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Maldonado IL, Descoteaux M, Rheault F, Zemmoura I, Benn A, Margulies D, Boré A, Duffau H, Mandonnet E. Multimodal study of multilevel pulvino-temporal connections: a new piece in the puzzle of lexical retrieval networks. Brain 2024; 147:2245-2257. [PMID: 38243610 PMCID: PMC11146422 DOI: 10.1093/brain/awae021] [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: 06/19/2023] [Revised: 11/18/2023] [Accepted: 12/30/2023] [Indexed: 01/21/2024] Open
Abstract
Advanced methods of imaging and mapping the healthy and lesioned brain have allowed for the identification of the cortical nodes and white matter tracts supporting the dual neurofunctional organization of language networks in a dorsal phonological and a ventral semantic stream. Much less understood are the anatomical correlates of the interaction between the two streams; one hypothesis being that of a subcortically mediated interaction, through crossed cortico-striato-thalamo-cortical and cortico-thalamo-cortical loops. In this regard, the pulvinar is the thalamic subdivision that has most regularly appeared as implicated in the processing of lexical retrieval. However, descriptions of its connections with temporal (language) areas remain scarce. Here we assess this pulvino-temporal connectivity using a combination of state-of-the-art techniques: white matter stimulation in awake surgery and postoperative diffusion MRI (n = 4), virtual dissection from the Human Connectome Project 3 and 7 T datasets (n = 172) and operative microscope-assisted post-mortem fibre dissection (n = 12). We demonstrate the presence of four fundamental fibre contingents: (i) the anterior component (Arnold's bundle proper) initially described by Arnold in the 19th century and destined to the anterior temporal lobe; (ii) the optic radiations-like component, which leaves the pulvinar accompanying the optical radiations and reaches the posterior basal temporal cortices; (iii) the lateral component, which crosses the temporal stem orthogonally and reaches the middle temporal gyrus; and (iv) the auditory radiations-like component, which leaves the pulvinar accompanying the auditory radiations to the superomedial aspect of the temporal operculum, just posteriorly to Heschl's gyrus. Each of those components might correspond to a different level of information processing involved in the lexical retrieval process of picture naming.
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Affiliation(s)
- Igor Lima Maldonado
- UMR 1253, iBrain, Université de Tours, Inserm, 37000 Tours, France
- Department of Neurosurgery, CHRU de Tours, 37000 Tours, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory, Department of Computer Science, Faculty of Sciences, Université de Sherbrooke, J1K 2X9 Sherbrooke, Quebec, Canada
- Imeka Solutions, J1H 4A7 Sherbrooke, Quebec, Canada
| | | | - Ilyess Zemmoura
- UMR 1253, iBrain, Université de Tours, Inserm, 37000 Tours, France
- Department of Neurosurgery, CHRU de Tours, 37000 Tours, France
| | - Austin Benn
- CNRS, Integrative Neuroscience and Cognition Center (UMR 8002), Université de Paris Cité, 75006 Paris, France
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX1 3QD Oxford, UK
| | - Daniel Margulies
- CNRS, Integrative Neuroscience and Cognition Center (UMR 8002), Université de Paris Cité, 75006 Paris, France
| | - Arnaud Boré
- Sherbrooke Connectivity Imaging Laboratory, Department of Computer Science, Faculty of Sciences, Université de Sherbrooke, J1K 2X9 Sherbrooke, Quebec, Canada
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, 34090 Montpellier, France
- Team ‘Plasticity of Central Nervous System, Stem Cells and Glial Tumors’, U1191 Laboratory, Institute of Functional Genomics, National Institute for Health and Medical Research (INSERM), University of Montpellier, 34000, Montpellier, France
| | - Emmanuel Mandonnet
- Department of Neurosurgery, Lariboisière Hospital, AP-HP, 75010 Paris, France
- Frontlab, CNRS UMR 7225, INSERM U1127, Paris Brain Institute (ICM), 75013 Paris, France
- UFR Médecine, Université de Paris Cité, 75006 Paris, France
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2
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Brunfeldt AT, Bregman BS, Lum PS. Responsiveness to exoskeleton loading during bimanual reaching is associated with corticospinal tract integrity in stroke. Front Neurosci 2024; 18:1348103. [PMID: 38500483 PMCID: PMC10944900 DOI: 10.3389/fnins.2024.1348103] [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: 12/01/2023] [Accepted: 01/30/2024] [Indexed: 03/20/2024] Open
Abstract
Background Device-based rehabilitation of upper extremity impairment following stroke often employs one-sized-fits-all approaches that do not account for individual differences in patient characteristics. Objective Determine if corticospinal tract lesion load could explain individual differences in the responsiveness to exoskeleton loading of the arms in chronic stroke participants. Methods Fourteen stroke participants performed a bimanual shared cursor reaching task in virtual reality while exoskeletons decreased the effective weight of the more-impaired arm and increased the effective weight of the less-impaired arm. We calculated the change in relative displacement between the arms (RC) and the change in relative muscle activity (MC) between the arms from the biceps and deltoids. We calculated corticospinal tract lesion load (wCSTLL) in a subset of 10 participants. Results Exoskeleton loading did not change RC (p = 0.07) or MC (p = 0.47) at the group level, but significant individual differences emerged. Participants with little overlap between the lesion and corticospinal tract responded to loading by decreasing muscle activity in the more-impaired arm relative to the less-impaired arm. The change in deltoid MC was associated with smaller wCSTLL (R2 = 0.43, p = 0.039); there was no such relationship for biceps MC (R2 < 0.001, p = 0.98). Conclusion Here we provide evidence that corticospinal tract integrity is a critical feature that determines one's ability to respond to upper extremity exoskeleton loading. Our work contributes to the development of personalized device-based interventions that would allow clinicians and researchers to titrate constraint levels during bimanual activities.
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Affiliation(s)
- Alexander T. Brunfeldt
- Department of Rehabilitation Medicine, Georgetown University Medical Center, Washington, DC, United States
- MedStar National Rehabilitation Network, Washington, DC, United States
- Department of Biomedical Engineering, The Catholic University of America, Washington, DC, United States
| | - Barbara S. Bregman
- Department of Rehabilitation Medicine, Georgetown University Medical Center, Washington, DC, United States
- MedStar National Rehabilitation Network, Washington, DC, United States
| | - Peter S. Lum
- Department of Biomedical Engineering, The Catholic University of America, Washington, DC, United States
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Tan S, Faull RLM, Curtis MA. The tracts, cytoarchitecture, and neurochemistry of the spinal cord. Anat Rec (Hoboken) 2023; 306:777-819. [PMID: 36099279 DOI: 10.1002/ar.25079] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/01/2022] [Accepted: 09/11/2022] [Indexed: 11/06/2022]
Abstract
The human spinal cord can be described using a range of nomenclatures with each providing insight into its structure and function. Here we have comprehensively reviewed the key literature detailing the general structure, configuration of tracts, the cytoarchitecture of Rexed's laminae, and the neurochemistry at the spinal segmental level. The purpose of this review is to detail current anatomical understanding of how the spinal cord is structured and to aid researchers in identifying gaps in the literature that need to be studied to improve our knowledge of the spinal cord which in turn will improve the potential of therapeutic intervention for disorders of the spinal cord.
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Affiliation(s)
- Sheryl Tan
- Centre for Brain Research and Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Richard L M Faull
- Centre for Brain Research and Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Maurice A Curtis
- Centre for Brain Research and Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
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Generative Sampling in Bundle Tractography using Autoencoders (GESTA). Med Image Anal 2023; 85:102761. [PMID: 36773366 DOI: 10.1016/j.media.2023.102761] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 01/11/2023] [Accepted: 01/24/2023] [Indexed: 02/04/2023]
Abstract
Current tractography methods use the local orientation information to propagate streamlines from seed locations. Many such seeds provide streamlines that stop prematurely or fail to map the true white matter pathways because some bundles are "harder-to-track" than others. This results in tractography reconstructions with poor white and gray matter spatial coverage. In this work, we propose a generative, autoencoder-based method, named GESTA (Generative Sampling in Bundle Tractography using Autoencoders), that produces streamlines achieving better spatial coverage. Compared to other deep learning methods, our autoencoder-based framework uses a single model to generate streamlines in a bundle-wise fashion, and does not require to propagate local orientations. GESTA produces new and complete streamlines for any given white matter bundle, including hard-to-track bundles. Applied on top of a given tractogram, GESTA is shown to be effective in improving the white matter volume coverage in poorly populated bundles, both on synthetic and human brain in vivo data. Our streamline evaluation framework ensures that the streamlines produced by GESTA are anatomically plausible and fit well to the local diffusion signal. The streamline evaluation criteria assess anatomy (white matter coverage), local orientation alignment (direction), and geometry features of streamlines, and optionally, gray matter connectivity. The GESTA framework offers considerable gains in bundle overlap using a reduced set of seeding streamlines with a 1.5x improvement for the "Fiber Cup", and 6x for the ISMRM 2015 Tractography Challenge datasets. Similarly, it provides a 4x white matter volume increase on the BIL&GIN callosal homotopic dataset, and successfully populates bundles on the multi-subject, multi-site, whole-brain in vivo TractoInferno dataset. GESTA is thus a novel deep generative bundle tractography method that can be used to improve the tractography reconstruction of the white matter.
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5
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Wang YR, Lefebvre G, Picard M, Lamoureux-Andrichuk A, Ferland MC, Therrien-Blanchet JM, Boré A, Tremblay J, Descoteaux M, Champoux F, Théoret H. Physiological, Anatomical and Metabolic Correlates of Aerobic Fitness in Human Primary Motor Cortex: A Multimodal Study. Neuroscience 2023; 517:70-83. [PMID: 36921757 DOI: 10.1016/j.neuroscience.2023.03.007] [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: 12/13/2022] [Revised: 01/29/2023] [Accepted: 03/07/2023] [Indexed: 03/16/2023]
Abstract
Physical activity (PA) has been shown to benefit various cognitive functions and promote neuroplasticity. Whereas the effects of PA on brain anatomy and function have been well documented in older individuals, data are scarce in young adults. Whether high levels of cardiorespiratory fitness (CRF) achieved through regular PA are associated with significant structural and functional changes in this age group remains largely unknown. In the present study, twenty young adults that engaged in at least 8 hours per week of aerobic exercise during the last 5 years were compared to twenty sedentary controls on measures of cortical excitability, white matter microstructure, cortical thickness and metabolite concentration. All measures were taken in the left primary motor cortex and CRF was assessed with VO2max. Transcranial magnetic stimulation (TMS) revealed higher corticospinal excitability in high- compared to low-fit individuals reflected by greater input/output curve amplitude and slope. No group differences were found for other TMS (short-interval intracortical inhibition and intracortical facilitation), diffusion MRI (fractional anisotropy and apparent fiber density), structural MRI (cortical thickness) and magnetic resonance spectroscopy (NAA, GABA, Glx) measures. Taken together, the present data suggest that brain changes associated with increased CRF are relatively limited, at least in primary motor cortex, in contrast to what has been observed in older adults.
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Affiliation(s)
- Yi Ran Wang
- Département de psychologie, Université de Montréal, Montréal, Québec, Canada; Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Québec, Canada
| | - Geneviève Lefebvre
- Département de psychologie, Université de Montréal, Montréal, Québec, Canada
| | - Maude Picard
- Département de psychologie, Université de Montréal, Montréal, Québec, Canada
| | | | | | | | - Arnaud Boré
- Sherbrooke Connectivity Imaging Lab, Université de Sherbrooke, Sherbrooke, Canada
| | - Jonathan Tremblay
- École de kinésiologie et des sciences de l'activité physique, Université de Montréal, Montréal, Québec, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Université de Sherbrooke, Sherbrooke, Canada
| | - François Champoux
- École d'Orthophonie et d'Audiologie, Université de Montréal, Montréal, QC, Canada
| | - Hugo Théoret
- Département de psychologie, Université de Montréal, Montréal, Québec, Canada.
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Kikuchi H, Jitsuishi T, Hirono S, Yamaguchi A, Iwadate Y. 2D and 3D structures of the whole-brain, directly visible from 100-micron slice 7TMRI images. INTERDISCIPLINARY NEUROSURGERY 2023. [DOI: 10.1016/j.inat.2023.101755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
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7
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Renauld E, Théberge A, Petit L, Houde JC, Descoteaux M. Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system. Sci Rep 2023; 13:2347. [PMID: 36759653 PMCID: PMC9911766 DOI: 10.1038/s41598-023-28560-w] [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: 12/24/2022] [Accepted: 01/20/2023] [Indexed: 02/11/2023] Open
Abstract
Since 2015, research groups have sought to produce the ne plus ultra of tractography algorithms using the ISMRM 2015 Tractography Challenge as evaluation. In particular, since 2017, machine learning has made its entrance into the tractography world. The ISMRM 2015 Tractography Challenge is the most used phantom during tractography validation, although it contains limitations. Here, we offer a new scoring system for this phantom, where segmentation of the bundles is now based on manually defined regions of interest rather than on bundle recognition. Bundles are now more reliably segmented, offering more representative metrics for future users. New code is available online. Scores of the initial 96 submissions to the challenge are updated. Overall, conclusions from the 2015 challenge are confirmed with the new scoring, but individual tractogram scores have changed, and the data is much improved at the bundle- and streamline-level. This work also led to the production of a ground truth tractogram with less broken or looping streamlines and of an example of processed data, all available on the Tractometer website. This enhanced scoring system and new data should continue helping researchers develop and evaluate the next generation of tractography techniques.
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Affiliation(s)
- Emmanuelle Renauld
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada.
| | - Antoine Théberge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada
| | - Laurent Petit
- Université de Bordeaux, CNRS, CEA, IMN, GIN, UMR 5293, 33000, Bordeaux, France
| | | | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada.,Imeka Solutions Inc, Sherbrooke, QC, Canada
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8
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The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography. Brain Struct Funct 2023; 228:103-120. [PMID: 35995880 DOI: 10.1007/s00429-022-02551-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 08/03/2022] [Indexed: 01/07/2023]
Abstract
The angular gyrus (AG) has been described in numerous studies to be consistently activated in various functional tasks. The angular gyrus is a critical connector epicenter linking multiple functional networks due to its location in the posterior part of the inferior parietal cortex, namely at the junction between the parietal, temporal, and occipital lobes. It is thus crucial to identify the different pathways that anatomically connect this high-order association region to the rest of the brain. Our study revisits the three-dimensional architecture of the structural AG connectivity by combining state-of-the-art postmortem blunt microdissection with advanced in vivo diffusion tractography to comprehensively describe the association, projection, and commissural fibers that connect the human angular gyrus. AG appears as a posterior "angular stone" of associative connections belonging to mid- and long-range dorsal and ventral fibers of the superior and inferior longitudinal systems, respectively, to short-range parietal, occipital, and temporal fibers, including U-shaped fibers in the posterior transverse system. Thus, AG is at a pivotal dorso-ventral position reflecting its critical role in the different functional networks, particularly in language elaboration and spatial attention and awareness in the left and right hemispheres, respectively. We also reveal striatal, thalamic, and brainstem connections and a typical inter-hemispheric homotopic callosal connectivity supporting the suggested AG role in the integration of sensory input for modulating motor control and planning. The present description of AG's highly distributed wiring diagram may drastically improve intraoperative subcortical testing and post-operative neurologic outcomes related to surgery in and around the angular gyrus.
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Rheault F, Schilling KG, Obaid S, Begnoche JP, Cutting LE, Descoteaux M, Landman BA, Petit L. The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow. Brain Struct Funct 2022; 227:2191-2207. [PMID: 35672532 PMCID: PMC9884471 DOI: 10.1007/s00429-022-02518-6] [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: 03/01/2022] [Accepted: 05/22/2022] [Indexed: 01/31/2023]
Abstract
Efficient communication across fields of research is challenging, especially when they are at opposite ends of the physical and digital spectrum. Neuroanatomy and neuroimaging may seem close to each other. When neuroimaging studies try to isolate structures of interest, according to a specific anatomical definition, a variety of challenges emerge. It is a non-trivial task to convert the neuroanatomical knowledge to instructions and rules to be executed in neuroimaging software. In the process called "virtual dissection" used to isolate coherent white matter structure in tractography, each white matter pathway has its own set of landmarks (regions of interest) used as inclusion and exclusion criteria. The ability to segment and study these pathways is critical for scientific progress, yet, variability may depend on region placement, and be influenced by the person positioning the region (i.e., a rater). When raters' variability is taken into account, the impact made by each region of interest becomes even more difficult to interpret. A delicate balance between anatomical validity, impact on the virtual dissection and raters' reproducibility emerge. In this work, we investigate this balance by leveraging manual delineation data of a group of raters from a previous study to quantify which set of landmarks and criteria contribute most to variability in virtual dissection. To supplement our analysis, the variability of each pathway with a region-by-region exploration was performed. We present a detailed exploration and description of each region, the causes of variability and its impacts. Finally, we provide a brief overview of the lessons learned from our previous virtual dissection projects and propose recommendations for future virtual dissection protocols as well as perspectives to reach better community agreement when it comes to anatomical definitions of white matter pathways.
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Affiliation(s)
- Francois Rheault
- Electrical and Computer Engineering, Vanderbilt University, Nashville, USA
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging, Nashville, USA,Department of Radiology and Radiological Science, Vanderbilt University Medical Center, Nashville, USA
| | - Sami Obaid
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d’Informatique, Université de Sherbrooke, Sherbrooke, Canada,Health Center Research Center, University of Montreal, Montreal, Canada
| | - John P. Begnoche
- The Center for Cognitive Medicine, Department of Psychiatry, Vanderbilt University Medical Center, Nashville, USA
| | - Laurie E. Cutting
- Vanderbilt Kennedy Center, University Medical Center, VanderbiltNashville, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d’Informatique, Université de Sherbrooke, Sherbrooke, Canada
| | - Bennett A. Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, USA,Vanderbilt University Institute of Imaging, Nashville, USA,Department of Radiology and Radiological Science, Vanderbilt University Medical Center, Nashville, USA,Computer Science, Vanderbilt University, Nashville, USA
| | - Laurent Petit
- Groupe d’Imagerie Neurofonctionnelle, Institut Des Maladies Neurodégénératives, CNRS, CEA University of Bordeaux, Bordeaux, France
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Weiss Lucas C, Faymonville AM, Loução R, Schroeter C, Nettekoven C, Oros-Peusquens AM, Langen KJ, Shah NJ, Stoffels G, Neuschmelting V, Blau T, Neuschmelting H, Hellmich M, Kocher M, Grefkes C, Goldbrunner R. Surgery of Motor Eloquent Glioblastoma Guided by TMS-Informed Tractography: Driving Resection Completeness Towards Prolonged Survival. Front Oncol 2022; 12:874631. [PMID: 35692752 PMCID: PMC9186060 DOI: 10.3389/fonc.2022.874631] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 03/21/2022] [Indexed: 12/13/2022] Open
Abstract
Background Surgical treatment of patients with glioblastoma affecting motor eloquent brain regions remains critically discussed given the risk–benefit dilemma of prolonging survival at the cost of motor-functional damage. Tractography informed by navigated transcranial magnetic stimulation (nTMS-informed tractography, TIT) provides a rather robust estimate of the individual location of the corticospinal tract (CST), a highly vulnerable structure with poor functional reorganisation potential. We hypothesised that by a more comprehensive, individualised surgical decision-making using TIT, tumours in close relationship to the CST can be resected with at least equal probability of gross total resection (GTR) than less eloquently located tumours without causing significantly more gross motor function harm. Moreover, we explored whether the completeness of TIT-aided resection translates to longer survival. Methods A total of 61 patients (median age 63 years, m = 34) with primary glioblastoma neighbouring or involving the CST were operated on between 2010 and 2015. TIT was performed to inform surgical planning in 35 of the patients (group T; vs. 26 control patients). To achieve largely unconfounded group comparisons for each co-primary outcome (i.e., gross-motor functional worsening, GTR, survival), (i) uni- and multivariate regression analyses were performed to identify features of optimal outcome prediction; (ii), optimal propensity score matching (PSM) was applied to balance those features pairwise across groups, followed by (iii) pairwise group comparison. Results Patients in group T featured a significantly higher lesion-CST overlap compared to controls (8.7 ± 10.7% vs. 3.8 ± 5.7%; p = 0.022). The frequency of gross motor worsening was higher in group T, albeit non-significant (n = 5/35 vs. n = 0/26; p = 0.108). PSM-based paired-sample comparison, controlling for the confounders of preoperative tumour volume and vicinity to the delicate vasculature of the insula, showed higher GTR rates in group T (77% vs. 69%; p = 0.025), particularly in patients with a priori intended GTR (87% vs. 78%; p = 0.003). This translates into a prolonged PFS in the same PSM subgroup (8.9 vs. 5.8 months; p = 0.03), with GTR representing the strongest predictor of PFS (p = 0.001) and OS (p = 0.0003) overall. Conclusion The benefit of TIT-aided GTR appears to overcome the drawbacks of potentially elevated motor functional risk in motor eloquent tumour localisation, leading to prolonged survival of patients with primary glioblastoma close to the CST.
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Affiliation(s)
- Carolin Weiss Lucas
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Andrea Maria Faymonville
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Neurosurgery, University Hospital Mannheim, Mannheim, Germany
| | - Ricardo Loução
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Stereotaxy and Functional Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Catharina Schroeter
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Charlotte Nettekoven
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | - Karl Josef Langen
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany.,JARA - BRAIN - Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Volker Neuschmelting
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Tobias Blau
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,Institute of Neuropathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Hannah Neuschmelting
- Institute of Pathology and Neuropathology, University Hospital Essen, Essen, Germany
| | - Martin Hellmich
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Martin Kocher
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Stereotaxy and Functional Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Christian Grefkes
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany.,Institute for Medical Statistics and Computational Biology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Roland Goldbrunner
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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11
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Rheault F, Schilling KG, Valcourt‐Caron A, Théberge A, Poirier C, Grenier G, Guberman GI, Begnoche J, Legarreta JH, Y. Cai L, Roy M, Edde M, Caceres MP, Ocampo‐Pineda M, Al‐Sharif N, Karan P, Bontempi P, Obaid S, Bosticardo S, Schiavi S, Sairanen V, Daducci A, Cutting LE, Petit L, Descoteaux M, Landman BA. Tractostorm 2: Optimizing tractography dissection reproducibility with segmentation protocol dissemination. Hum Brain Mapp 2022; 43:2134-2147. [PMID: 35141980 PMCID: PMC8996349 DOI: 10.1002/hbm.25777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/19/2021] [Accepted: 12/31/2021] [Indexed: 11/29/2022] Open
Abstract
The segmentation of brain structures is a key component of many neuroimaging studies. Consistent anatomical definitions are crucial to ensure consensus on the position and shape of brain structures, but segmentations are prone to variation in their interpretation and execution. White-matter (WM) pathways are global structures of the brain defined by local landmarks, which leads to anatomical definitions being difficult to convey, learn, or teach. Moreover, the complex shape of WM pathways and their representation using tractography (streamlines) make the design and evaluation of dissection protocols difficult and time-consuming. The first iteration of Tractostorm quantified the variability of a pyramidal tract dissection protocol and compared results between experts in neuroanatomy and nonexperts. Despite virtual dissection being used for decades, in-depth investigations of how learning or practicing such protocols impact dissection results are nonexistent. To begin to fill the gap, we evaluate an online educational tractography course and investigate the impact learning and practicing a dissection protocol has on interrater (groupwise) reproducibility. To generate the required data to quantify reproducibility across raters and time, 20 independent raters performed dissections of three bundles of interest on five Human Connectome Project subjects, each with four timepoints. Our investigation shows that the dissection protocol in conjunction with an online course achieves a high level of reproducibility (between 0.85 and 0.90 for the voxel-based Dice score) for the three bundles of interest and remains stable over time (repetition of the protocol). Suggesting that once raters are familiar with the software and tasks at hand, their interpretation and execution at the group level do not drastically vary. When compared to previous work that used a different method of communication for the protocol, our results show that incorporating a virtual educational session increased reproducibility. Insights from this work may be used to improve the future design of WM pathway dissection protocols and to further inform neuroanatomical definitions.
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Affiliation(s)
- Francois Rheault
- Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Kurt G. Schilling
- Vanderbilt University Institute of ImagingNashvilleTennesseeUSA
- Department of Radiology and Radiological ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Alex Valcourt‐Caron
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Antoine Théberge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
- Videos and Images Theory and Analytics Laboratory (VITAL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Charles Poirier
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Gabrielle Grenier
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Guido I. Guberman
- Department of Neurology and Neurosurgery, Faculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - John Begnoche
- The Center for Cognitive Medicine, Department of PsychiatryVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jon Haitz Legarreta
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
- Videos and Images Theory and Analytics Laboratory (VITAL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Leon Y. Cai
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Maggie Roy
- Research Center on AgingUniversité de SherbrookeSherbrookeQuébecCanada
| | - Manon Edde
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Marco Perez Caceres
- Département de Radiologie DiagnostiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Mario Ocampo‐Pineda
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's HospitalHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Noor Al‐Sharif
- McGill Centre for Integrative Neuroscience (MCIN)McGill UniversityMontrealQuébecCanada
| | - Philippe Karan
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Pietro Bontempi
- Department of Neurosciences, Biomedicine and Movement SciencesUniversity of VeronaVeronaItaly
| | - Sami Obaid
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
- University of Montreal, Health Center Research CenterMontrealCanada
| | - Sara Bosticardo
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's HospitalHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Simona Schiavi
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's HospitalHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Viljami Sairanen
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's HospitalHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Alessandro Daducci
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's HospitalHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Laurie E. Cutting
- Vanderbilt Kennedy CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Laurent Petit
- Groupe d'imagerie neurofonctionnelleCNRS, CEA, IMN, University of BordeauxBordeauxFrance
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d'InformatiqueUniversité de SherbrookeSherbrookeQuébecCanada
| | - Bennett A. Landman
- Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
- Vanderbilt University Institute of ImagingNashvilleTennesseeUSA
- Department of Radiology and Radiological ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
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12
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Yang Q, Hansen CB, Cai LY, Rheault F, Lee HH, Bao S, Chandio BQ, Williams O, Resnick SM, Garyfallidis E, Anderson AW, Descoteaux M, Schilling KG, Landman BA. Learning white matter subject-specific segmentation from structural MRI. Med Phys 2022; 49:2502-2513. [PMID: 35090192 PMCID: PMC9053869 DOI: 10.1002/mp.15495] [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: 01/24/2021] [Revised: 12/20/2021] [Accepted: 01/10/2022] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Mapping brain white matter (WM) is essential for building an understanding of brain anatomy and function. Tractography-based methods derived from diffusion-weighted MRI (dMRI) are the principal tools for investigating WM. These procedures rely on time-consuming dMRI acquisitions that may not always be available, especially for legacy or time-constrained studies. To address this problem, we aim to generate WM tracts from structural magnetic resonance imaging (MRI) image by deep learning. METHODS Following recently proposed innovations in structural anatomical segmentation, we evaluate the feasibility of training multiply spatial localized convolution neural networks to learn context from fixed spatial patches from structural MRI on standard template. We focus on six widely used dMRI tractography algorithms (TractSeg, RecoBundles, XTRACT, Tracula, automated fiber quantification (AFQ), and AFQclipped) and train 125 U-Net models to learn these techniques from 3870 T1-weighted images from the Baltimore Longitudinal Study of Aging, the Human Connectome Project S1200 release, and scans acquired at Vanderbilt University. RESULTS The proposed framework identifies fiber bundles with high agreement against tractography-based pathways with a median Dice coefficient from 0.62 to 0.87 on a test cohort, achieving improved subject-specific accuracy when compared to population atlas-based methods. We demonstrate the generalizability of the proposed framework on three externally available datasets. CONCLUSIONS We show that patch-wise convolutional neural network can achieve robust bundle segmentation from T1w. We envision the use of this framework for visualizing the expected course of WM pathways when dMRI is not available.
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Affiliation(s)
- Qi Yang
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Colin B. Hansen
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Francois Rheault
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Ho Hin Lee
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Shunxing Bao
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Bramsh Qamar Chandio
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, USA
| | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland, USA
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, USA,Program of Neuroscience, Indiana University, Bloomington, Indiana, USA
| | - Adam W. Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Centre, Nashville, Tennessee, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Centre, Nashville, Tennessee, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Centre, Nashville, Tennessee, USA
| | - Bennett A. Landman
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA,Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Centre, Nashville, Tennessee, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Centre, Nashville, Tennessee, USA
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13
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Radwan AM, Sunaert S, Schilling K, Descoteaux M, Landman BA, Vandenbulcke M, Theys T, Dupont P, Emsell L. An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI. Neuroimage 2022; 254:119029. [PMID: 35231632 DOI: 10.1016/j.neuroimage.2022.119029] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 01/19/2022] [Accepted: 02/21/2022] [Indexed: 11/17/2022] Open
Abstract
Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.
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Affiliation(s)
- Ahmed M Radwan
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium.
| | - Stefan Sunaert
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Kurt Schilling
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, TN, USA
| | | | - Bennett A Landman
- Vanderbilt University, Department of Electrical Engineering and Computer Engineering, Nashville, TN, USA
| | - Mathieu Vandenbulcke
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Neuropsychiatry, Leuven, Belgium; KU Leuven, Department of Geriatric Psychiatry, University Psychiatric Center (UPC), Leuven, Belgium
| | - Tom Theys
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Research Group Experimental Neurosurgery and Neuroanatomy, Leuven, Belgium; UZ Leuven, Department of Neurosurgery, Leuven, Belgium
| | - Patrick Dupont
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven, Belgium
| | - Louise Emsell
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Neuropsychiatry, Leuven, Belgium; KU Leuven, Department of Geriatric Psychiatry, University Psychiatric Center (UPC), Leuven, Belgium
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14
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Nitert AD, Tan HH, Walhout R, Knijnenburg NL, van Es MA, Veldink JH, Hendrikse J, Westeneng HJ, van den Berg LH. Sensitivity of brain MRI and neurological examination for detection of upper motor neurone degeneration in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2022; 93:82-92. [PMID: 34663622 PMCID: PMC8685620 DOI: 10.1136/jnnp-2021-327269] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/12/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES To investigate sensitivity of brain MRI and neurological examination for detection of upper motor neuron (UMN) degeneration in patients with amyotrophic lateral sclerosis (ALS). METHODS We studied 192 patients with ALS and 314 controls longitudinally. All patients visited our centre twice and underwent full neurological examination and brain MRI. At each visit, we assessed UMN degeneration by measuring motor cortex thickness (CT) and pyramidal tract fibre density (FD) corresponding to five body regions (bulbar region and limbs). For each body region, we measured degree of clinical UMN and lower motor neuron (LMN) symptom burden using a validated scoring system. RESULTS We found deterioration over time of CT of motor regions (p≤0.0081) and progression of UMN signs of bulbar region and left arm (p≤0.04). FD was discriminative between controls and patients with moderate/severe UMN signs (all regions, p≤0.034), but did not change longitudinally. Higher clinical UMN burden correlated with reduced CT, but not lower FD, for the bulbar region (p=2.2×10-10) and legs (p≤0.025). In the arms, we found that severe LMN signs may reduce the detectability of UMN signs (p≤0.043). With MRI, UMN degeneration was detectable before UMN signs became clinically evident (CT: p=1.1×10-10, FD: p=6.3×10-4). Motor CT, but not FD, deteriorated more than UMN signs during the study period. CONCLUSIONS Motor CT is a more sensitive measure of UMN degeneration than UMN signs. Motor CT and pyramidal tract FD are discriminative between patients and controls. Brain MRI can monitor UMN degeneration before signs become clinically evident. These findings promote MRI as a potential biomarker for UMN progression in clinical trials in ALS.
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Affiliation(s)
- Abram D Nitert
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Harold Hg Tan
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Renée Walhout
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Nienke L Knijnenburg
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Michael A van Es
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Jan H Veldink
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Henk-Jan Westeneng
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
| | - Leonard H van den Berg
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht, The Netherlands
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15
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Rheault F, Bayrak RG, Wang X, Schilling KG, Greer JM, Hansen CB, Kerley C, Ramadass K, Remedios LW, Blaber JA, Williams O, Beason-Held LL, Resnick SM, Rogers BP, Landman BA. TractEM: Evaluation of protocols for deterministic tractography white matter atlas. Magn Reson Imaging 2022; 85:44-56. [PMID: 34666161 PMCID: PMC8629950 DOI: 10.1016/j.mri.2021.10.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/25/2021] [Accepted: 10/12/2021] [Indexed: 01/03/2023]
Abstract
Reproducible identification of white matter pathways across subjects is essential for the study of structural connectivity of the human brain. One of the key challenges is anatomical differences between subjects and human rater subjectivity in labeling. Labeling white matter regions of interest presents many challenges due to the need to integrate both local and global information. Clearly communicating the manual processes to capture this information is cumbersome, yet essential to lay a solid foundation for comprehensive atlases. Segmentation protocols must be designed so the interpretation of the requested tasks as well as locating structural landmarks is anatomically accurate, intuitive and reproducible. In this work, we quantified the reproducibility of a first iteration of an open/public multi-bundle segmentation protocol. This allowed us to establish a baseline for its reproducibility as well as to identify the limitations for future iterations. The protocol was tested/evaluated on both typical 3 T research acquisition Baltimore Longitudinal Study of Aging (BLSA) and high-acquisition quality Human Connectome Project (HCP) datasets. The results show that a rudimentary protocol can produce acceptable intra-rater and inter-rater reproducibility. However, this work highlights the difficulty in generalizing reproducible results and the importance of reaching consensus on anatomical description of white matter pathways. The protocol has been made available in open source to improve generalizability and reliability in collaboration. The goal is to improve upon the first iteration and initiate a discussion on the anatomical validity (or lack thereof) of some bundle definitions and the importance of reproducibility of tractography segmentation.
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Affiliation(s)
- Francois Rheault
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
| | - Roza G Bayrak
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Xuan Wang
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
| | - Jasmine M Greer
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
| | - Colin B Hansen
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Cailey Kerley
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | | | | | | | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Lori L Beason-Held
- 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
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Nashville, TN, USA; Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
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16
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Maffei C, Lee C, Planich M, Ramprasad M, Ravi N, Trainor D, Urban Z, Kim M, Jones RJ, Henin A, Hofmann SG, Pizzagalli DA, Auerbach RP, Gabrieli JDE, Whitfield-Gabrieli S, Greve DN, Haber SN, Yendiki A. Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data. Neuroimage 2021; 245:118706. [PMID: 34780916 PMCID: PMC8835483 DOI: 10.1016/j.neuroimage.2021.118706] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/11/2021] [Accepted: 11/01/2021] [Indexed: 11/27/2022] Open
Abstract
The development of scanners with ultra-high gradient strength, spearheaded by the Human Connectome Project, has led to dramatic improvements in the spatial, angular, and diffusion resolution that is feasible for in vivo diffusion MRI acquisitions. The improved quality of the data can be exploited to achieve higher accuracy in the inference of both microstructural and macrostructural anatomy. However, such high-quality data can only be acquired on a handful of Connectom MRI scanners worldwide, while remaining prohibitive in clinical settings because of the constraints imposed by hardware and scanning time. In this study, we first update the classical protocols for tractography-based, manual annotation of major white-matter pathways, to adapt them to the much greater volume and variability of the streamlines that can be produced from today’s state-of-the-art diffusion MRI data. We then use these protocols to annotate 42 major pathways manually in data from a Connectom scanner. Finally, we show that, when we use these manually annotated pathways as training data for global probabilistic tractography with anatomical neighborhood priors, we can perform highly accurate, automated reconstruction of the same pathways in much lower-quality, more widely available diffusion MRI data. The outcomes of this work include both a new, comprehensive atlas of WM pathways from Connectom data, and an updated version of our tractography toolbox, TRActs Constrained by UnderLying Anatomy (TRACULA), which is trained on data from this atlas. Both the atlas and TRACULA are distributed publicly as part of FreeSurfer. We present the first comprehensive comparison of TRACULA to the more conventional, multi-region-of-interest approach to automated tractography, and the first demonstration of training TRACULA on high-quality, Connectom data to benefit studies that use more modest acquisition protocols.
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Affiliation(s)
- C Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - C Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Planich
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Ramprasad
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - N Ravi
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - D Trainor
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Z Urban
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - R J Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - A Henin
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - S G Hofmann
- Department of Clinical Psychology, Philipps University Marburg, Germany; Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - D A Pizzagalli
- McLean Hospital and Harvard Medical School, Belmont, MA, USA
| | | | - J D E Gabrieli
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - D N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - S N Haber
- McLean Hospital and Harvard Medical School, Belmont, MA, USA; Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, NY, USA
| | - A Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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17
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Sato T, Nakamura Y, Takeda A, Ueno M. Lesion Area in the Cerebral Cortex Determines the Patterns of Axon Rewiring of Motor and Sensory Corticospinal Tracts After Stroke. Front Neurosci 2021; 15:737034. [PMID: 34707476 PMCID: PMC8542932 DOI: 10.3389/fnins.2021.737034] [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: 07/06/2021] [Accepted: 09/21/2021] [Indexed: 11/18/2022] Open
Abstract
The corticospinal tract (CST) is an essential neural pathway for reorganization that recovers motor functions after brain injuries such as stroke. CST comprises multiple pathways derived from different sensorimotor areas of the cerebral cortex; however, the patterns of reorganization in such complex pathways postinjury are largely unknown. Here we comprehensively examined the rewiring patterns of the CST pathways of multiple cerebral origins in a mouse stroke model that varied in size and location in the sensorimotor cortex. We found that spared contralesional motor and sensory CST axons crossed the midline and sprouted into the denervated side of the cervical spinal cord after stroke in a large cortical area. In contrast, the contralesional CST fibers did not sprout in a small stroke, whereas the ipsilesional axons from the spared motor area grew on the denervated side. We further showed that motor and sensory CST axons did not innervate the projecting areas mutually when either one was injured. The present results reveal the basic principles that generate the patterns of CST rewiring, which depend on stroke location and CST subtype. Our data indicate the importance of targeting different neural substrates to restore function among the types of injury.
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Affiliation(s)
| | | | | | - Masaki Ueno
- Department of System Pathology for Neurological Disorders, Brain Research Institute, Niigata University, Niigata, Japan
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18
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Tsuchida A, Laurent A, Crivello F, Petit L, Pepe A, Beguedou N, Debette S, Tzourio C, Mazoyer B. Age-Related Variations in Regional White Matter Volumetry and Microstructure During the Post-adolescence Period: A Cross-Sectional Study of a Cohort of 1,713 University Students. Front Syst Neurosci 2021; 15:692152. [PMID: 34413727 PMCID: PMC8369154 DOI: 10.3389/fnsys.2021.692152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 07/05/2021] [Indexed: 12/30/2022] Open
Abstract
Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterizations of the microstructural architecture of white matter, and they are increasingly utilized to study white matter changes during development and aging. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18-26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined in the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterized by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.
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Affiliation(s)
- Ami Tsuchida
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Alexandre Laurent
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Fabrice Crivello
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Laurent Petit
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Antonietta Pepe
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Naka Beguedou
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France
| | - Stephanie Debette
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France.,Centre Hospitalier Universitaire, Bordeaux, France
| | - Christophe Tzourio
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France.,Centre Hospitalier Universitaire, Bordeaux, France
| | - Bernard Mazoyer
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA, Bordeaux, France.,Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France.,Centre Hospitalier Universitaire, Bordeaux, France
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19
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Sheng Z, Yu J, Chen Z, Sun Y, Bu X, Wang M, Sarica C, Hernesniemi J, Nelson BJ, Zemmar A, Avecillas-Chasin JM. Constrained-Spherical Deconvolution Tractography in the Evaluation of the Corticospinal Tract in Glioma Surgery. Front Surg 2021; 8:646465. [PMID: 34395506 PMCID: PMC8358074 DOI: 10.3389/fsurg.2021.646465] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 05/24/2021] [Indexed: 11/25/2022] Open
Abstract
Introduction: Tractography has demonstrated utility for surgical resection in the setting of primary brain tumors involving eloquent white matter (WM) pathways. Methods: Twelve patients with glioma in or near eloquent motor areas were analyzed. The motor status was recorded before and after surgery. Two different tractography approaches were used to generate the motor corticospinal tract (CST): Constrained spherical deconvolution probabilistic tractography (CSD-Prob) and single tensor deterministic tractography (Tens-DET). To define the degree of disruption of the CST after surgical resection of the tumor, we calculated the percentage of the CST affected by surgical resection, which was then correlated with the postoperative motor status. Moreover, the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of the CST generated by the CSD-Prob and the Tens-DET was measured and compared between the ipsilesional and contralesional side. Results: The CST was identified in all patients and its trajectory was displaced by the tumor. Only the CSD-Prob approach showed the CST with the characteristic fan-like projections from the precentral gyrus to the brainstem. Disruption of the CST was identified in 6/6 with postoperative motor deficit by CSD-Prob approach and in 5/6 in the Tens-DET. The degree of disruption was significantly associated with the motor deficit with the CSD-Prob approach (rho = −0.88, p = 0.021). However, with the Tens-DET approach the CST disruption did not show significant association with the motor function (rho = −0.27, p = 0.6). There was a significant decrease in FA (p = 0.006) and a significant increase in MD (p = 0.0004) and RD (p = 0.005) on the ipsilesional CST compared with the contralesional CST only with the CSD-Prob approach. Conclusion: CSD-Prob accurately represented the known anatomy of the CST and provided a meaningful estimate of microstructural changes of the CST affected by the tumor and its macrostructural damage after surgery. Newer surgical planning stations should include advanced models and algorithms of tractography in order to obtain more meaningful reconstructions of the WM pathways during glioma surgery.
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Affiliation(s)
- Zhiyuan Sheng
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Jinliang Yu
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Zhongcan Chen
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Yong Sun
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Xingyao Bu
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, People's Hospital of Zhengzhou University (Henan Provincial People's Hospital), Zhengzhou, China
| | - Can Sarica
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Juha Hernesniemi
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China
| | - Bradley J Nelson
- Multi Scale Robotics Laboratory, ETH Zurich, Zurich, Switzerland
| | - Ajmal Zemmar
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China.,Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Josue M Avecillas-Chasin
- Juha Hernesniemi International Neurosurgery Center, Zhengzhou University People's Hospital (Henan Provincial People's Hospital), Zhengzhou, China.,Department of Neurosurgery, Center for Neuromodulation, Mount Sinai Health System, New York, NY, United States
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20
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Cao X, Wang Z, Chen X, Liu Y, Wang W, Abdoulaye IA, Ju S, Yang X, Wang Y, Guo Y. White matter degeneration in remote brain areas of stroke patients with motor impairment due to basal ganglia lesions. Hum Brain Mapp 2021; 42:4750-4761. [PMID: 34232552 PMCID: PMC8410521 DOI: 10.1002/hbm.25583] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 05/15/2021] [Accepted: 06/25/2021] [Indexed: 12/14/2022] Open
Abstract
Diffusion tensor imaging (DTI) studies have revealed distinct white matter (WM) characteristics of the brain following diseases. Beyond the lesion‐symptom maps, stroke is characterized by extensive structural and functional alterations of brain areas remote to local lesions. Here, we further investigated the structural changes over a global level by using DTI data of 10 ischemic stroke patients showing motor impairment due to basal ganglia lesions and 11 healthy controls. DTI data were processed to obtain fractional anisotropy (FA) maps, and multivariate pattern analysis was used to explore brain regions that play an important role in classification based on FA maps. The WM structural network was constructed by the deterministic fiber‐tracking approach. In comparison with the controls, the stroke patients showed FA reductions in the perilesional basal ganglia, brainstem, and bilateral frontal lobes. Using network‐based statistics, we found a significant reduction in the WM subnetwork in stroke patients. We identified the patterns of WM degeneration affecting brain areas remote to the lesions, revealing the abnormal organization of the structural network in stroke patients, which may be helpful in understanding of the neural mechanisms underlying hemiplegia.
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Affiliation(s)
- Xuejin Cao
- Department of Neurology, Southeast University Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Southeast University Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Xiaohui Chen
- Department of Radiology, Zhongda Hospital, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Yanli Liu
- Department of Rehabilitation, Southeast University Zhongda Hospital, Nanjing, China
| | - Wei Wang
- Department of Radiology, Zhongda Hospital, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Idriss Ali Abdoulaye
- Department of Neurology, Southeast University Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Shenghong Ju
- Department of Radiology, Zhongda Hospital, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Xi Yang
- Department of Rehabilitation, Southeast University Zhongda Hospital, Nanjing, China
| | - Yuancheng Wang
- Department of Radiology, Zhongda Hospital, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Yijing Guo
- Department of Neurology, Southeast University Zhongda Hospital, Medical School of Southeast University, Nanjing, China.,Department of Neurology, Lishui People's Hospital, Southeast University Zhongda Hospital Lishui Branch, Nanjing, China
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21
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Hau J, S Kohli J, Shryock I, Kinnear MK, Schadler A, Müller RA, Carper RA. Supplementary and Premotor Aspects of the Corticospinal Tract Show Links with Restricted and Repetitive Behaviors in Middle-Aged Adults with Autism Spectrum Disorder. Cereb Cortex 2021; 31:3962-3972. [PMID: 33791751 PMCID: PMC8258444 DOI: 10.1093/cercor/bhab062] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 01/29/2021] [Accepted: 02/24/2021] [Indexed: 12/18/2022] Open
Abstract
Individuals with autism spectrum disorder (ASD) show motor impairment into adulthood and risk decline during aging, but little is known about brain changes in aging adults with ASD. Few studies of ASD have directly examined the corticospinal tract (CST)-the major descending pathway in the brain responsible for voluntary motor behavior-outside its primary motor (M1) connections. In 26 middle-aged adults with ASD and 26 age-matched typical comparison participants, we used diffusion imaging to examine the microstructure and volume of CST projections from M1, dorsal premotor (PMd), supplementary motor area (SMA), and primary somatosensory (S1) cortices with respect to age. We also examined relationships between each CST sub-tract (-cst), motor skills, and autism symptoms. We detected no significant group or age-related differences in tracts extending from M1 or other areas. However, sub-tracts of the CST extending from secondary (but not primary) motor areas were associated with core autism traits. Increased microstructural integrity of left PMd-cst and SMA-cst were associated with less-severe restricted and repetitive behaviors (RRB) in the ASD group. These findings suggest that secondary motor cortical areas, known to be involved in selecting motor programs, may be implicated in cognitive motor processes underlying RRB in ASD.
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Affiliation(s)
- Janice Hau
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Jiwandeep S Kohli
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Ian Shryock
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Mikaela K Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Adam Schadler
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Ralph-Axel Müller
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
| | - Ruth A Carper
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, CA 92120, USA
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22
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Hansen CB, Yang Q, Lyu I, Rheault F, Kerley C, Chandio BQ, Fadnavis S, Williams O, Shafer AT, Resnick SM, Zald DH, Cutting LE, Taylor WD, Boyd B, Garyfallidis E, Anderson AW, Descoteaux M, Landman BA, Schilling KG. Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography. Neuroinformatics 2021; 19:447-460. [PMID: 33196967 PMCID: PMC8124084 DOI: 10.1007/s12021-020-09497-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 12/21/2022]
Abstract
Brain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate "regions" rather than as white matter "bundles" or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different automated state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.
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Affiliation(s)
- Colin B Hansen
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Qi Yang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Francois Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Cailey Kerley
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bramsh Qamar Chandio
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Shreyas Fadnavis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Andrea T Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - David H Zald
- Center for Advanced Human Brain Imaging Research, Rutgers University, Piscataway, NJ, USA
| | - Laurie E Cutting
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Warren D Taylor
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Brian Boyd
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Program of Neuroscience, Indiana University, Bloomington, IN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
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23
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Legarreta JH, Petit L, Rheault F, Theaud G, Lemaire C, Descoteaux M, Jodoin PM. Filtering in tractography using autoencoders (FINTA). Med Image Anal 2021; 72:102126. [PMID: 34161915 DOI: 10.1016/j.media.2021.102126] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 04/20/2021] [Accepted: 05/26/2021] [Indexed: 10/21/2022]
Abstract
Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that are not supported by the underlying diffusion signal; and under-representing some fiber populations, among others. In this paper, we describe a novel autoencoder-based learning method to filter streamlines from diffusion MRI tractography, and hence, to obtain more reliable tractograms. Our method, dubbed FINTA (Filtering in Tractography using Autoencoders) uses raw, unlabeled tractograms to train the autoencoder, and to learn a robust representation of brain streamlines. Such an embedding is then used to filter undesired streamline samples using a nearest neighbor algorithm. Our experiments on both synthetic and in vivo human brain diffusion MRI tractography data obtain accuracy scores exceeding the 90% threshold on the test set. Results reveal that FINTA has a superior filtering performance compared to conventional, anatomy-based methods, and the RecoBundles state-of-the-art method. Additionally, we demonstrate that FINTA can be applied to partial tractograms without requiring changes to the framework. We also show that the proposed method generalizes well across different tracking methods and datasets, and shortens significantly the computation time for large (>1 M streamlines) tractograms. Together, this work brings forward a new deep learning framework in tractography based on autoencoders, which offers a flexible and powerful method for white matter filtering and bundling that could enhance tractometry and connectivity analyses.
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Affiliation(s)
- Jon Haitz Legarreta
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada; Videos & Images Theory and Analytics Laboratory (VITAL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada.
| | - Laurent Petit
- Groupe d'Imagerie Neurofonctionnelle (GIN), Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, Bordeaux F-33000, France
| | - François Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada
| | - Carl Lemaire
- Centre de Calcul Scientifique, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada
| | - Pierre-Marc Jodoin
- Videos & Images Theory and Analytics Laboratory (VITAL), Department of Computer Science, Université de Sherbrooke, 2500, boul. de l'Université, Sherbrooke, Québec J1K 2R1, Canada
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24
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Intraoperative mapping of pre-central motor cortex and subcortex: a proposal for supplemental cortical and novel subcortical maps to Penfield's motor homunculus. Brain Struct Funct 2021; 226:1601-1611. [PMID: 33871691 PMCID: PMC8096772 DOI: 10.1007/s00429-021-02274-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 04/09/2021] [Indexed: 12/17/2022]
Abstract
Penfield’s motor homunculus describes a caricaturised yet useful representation of the map of various body parts on the pre-central cortex. We propose a supplemental map of the clinically represented areas of human body in pre-central cortex and a novel subcortical corticospinal tract map. We believe this knowledge is essential for safe surgery in patients with eloquent brain lesions. A single-institution retrospective cohort study of patients who underwent craniotomy for motor eloquent lesions with intraoperative motor neuromonitoring (cortical and subcortical) between 2015 and 2020 was performed. All positive cortical and subcortical stimulation points were taken into account and cartographic maps were produced to demonstrate cortical and subcortical areas of motor representation and their configuration. A literature review in PubMed was performed. One hundred and eighty consecutive patients (58.4% male, 41.6% female) were included in the study with 81.6% asleep and 18.4% awake craniotomies for motor eloquent lesions (gliomas 80.7%, metastases 13.8%) with intraoperative cortical and subcortical motor mapping. Based on the data, we propose a supplemental clinical cortical and a novel subcortical motor map to the original Penfield’s motor homunculus, including demonstration of localisation of intercostal muscles both in the cortex and subcortex which has not been previously described. The supplementary clinical cortical and novel subcortical motor maps of the homunculus presented here have been derived from a large cohort of patients undergoing direct cortical and subcortical brain mapping. The information will have direct relevance for improving the safety and outcome of patients undergoing resection of motor eloquent brain lesions.
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Importance of Different Characteristic of the Corticospinal Tract Based on DTI and Cadaveric Microdissection. JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES 2021. [DOI: 10.30621/jbachs.904035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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26
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Ocampo-Pineda M, Schiavi S, Rheault F, Girard G, Petit L, Descoteaux M, Daducci A. Hierarchical Microstructure Informed Tractography. Brain Connect 2021; 11:75-88. [PMID: 33512262 DOI: 10.1089/brain.2020.0907] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Tractography uses diffusion magnetic resonance imaging to noninvasively infer the macroscopic pathways of white matter fibers and it is the only available technique to probe in vivo the structural connectivity of the brain. However, despite this unique and compelling ability and its wide range of possible neurological applications, tractography is still limited, lacks anatomical precision, and suffers from a serious sensitivity/specificity trade-off. For this reason, in the past few years, tractography postprocessing techniques have emerged and proved effective for improving the quality of the reconstructions. Among them, the Convex Optimization Modeling for Microstructure Informed Tractography formulation allows incorporating the anatomical prior that fibers are naturally organized in fascicles, and has obtained exceptional results in increasing the accuracy of the estimated tractograms. Methods: We propose an extension to this idea and introduce a multilevel grouping of the streamlines to capture the white matter arrangement in fascicles and subfascicles. We tested our proposed formulation in synthetic and in vivo data. Results: Our experiments show that using multiple levels allows considering information about the white matter organization more adequately and helps to improve further the accuracy of the resulting tractograms. Conclusion: This new formulation represents a further important step toward a more accurate structural connectivity estimation.
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Affiliation(s)
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - François Rheault
- Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Gabriel Girard
- Center for BioMedical Imaging (CIBM), Lausanne, Switzerland.,University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Laurent Petit
- Groupe d'Imagerie Neurofonctionnelle, Université de Bordeaux, CNRS, CEA, IMN, UMR 5293, Bordeaux, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, Canada
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Abstract
Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.
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Affiliation(s)
- Wieslaw L Nowinski
- John Paul II Center for Virtual Anatomy and Surgical Simulation, University of Cardinal Stefan Wyszynski, Woycickiego 1/3, Block 12, room 1220, 01-938, Warsaw, Poland.
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Girard G, Caminiti R, Battaglia-Mayer A, St-Onge E, Ambrosen KS, Eskildsen SF, Krug K, Dyrby TB, Descoteaux M, Thiran JP, Innocenti GM. On the cortical connectivity in the macaque brain: A comparison of diffusion tractography and histological tracing data. Neuroimage 2020; 221:117201. [PMID: 32739552 DOI: 10.1016/j.neuroimage.2020.117201] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 07/17/2020] [Accepted: 07/22/2020] [Indexed: 12/22/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) tractography is a non-invasive tool to probe neural connections and the structure of the white matter. It has been applied successfully in studies of neurological disorders and normal connectivity. Recent work has revealed that tractography produces a high incidence of false-positive connections, often from "bottleneck" white matter configurations. The rich literature in histological connectivity analysis studies in the macaque monkey enables quantitative evaluation of the performance of tractography algorithms. In this study, we use the intricate connections of frontal, cingulate, and parietal areas, well established by the anatomical literature, to derive a symmetrical histological connectivity matrix composed of 59 cortical areas. We evaluate the performance of fifteen diffusion tractography algorithms, including global, deterministic, and probabilistic state-of-the-art methods for the connectivity predictions of 1711 distinct pairs of areas, among which 680 are reported connected by the literature. The diffusion connectivity analysis was performed on a different ex-vivo macaque brain, acquired using multi-shell DW-MRI protocol, at high spatial and angular resolutions. Across all tested algorithms, the true-positive and true-negative connections were dominant over false-positive and false-negative connections, respectively. Moreover, three-quarters of streamlines had endpoints location in agreement with histological data, on average. Furthermore, probabilistic streamline tractography algorithms show the best performances in predicting which areas are connected. Altogether, we propose a method for quantitative evaluation of tractography algorithms, which aims at improving the sensitivity and the specificity of diffusion-based connectivity analysis. Overall, those results confirm the usefulness of tractography in predicting connectivity, although errors are produced. Many of the errors result from bottleneck white matter configurations near the cortical grey matter and should be the target of future implementation of methods.
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Affiliation(s)
- Gabriel Girard
- Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; Center for BioMedical Imaging, Lausanne, Switzerland; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Roberto Caminiti
- Neuroscience and Behavior Laboratory, Istituto Italiano di Tecnologia, Rome, Italy
| | | | - Etienne St-Onge
- Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada
| | - Karen S Ambrosen
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark; Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Simon F Eskildsen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Kristine Krug
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom; Institute of Biology, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany; Leibniz-Insitute for Neurobiology, Magdeburg, Germany
| | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada
| | - Jean-Philippe Thiran
- Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; Center for BioMedical Imaging, Lausanne, Switzerland; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Giorgio M Innocenti
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden; Brain and Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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29
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Warrington S, Bryant KL, Khrapitchev AA, Sallet J, Charquero-Ballester M, Douaud G, Jbabdi S, Mars RB, Sotiropoulos SN. XTRACT - Standardised protocols for automated tractography in the human and macaque brain. Neuroimage 2020; 217:116923. [PMID: 32407993 PMCID: PMC7260058 DOI: 10.1016/j.neuroimage.2020.116923] [Citation(s) in RCA: 118] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 03/27/2020] [Accepted: 05/01/2020] [Indexed: 01/19/2023] Open
Abstract
We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science. A new software package for standardised and automated cross-species tractography. Homologous white matter bundles in the human and macaque brain. Human white matter tract atlases generated from large datasets (1000 subjects). Tractography protocols are standardised, but preserve individual variability. Generalisability across datasets shown using the HCP and the UK Biobank data.
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Affiliation(s)
- Shaun Warrington
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK.
| | - Katherine L Bryant
- Donders Institute for Brain, Cognition, & Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands; Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Alexandr A Khrapitchev
- CRUK and MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging - Department of Experimental Psychology, University of Oxford, UK; Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France
| | - Marina Charquero-Ballester
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Psychiatry, University of Oxford, UK
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rogier B Mars
- Donders Institute for Brain, Cognition, & Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands; Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK.
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30
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Rheault F, De Benedictis A, Daducci A, Maffei C, Tax CMW, Romascano D, Caverzasi E, Morency FC, Corrivetti F, Pestilli F, Girard G, Theaud G, Zemmoura I, Hau J, Glavin K, Jordan KM, Pomiecko K, Chamberland M, Barakovic M, Goyette N, Poulin P, Chenot Q, Panesar SS, Sarubbo S, Petit L, Descoteaux M. Tractostorm: The what, why, and how of tractography dissection reproducibility. Hum Brain Mapp 2020; 41:1859-1874. [PMID: 31925871 PMCID: PMC7267902 DOI: 10.1002/hbm.24917] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 11/23/2019] [Accepted: 12/16/2019] [Indexed: 12/19/2022] Open
Abstract
Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.
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Affiliation(s)
- Francois Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeSherbrookeCanada
| | - Alessandro De Benedictis
- Neurosurgery Unit, Department of Neuroscience and NeurorehabilitationBambino Gesù Children's Hospital, IRCCSRomeItaly
| | | | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General Hospital and Harvard Medical SchoolBostonMA
| | - Chantal M. W. Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - David Romascano
- Signal Processing Lab (LTS5)École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | | | | | | | - Franco Pestilli
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIN
| | - Gabriel Girard
- Signal Processing Lab (LTS5)École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeSherbrookeCanada
| | | | - Janice Hau
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCAUSA
| | - Kelly Glavin
- Learning Research & Development Center (LRDC)University of PittsburghPittsburghPAUSA
| | | | - Kristofer Pomiecko
- Learning Research & Development Center (LRDC)University of PittsburghPittsburghPAUSA
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Muhamed Barakovic
- Signal Processing Lab (LTS5)École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | | | - Philippe Poulin
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeSherbrookeCanada
| | | | | | - Silvio Sarubbo
- Division of Neurosurgery, Emergency Department, "S. Chiara" HospitalAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Laurent Petit
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives ‐ UMR 5293, CNRSCEA University of BordeauxBordeauxFrance
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeSherbrookeCanada
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31
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Vanderweyen DC, Theaud G, Sidhu J, Rheault F, Sarubbo S, Descoteaux M, Fortin D. The role of diffusion tractography in refining glial tumor resection. Brain Struct Funct 2020; 225:1413-1436. [PMID: 32180019 DOI: 10.1007/s00429-020-02056-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Accepted: 02/28/2020] [Indexed: 12/14/2022]
Abstract
Primary brain tumors are notoriously hard to resect surgically. Due to their infiltrative nature, finding the optimal resection boundary without damaging healthy tissue can be challenging. One potential tool to help make this decision is diffusion-weighted magnetic resonance imaging (dMRI) tractography. dMRI exploits the diffusion of water molecule along axons to generate a 3D modelization of the white matter bundles in the brain. This feature is particularly useful to visualize how a tumor affects its surrounding white matter and plan a surgical path. This paper reviews the different ways in which dMRI can be used to improve brain tumor resection, its benefits and also its limitations. We expose surgical tools that can be paired with dMRI to improve its impact on surgical outcome, such as loading the 3D tractography in the neuronavigation system and direct electrical stimulation to validate the position of the white matter bundles of interest. We also review articles validating dMRI findings using other anatomical investigation techniques, such as postmortem dissections, manganese-enhanced MRI, electrophysiological stimulations, and phantom studies with known ground truth. We will be discussing the areas of the brain where dMRI performs well and where the future challenges are. We will conclude this review with suggestions and take home messages for neurosurgeons, tractographers, and vendors for advancing the field and on how to benefit from tractography's use in clinical practice.
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Affiliation(s)
- Davy Charles Vanderweyen
- Department of Surgery, Division of Neurosurgery, Faculty of Medicine, University of Sherbrooke, 3001 12 Ave N, Sherbrooke, QC, J1H 5H3, Canada.
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, University of Sherbrooke, 2500 Boulevard Université, Sherbrooke, QC, J1K2R1, Canada
| | - Jasmeen Sidhu
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, University of Sherbrooke, 2500 Boulevard Université, Sherbrooke, QC, J1K2R1, Canada
| | - François Rheault
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, University of Sherbrooke, 2500 Boulevard Université, Sherbrooke, QC, J1K2R1, Canada
| | - Silvio Sarubbo
- Division of Neurosurgery, Emergency Area, Structural and Functional Connectivity Lab Project, "S. Chiara" Hospital, Azienda Provinciale Per I Servizi Sanitari (APSS), Trento, Italy
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, University of Sherbrooke, 2500 Boulevard Université, Sherbrooke, QC, J1K2R1, Canada
| | - David Fortin
- Department of Surgery, Division of Neurosurgery, Faculty of Medicine, University of Sherbrooke, 3001 12 Ave N, Sherbrooke, QC, J1H 5H3, Canada
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32
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Rheault F, Poulin P, Valcourt Caron A, St-Onge E, Descoteaux M. Common misconceptions, hidden biases and modern challenges of dMRI tractography. J Neural Eng 2020; 17:011001. [PMID: 31931484 DOI: 10.1088/1741-2552/ab6aad] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
The human brain is a complex and organized network, where the connection between regions is not achieved with single axons crisscrossing each other but rather millions of densely packed and well-ordered axons. Reconstruction from diffusion MRI tractography is only an attempt to capture the full complexity of this network, at the macroscale. This review provides an overview of the misconceptions, biases and pitfalls present in structural white matter bundle and connectome reconstruction using tractography. The goal is not to discourage readers, but rather to inform them of the limitations present in the methods used by researchers in the field in order to focus on what they can do and promote proper interpretations of their results. It also provides a list of open problems that could be solved in future research projects for the next generation of PhD students.
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Affiliation(s)
- Francois Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada. 2500, boul. de l'Université, Sherbrooke (Québec), J1K 2R1, Sherbrooke, Canada. Author to whom any correspondence should be addressed
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33
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Harrington RM, Chan E, Rounds AK, Wutzke CJ, Dromerick AW, Turkeltaub PE, Harris-Love ML. Roles of Lesioned and Nonlesioned Hemispheres in Reaching Performance Poststroke. Neurorehabil Neural Repair 2020; 34:61-71. [PMID: 31858870 PMCID: PMC6954952 DOI: 10.1177/1545968319876253] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background. Severe poststroke arm impairment is associated with greater activation of the nonlesioned hemisphere during movement of the affected arm. The circumstances under which this activation may be adaptive or maladaptive remain unclear. Objective. To identify the functional relevance of key lesioned and nonlesioned hemisphere motor areas to reaching performance in patients with mild versus severe arm impairment. Methods. A total of 20 participants with chronic stroke performed a reaching response time task with their affected arm. During the reaction time period, a transient magnetic stimulus was applied over the primary (M1) or dorsal premotor cortex (PMd) of either hemisphere, and the effect of the perturbation on movement time (MT) was calculated. Results. For perturbation of the nonlesioned hemisphere, there was a significant interaction effect of Site of perturbation (PMd vs M1) by Group (mild vs severe; P < .001). Perturbation of PMd had a greater effect on MT in the severe versus the mild group. This effect was not observed with perturbation of M1. For perturbation of the lesioned hemisphere, there was a main effect of site of perturbation (P < .05), with perturbation of M1 having a greater effect on MT than PMd. Conclusions. These results demonstrate that, in the context of reaching movements, the role of the nonlesioned hemisphere depends on both impairment severity and the specific site that is targeted. A deeper understanding of these individual-, task-, and site-specific factors is essential for advancing the potential usefulness of neuromodulation to enhance poststroke motor recovery.
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Affiliation(s)
- Rachael M. Harrington
- Georgetown University, Interdisciplinary Program in Neuroscience
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- George Mason University, Department of Bioengineering
- Georgia State University, Center for Research on the Acquisition of Language and Literacy
| | - Evan Chan
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- MedStar Health Research Institute
| | - Amanda K. Rounds
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- MedStar Health Research Institute
- George Mason University, Department of Rehabilitation Science
| | | | - Alexander W. Dromerick
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- Georgetown University Medical Center, Department of Neurology
- Georgetown University Medical Center, Department of Rehabilitation Medicine
| | - Peter E. Turkeltaub
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- Georgetown University Medical Center, Department of Neurology
| | - Michelle L. Harris-Love
- MedStar National Rehabilitation Hospital, Center for Brain Plasticity and Recovery
- George Mason University, Department of Bioengineering
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Wang ZM, Shan Y, Zhang M, Wei PH, Li QG, Yin YY, Lu J. Projections of Brodmann Area 6 to the Pyramidal Tract in Humans: Quantifications Using High Angular Resolution Data. Front Neural Circuits 2019; 13:62. [PMID: 31616257 PMCID: PMC6775280 DOI: 10.3389/fncir.2019.00062] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 09/12/2019] [Indexed: 12/20/2022] Open
Abstract
Primate studies indicate that the pyramidal tract (PyT) could originate from Brodmann area (BA) 6. However, in humans, the accurate origin of PyT from BA 6 is still uncertain owing to difficulties in visualizing anatomical features such as the fanning shape at the corona radiata and multiple crossings at the semioval centrum. High angular-resolution diffusion imaging (HARDI) could reliably replicate these anatomical features. We explored the origin of the human PyT from BA 6 using HARDI. With HARDI data of 30 adults from the Massachusetts General Hospital-Human Connectome Project (MGH-HCP) database and the HCP 1021 template (average of 1021 HCP diffusion data), we visualized the PyT at the 30-averaged group level and the 1021 large-sample level and validated the observations in each of the individuals. Endpoints of the fibers within each subregion were quantified. PyT fibers originating from the BA 6 were consistently visualized in all images. Specifically, the bilateral supplementary motor area (SMA) and dorsal premotor area (dPMA) were consistently found to contribute to the PyT. PyT fibers from BA 6 and those from BA 4 exhibited a twisting topology. The PyT contains fibers originating from the SMA and dPMA in BA 6. Infarction of these regions or aging would result in incomplete provision of information to the PyT and concomitant decreases in motor planning and coordination abilities.
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Affiliation(s)
- Zhen-Ming Wang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yi Shan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Miao Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Peng-Hu Wei
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qiong-Ge Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Ya-Yan Yin
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.,Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
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35
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Minkova L, Peter J, Abdulkadir A, Schumacher LV, Kaller CP, Nissen C, Klöppel S, Lahr J. Determinants of Inter-Individual Variability in Corticomotor Excitability Induced by Paired Associative Stimulation. Front Neurosci 2019; 13:841. [PMID: 31474818 PMCID: PMC6702284 DOI: 10.3389/fnins.2019.00841] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 07/26/2019] [Indexed: 12/23/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) is a well-established tool in probing cortical plasticity in vivo. Changes in corticomotor excitability can be induced using paired associative stimulation (PAS) protocol, in which TMS over the primary motor cortex is conditioned with an electrical peripheral nerve stimulation of the contralateral hand. PAS with an inter-stimulus interval of 25 ms induces long-term potentiation (LTP)-like effects in cortical excitability. However, the response to a PAS protocol tends to vary substantially across individuals. In this study, we used univariate and multivariate data-driven methods to investigate various previously proposed determinants of inter-individual variability in PAS efficacy, such as demographic, cognitive, clinical, neurophysiological, and neuroimaging measures. Forty-one right-handed participants, comprising 22 patients with amnestic mild cognitive impairment (MCI) and 19 healthy controls (HC), underwent the PAS protocol. Prior to stimulation, demographic, genetic, clinical, as well as structural and resting-state functional MRI data were acquired. The two groups did not differ in any of the variables, except by global cognitive status. Univariate analysis showed that only 61% of all participants were classified as PAS responders, irrespective of group membership. Higher PAS response was associated with lower TMS intensity and with higher resting-state connectivity within the sensorimotor network, but only in responders, as opposed to non-responders. We also found an overall positive correlation between PAS response and structural connectivity within the corticospinal tract, which did not differ between groups. A multivariate random forest (RF) model identified age, gender, education, IQ, global cognitive status, sleep quality, alertness, TMS intensity, genetic factors, and neuroimaging measures (functional and structural connectivity, gray matter (GM) volume, and cortical thickness as poor predictors of PAS response. The model resulted in low accuracy of the RF classifier (58%; 95% CI: 42 - 74%), with a higher relative importance of brain connectivity measures compared to the other variables. We conclude that PAS variability in our sample was not well explained by factors known to influence PAS efficacy, emphasizing the need for future replication studies.
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Affiliation(s)
- Lora Minkova
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Freiburg Brain Imaging, Medical Center - University of Freiburg, Freiburg, Germany
| | - Jessica Peter
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Ahmed Abdulkadir
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Lena V Schumacher
- Department of Medical Psychology and Medical Sociology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christoph P Kaller
- Freiburg Brain Imaging, Medical Center - University of Freiburg, Freiburg, Germany.,Department of Neuroradiology, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christoph Nissen
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,University Hospital of Psychiatry and Psychotherapy, University Psychiatric Services, University of Bern, Bern, Switzerland.,Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Center for Geriatrics and Gerontology Freiburg, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jacob Lahr
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Freiburg Brain Imaging, Medical Center - University of Freiburg, Freiburg, Germany
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Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain. Neuroimage 2019; 200:89-100. [PMID: 31228638 PMCID: PMC6711466 DOI: 10.1016/j.neuroimage.2019.06.020] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 06/05/2019] [Accepted: 06/07/2019] [Indexed: 12/13/2022] Open
Abstract
Various diffusion MRI (dMRI) measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different dMRI measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. Indeed, it quickly becomes intractable for existing analysis pipelines to process multiple measurements at each voxel and at each vertex forming a streamline, highlighting the need for new ways to visualise or analyse such high-dimensional data. In a sample of 36 typically developing children aged 8–18 years, we profiled various commonly used dMRI measures across 22 brain pathways. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in these dMRI measures. The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We then demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. In summary, our findings demonstrate that dMRI analyses can benefit from dimensionality reduction techniques, to help disentangling the neurobiological underpinnings of white matter organisation.
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Peruffo A, Corain L, Bombardi C, Centelleghe C, Grisan E, Graïc JM, Bontempi P, Grandis A, Cozzi B. The motor cortex of the sheep: laminar organization, projections and diffusion tensor imaging of the intracranial pyramidal and extrapyramidal tracts. Brain Struct Funct 2019; 224:1933-1946. [DOI: 10.1007/s00429-019-01885-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 05/03/2019] [Indexed: 02/06/2023]
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Yeh FC, Panesar S, Fernandes D, Meola A, Yoshino M, Fernandez-Miranda JC, Vettel JM, Verstynen T. Population-averaged atlas of the macroscale human structural connectome and its network topology. Neuroimage 2018; 178:57-68. [PMID: 29758339 DOI: 10.1016/j.neuroimage.2018.05.027] [Citation(s) in RCA: 312] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 04/03/2018] [Accepted: 05/09/2018] [Indexed: 11/27/2022] Open
Abstract
A comprehensive map of the structural connectome in the human brain has been a coveted resource for understanding macroscopic brain networks. Here we report an expert-vetted, population-averaged atlas of the structural connectome derived from diffusion MRI data (N = 842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles annotated by 80 anatomical labels. The trajectories were subsequently clustered and labeled by a team of experienced neuroanatomists in order to conform to prior neuroanatomical knowledge. A multi-level network topology was then described using whole-brain connectograms, with subdivisions of the association pathways showing small-worldness in intra-hemisphere connections, projection pathways showing hub structures at thalamus, putamen, and brainstem, and commissural pathways showing bridges connecting cerebral hemispheres to provide global efficiency. This atlas of the structural connectome provides representative organization of human brain white matter, complementary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectome studies.
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Affiliation(s)
- Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Sandip Panesar
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - David Fernandes
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Antonio Meola
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | | | - Juan C Fernandez-Miranda
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Jean M Vettel
- U.S. Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD, USA; Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy Verstynen
- Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pennsylvania, USA.
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