18-19 years by assessing their propensity for risky behavior and vulnerability to peer influence with personality tests, and compared structural differences in gray and white matter of the brain with voxel-based morphometry (VBM) and diffusion tensor imaging (DTI), respectively. We also compared the brain structures according to the participants' actual risk-taking behavior in a simulated driving task with two different social conditions making up a peer competition situation. There was a discrepancy between the self-reported personality test results and risky driving behavior (running through an intersection with traffic lights turning yellow, chancing a collision with another vehicle). Comparison between high and low risk-taking adolescents according to personality test results revealed no significant difference in gray matter volume and white matter integrity. However, comparison according to actual risk-taking behavior during task performance revealed significantly higher white matter integrity in the high risk-taking group, suggesting that increased risky behavior during adolescence is not necessarily attributed to the immature brain as conventional wisdom says.
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Weiskopf N, Callaghan MF, Josephs O, Lutti A, Mohammadi S. Estimating the apparent transverse relaxation time (R2(*)) from images with different contrasts (ESTATICS) reduces motion artifacts. Front Neurosci 2014; 8:278. [PMID: 25309307 PMCID: PMC4159978 DOI: 10.3389/fnins.2014.00278] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 08/18/2014] [Indexed: 12/26/2022] Open
Abstract
Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2*, which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2* from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2* maps and reduced the coefficient of variation for both types of data—with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.
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Affiliation(s)
- Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK
| | - Martina F Callaghan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK
| | - Oliver Josephs
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK ; Birkbeck-UCL Centre for NeuroImaging London, UK
| | - Antoine Lutti
- Laboratoire de Recherche en Neuroimagerie, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois Lausanne, Switzerland
| | - Siawoosh Mohammadi
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK
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Zhang B, Xu Y, Zhu B, Kantarci K. The role of diffusion tensor imaging in detecting microstructural changes in prodromal Alzheimer's disease. CNS Neurosci Ther 2013; 20:3-9. [PMID: 24330534 DOI: 10.1111/cns.12166] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Revised: 07/23/2013] [Accepted: 07/23/2013] [Indexed: 12/13/2022] Open
Abstract
The MRI technique diffusion tensor imaging (DTI) is reviewed along with microstructural changes associated with prodromal Alzheimer's disease (AD) as a potential biomarker for clinical applications. The prodromal stage of AD is characterized by mild cognitive impairment (MCI), representing a transitional state between normal aging and AD. Microstructural abnormalities on DTI are promising in vivo biomarkers of gray and white matter changes associated with the progression of AD pathology. Elevated mean diffusivity and decreased fractional anisotropy are consistently found in prodromal AD, and even in cognitively normal elderly who progress to MCI. However, quality of parameter maps may be affected by artifacts of motion, susceptibility, and eddy current-induced distortions. The DTI maps are typically analyzed by region-of-interest or voxel-based analytic techniques such as tract-based spatial statistics. DTI-based index of diffusivity is complementary to macrostructural gray matter changes in the hippocampus in detecting prodromal AD. Breakdown of structural connectivity measured with DTI may impact cognitive performance during early AD. Furthermore, assessment of hippocampal connections may help in understanding the cerebral organization and remodeling associated with treatment response.
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Affiliation(s)
- Bing Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China; Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Advances in diffusion MRI acquisition and processing in the Human Connectome Project. Neuroimage 2013; 80:125-43. [PMID: 23702418 DOI: 10.1016/j.neuroimage.2013.05.057] [Citation(s) in RCA: 611] [Impact Index Per Article: 55.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2013] [Revised: 04/30/2013] [Accepted: 05/08/2013] [Indexed: 11/23/2022] Open
Abstract
The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013.
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Mohammadi S, Freund P, Feiweier T, Curt A, Weiskopf N. The impact of post-processing on spinal cord diffusion tensor imaging. Neuroimage 2013; 70:377-85. [PMID: 23298752 PMCID: PMC3605597 DOI: 10.1016/j.neuroimage.2012.12.058] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2012] [Revised: 12/20/2012] [Accepted: 12/22/2012] [Indexed: 01/19/2023] Open
Abstract
Diffusion tensor imaging (DTI) provides information about the microstructure in the brain and spinal cord. While new neuroimaging techniques have significantly advanced the accuracy and sensitivity of DTI of the brain, the quality of spinal cord DTI data has improved less. This is in part due to the small size of the spinal cord (ca. 1cm diameter) and more severe instrumental (e.g. eddy current) and physiological (e.g. cardiac pulsation) artefacts present in spinal cord DTI. So far, the improvements in image quality and resolution have resulted from cardiac gating and new acquisition approaches (e.g. reduced field-of-view techniques). The use of retrospective correction methods is not well established for spinal cord DTI. The aim of this paper is to develop an improved post-processing pipeline tailored for DTI data of the spinal cord with increased quality. For this purpose, we compared two eddy current and motion correction approaches using three-dimensional affine (3D-affine) and slice-wise registrations. We also introduced a new robust-tensor-fitting method that controls for whole-volume outliers. Although in general 3D-affine registration improves data quality, occasionally it can lead to misregistrations and biassed tensor estimates. The proposed robust tensor fitting reduced misregistration-related bias and yielded more reliable tensor estimates. Overall, the combination of slice-wise motion correction, eddy current correction, and robust tensor fitting yielded the best results. It increased the contrast-to-noise ratio (CNR) in FA maps by about 30% and reduced intra-subject variation in fractional anisotropy (FA) maps by 18%. The higher quality of FA maps allows for a better distinction between grey and white matter without increasing scan time and is compatible with any multi-directional DTI acquisition scheme.
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Affiliation(s)
- Siawoosh Mohammadi
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, UK.
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Nagy Z, Thomas DL, Weiskopf N. Orthogonalizing crusher and diffusion‐encoding gradients to suppress undesired echo pathways in the twice‐refocused spin echo diffusion sequence. Magn Reson Med 2013; 71:506-15. [DOI: 10.1002/mrm.24676] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Zoltán Nagy
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College LondonLondon UK
| | - David L. Thomas
- Department of Brain Repair and RehabilitationUCL Institute of NeurologyUniversity College LondonLondon UK
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College LondonLondon UK
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