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Takemura H, Kruper JA, Miyata T, Rokem A. Tractometry of Human Visual White Matter Pathways in Health and Disease. Magn Reson Med Sci 2024; 23:316-340. [PMID: 38866532 PMCID: PMC11234945 DOI: 10.2463/mrms.rev.2024-0007] [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] [Indexed: 06/14/2024] Open
Abstract
Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Hayama, Kanagawa, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - John A Kruper
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | - Toshikazu Miyata
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - Ariel Rokem
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
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2
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Tipado Z, Kuypers KPC, Sorger B, Ramaekers JG. Visual hallucinations originating in the retinofugal pathway under clinical and psychedelic conditions. Eur Neuropsychopharmacol 2024; 85:10-20. [PMID: 38648694 DOI: 10.1016/j.euroneuro.2024.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 04/11/2024] [Accepted: 04/13/2024] [Indexed: 04/25/2024]
Abstract
Psychedelics like LSD (Lysergic acid diethylamide) and psilocybin are known to modulate perceptual modalities due to the activation of mostly serotonin receptors in specific cortical (e.g., visual cortex) and subcortical (e.g., thalamus) regions of the brain. In the visual domain, these psychedelic modulations often result in peculiar disturbances of viewed objects and light and sometimes even in hallucinations of non-existent environments, objects, and creatures. Although the underlying processes are poorly understood, research conducted over the past twenty years on the subjective experience of psychedelics details theories that attempt to explain these perceptual alterations due to a disruption of communication between cortical and subcortical regions. However, rare medical conditions in the visual system like Charles Bonnet syndrome that cause perceptual distortions may shed new light on the additional importance of the retinofugal pathway in psychedelic subjective experiences. Interneurons in the retina called amacrine cells could be the first site of visual psychedelic modulation and aid in disrupting the hierarchical structure of how humans perceive visual information. This paper presents an understanding of how the retinofugal pathway communicates and modulates visual information in psychedelic and clinical conditions. Therefore, we elucidate a new theory of psychedelic modulation in the retinofugal pathway.
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Affiliation(s)
- Zeus Tipado
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands.
| | - Kim P C Kuypers
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Johannes G Ramaekers
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
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3
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Carrozzi A, Gramegna LL, Sighinolfi G, Zoli M, Mazzatenta D, Testa C, Lodi R, Tonon C, Manners DN. Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods. Neuroimage Clin 2023; 39:103494. [PMID: 37651845 PMCID: PMC10477810 DOI: 10.1016/j.nicl.2023.103494] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 06/21/2023] [Accepted: 08/07/2023] [Indexed: 09/02/2023]
Abstract
The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g., traumatic optic neuropathy) or chronic conditions that affect AOP structures (e.g., amblyopia, glaucoma, demyelinating disorders or genetic optic nerve atrophies). However, its peculiar anatomy and course, as well as its surroundings, pose a serious challenge to obtaining successful tractographic reconstructions. Several AOP tractography strategies have been adopted but no standard procedure has been agreed upon. We performed a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines in order to find the combinations of acquisition and reconstruction parameters that have been performed previously and have provided the highest rate of successful reconstruction of the AOP, in order to promote their routine implementation in clinical practice. For this purpose, we reviewed data regarding how the process of anatomical validation of the tractographies was performed. The Cochrane Handbook for Systematic Reviews of Interventions was used to assess the risk of bias and thus the study quality We identified thirty-nine studies that met our inclusion criteria, and only five were considered at low risk of bias and achieved over 80% of successful reconstructions. We found a high degree of heterogeneity in the acquisition and analysis parameters used to perform AOP tractography and different combinations of them can achieve satisfactory levels of anterior optic tractographic reconstruction both in real-life research and clinical scenarios. One thousand s/mm2 was the most frequently used b value, while both deterministic and probabilistic tractography algorithms performed morphological reconstruction of the tract satisfactorily, although probabilistic algorithms estimated a more realistic percentage of crossing fibers (45.6%) in healthy subjects. A wide heterogeneity was also found regarding the method used to assess the anatomical fidelity of the AOP reconstructions. Three main strategies can be found: direct visual direct visual assessment of the tractography superimposed to a conventional MR image, surgical evaluation, and computational methods. Because the latter is less dependent on a priori knowledge of the anatomy by the operator, computational methods of validation of the anatomy should be considered whenever possible.
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Affiliation(s)
- Alessandro Carrozzi
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Laura Ludovica Gramegna
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Functional and Molecular Neuroimaging Unit, Bologna, Italy.
| | - Giovanni Sighinolfi
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Matteo Zoli
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Pituitary Unit, Bologna, Italy
| | - Diego Mazzatenta
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Pituitary Unit, Bologna, Italy
| | - Claudia Testa
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Functional and Molecular Neuroimaging Unit, Bologna, Italy
| | - David Neil Manners
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Functional and Molecular Neuroimaging Unit, Bologna, Italy; Department for Life Quality Studies (QUVI), University of Bologna, Bologna, Italy
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4
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He J, Yao S, Zeng Q, Chen J, Sang T, Xie L, Pan Y, Feng Y. A unified global tractography framework for automatic visual pathway reconstruction. NMR IN BIOMEDICINE 2023; 36:e4904. [PMID: 36633539 DOI: 10.1002/nbm.4904] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 01/05/2023] [Accepted: 01/10/2023] [Indexed: 06/15/2023]
Abstract
The human visual pathway starts from the retina, passes through the retinogeniculate visual pathway, the optic radiation, and finally connects to the primary visual cortex. Diffusion MRI tractography is the only technology that can noninvasively reconstruct the visual pathway. However, complete and accurate visual pathway reconstruction is challenging because of the skull base environment and complex fiber geometries. Specifically, the optic nerve within the complex skull base environment can cause abnormal diffusion signals. The crossing and fanning fibers at the optic chiasm, and a sharp turn of Meyer's loop at the optic radiation, contribute to complex fiber geometries of the visual pathway. A fiber trajectory distribution (FTD) function-based tractography method of our previous work and several high sensitivity tractography methods can reveal these complex fiber geometries, but are accompanied by false-positive fibers. Thus, the related studies of the visual pathway mostly applied the expert region of interest selection strategy. However, interobserver variability is an issue in reconstructing an accurate visual pathway. In this paper, we propose a unified global tractography framework to automatically reconstruct the visual pathway. We first extend the FTD function to a high-order streamline differential equation for global trajectory estimation. At the global level, the tractography process is simplified as the estimation of global trajectory distribution coefficients by minimizing the cost between trajectory distribution and the selected directions under the prior guidance by introducing the tractography template as anatomic priors. Furthermore, we use a deep learning-based method and tractography template prior information to automatically generate the mask for tractography. The experimental results demonstrate that our proposed method can successfully reconstruct the visual pathway with high accuracy.
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Affiliation(s)
- Jianzhong He
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
| | - Shun Yao
- Center for Pituitary Tumor Surgery, Department of Neurosurgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Qingrun Zeng
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
| | - Jinping Chen
- Center for Pituitary Tumor Surgery, Department of Neurosurgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Tian Sang
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
| | - Lei Xie
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
| | - Yiang Pan
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
| | - Yuanjing Feng
- Institution of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China
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5
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Kruper J, Benson NC, Caffarra S, Owen J, Wu Y, Lee AY, Lee CS, Yeatman JD, Rokem A. Optic radiations representing different eccentricities age differently. Hum Brain Mapp 2023; 44:3123-3135. [PMID: 36896869 PMCID: PMC10171550 DOI: 10.1002/hbm.26267] [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: 05/28/2022] [Revised: 01/10/2023] [Accepted: 02/16/2023] [Indexed: 03/11/2023] Open
Abstract
The neural pathways that carry information from the foveal, macular, and peripheral visual fields have distinct biological properties. The optic radiations (OR) carry foveal and peripheral information from the thalamus to the primary visual cortex (V1) through adjacent but separate pathways in the white matter. Here, we perform white matter tractometry using pyAFQ on a large sample of diffusion MRI (dMRI) data from subjects with healthy vision in the U.K. Biobank dataset (UKBB; N = 5382; age 45-81). We use pyAFQ to characterize white matter tissue properties in parts of the OR that transmit information about the foveal, macular, and peripheral visual fields, and to characterize the changes in these tissue properties with age. We find that (1) independent of age there is higher fractional anisotropy, lower mean diffusivity, and higher mean kurtosis in the foveal and macular OR than in peripheral OR, consistent with denser, more organized nerve fiber populations in foveal/parafoveal pathways, and (2) age is associated with increased diffusivity and decreased anisotropy and kurtosis, consistent with decreased density and tissue organization with aging. However, anisotropy in foveal OR decreases faster with age than in peripheral OR, while diffusivity increases faster in peripheral OR, suggesting foveal/peri-foveal OR and peripheral OR differ in how they age.
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Affiliation(s)
- John Kruper
- Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
- eScience InstituteUniversity of WashingtonSeattleWashingtonUSA
| | - Noah C. Benson
- eScience InstituteUniversity of WashingtonSeattleWashingtonUSA
| | - Sendy Caffarra
- Graduate School of Education, Stanford University and Division of Developmental‐Behavioral Pediatrics, Stanford University School of MedicineStanford UniversityStanfordCaliforniaUSA
- Department of Biomedical, Metabolic and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
| | - Julia Owen
- Department of OphthalmologyUniversity of WashingtonSeattleWashingtonUSA
- Roger and Angie Karalis Johnson Retina CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Yue Wu
- Department of OphthalmologyUniversity of WashingtonSeattleWashingtonUSA
- Roger and Angie Karalis Johnson Retina CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Aaron Y. Lee
- Department of OphthalmologyUniversity of WashingtonSeattleWashingtonUSA
- Roger and Angie Karalis Johnson Retina CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Cecilia S. Lee
- Department of OphthalmologyUniversity of WashingtonSeattleWashingtonUSA
- Roger and Angie Karalis Johnson Retina CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Jason D. Yeatman
- Graduate School of Education, Stanford University and Division of Developmental‐Behavioral Pediatrics, Stanford University School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Ariel Rokem
- Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
- eScience InstituteUniversity of WashingtonSeattleWashingtonUSA
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6
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Jin R, Cai Y, Zhang S, Yang T, Feng H, Jiang H, Zhang X, Hu Y, Liu J. Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review. Front Neurosci 2023; 17:1191999. [PMID: 37304011 PMCID: PMC10250625 DOI: 10.3389/fnins.2023.1191999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023] Open
Abstract
Optic never fibers in the visual pathway play significant roles in vision formation. Damages of optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and neurological diseases; also, there is a need to prevent the optic nerve fibers from getting damaged in neurosurgery and radiation therapy. Reconstruction of optic nerve fibers from medical images can facilitate all these clinical applications. Although many computational methods are developed for the reconstruction of optic nerve fibers, a comprehensive review of these methods is still lacking. This paper described both the two strategies for optic nerve fiber reconstruction applied in existing studies, i.e., image segmentation and fiber tracking. In comparison to image segmentation, fiber tracking can delineate more detailed structures of optic nerve fibers. For each strategy, both conventional and AI-based approaches were introduced, and the latter usually demonstrates better performance than the former. From the review, we concluded that AI-based methods are the trend for optic nerve fiber reconstruction and some new techniques like generative AI can help address the current challenges in optic nerve fiber reconstruction.
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Affiliation(s)
- Richu Jin
- Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yongning Cai
- Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
| | - Shiyang Zhang
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Ting Yang
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Haibo Feng
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Hongyang Jiang
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Xiaoqing Zhang
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yan Hu
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Jiang Liu
- Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
- Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
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7
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Wang H, Wang X, Wang Y, Zhang D, Yang Y, Zhou Y, Qiu B, Zhang P. White matter BOLD signals at 7 Tesla reveal visual field maps in optic radiation and vertical occipital fasciculus. Neuroimage 2023; 269:119916. [PMID: 36736638 DOI: 10.1016/j.neuroimage.2023.119916] [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: 11/15/2022] [Revised: 01/18/2023] [Accepted: 01/30/2023] [Indexed: 02/03/2023] Open
Abstract
There is growing evidence that blood-oxygen-level-dependent (BOLD) activity in the white matter (WM) can be detected by functional magnetic resonance imaging (fMRI). However, the functional relevance and significance of WM BOLD signals remain controversial. Here we investigated whether 7T BOLD fMRI can reveal fine-scale functional organizations of a WM bundle. Population receptive field (pRF) analyses of the 7T retinotopy dataset from the Human Connectome Project revealed clear contralateral retinotopic organizations of two visual WM bundles: the optic radiation (OR) and the vertical occipital fasciculus (VOF). The retinotopic maps of OR are highly consistent with post-mortem dissections and diffusion tractographies, while the VOF maps are compatible with the dorsal and ventral visual areas connected by the WM. Similar to the grey matter (GM) visual areas, both WM bundles show over-representations of the central visual field and increasing pRF size with eccentricity. Hemodynamic response functions of visual WM were slower and wider compared with those of GM areas. These findings clearly demonstrate that WM BOLD at 7 Tesla is closely coupled with neural activity related to axons, encoding highly specific information that can be used to characterize fine-scale functional organizations of a WM bundle.
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Affiliation(s)
- Huan Wang
- Hefei National Research Center for Physical Sciences at the Microscale, School of Life Science, University of Science and Technology of China, Hefei, Anhui 230027, China; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoxiao Wang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yanming Wang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Du Zhang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yan Yang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yifeng Zhou
- Hefei National Research Center for Physical Sciences at the Microscale, School of Life Science, University of Science and Technology of China, Hefei, Anhui 230027, China; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
| | - Bensheng Qiu
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China.
| | - Peng Zhang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; School of Ophthalmology and Optometry and Eye hospital, and State Key Laboratory of Ophthalmology, Optometry and Vision Science, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.; University of Chinese Academy of Sciences, Beijing 100049, China..
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8
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Ta D, Tu Y, Lu ZL, Wang Y. Quantitative characterization of the human retinotopic map based on quasiconformal mapping. Med Image Anal 2022; 75:102230. [PMID: 34666194 PMCID: PMC8678293 DOI: 10.1016/j.media.2021.102230] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 07/11/2021] [Accepted: 09/10/2021] [Indexed: 01/03/2023]
Abstract
The retinotopic map depicts the cortical neurons' response to visual stimuli on the retina and has contributed significantly to our understanding of human visual system. Although recent advances in high field functional magnetic resonance imaging (fMRI) have made it possible to generate the in vivo retinotopic map with great detail, quantifying the map remains challenging. Existing quantification methods do not preserve surface topology and often introduce large geometric distortions to the map. In this study, we developed a new framework based on computational conformal geometry and quasiconformal Teichmüller theory to quantify the retinotopic map. Specifically, we introduced a general pipeline, consisting of cortical surface conformal parameterization, surface-spline-based cortical activation signal smoothing, and vertex-wise Beltrami coefficient-based map description. After correcting most of the violations of the topological conditions, the result was a "Beltrami coefficient map" (BCM) that rigorously and completely characterizes the retinotopic map by quantifying the local quasiconformal mapping distortion at each visual field location. The BCM provided topological and fully reconstructable retinotopic maps. We successfully applied the new framework to analyze the V1 retinotopic maps from the Human Connectome Project (n=181), the largest state of the art retinotopy dataset currently available. With unprecedented precision, we found that the V1 retinotopic map was quasiconformal and the local mapping distortions were similar across observers. The new framework can be applied to other visual areas and retinotopic maps of individuals with and without eye diseases, and improve our understanding of visual cortical organization in normal and clinical populations.
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Affiliation(s)
- Duyan Ta
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA
| | - Yanshuai Tu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA
| | - Zhong-Lin Lu
- Division of Arts and Sciences, New York University Shanghai, Shanghai, China; Center for Neural Science and Department of Psychology, New York University, New York, NY, USA; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China
| | - Yalin Wang
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
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9
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Blazquez Freches G, Haak KV, Beckmann CF, Mars RB. Connectivity gradients on tractography data: Pipeline and example applications. Hum Brain Mapp 2021; 42:5827-5845. [PMID: 34559432 PMCID: PMC8596970 DOI: 10.1002/hbm.25623] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 07/03/2021] [Accepted: 07/30/2021] [Indexed: 11/08/2022] Open
Abstract
Gray matter connectivity can be described in terms of its topographical organization, but the differential role of white matter connections underlying that organization is often unknown. In this study, we propose a method for unveiling principles of organization of both gray and white matter based on white matter connectivity as assessed using diffusion magnetic ressonance imaging (MRI) tractography with spectral embedding gradient mapping. A key feature of the proposed approach is its capacity to project the individual connectivity gradients it reveals back onto its input data in the form of projection images, allowing one to assess the contributions of specific white matter tracts to the observed gradients. We demonstrate the ability of our proposed pipeline to identify connectivity gradients in prefrontal and occipital gray matter. Finally, leveraging the use of tractography, we demonstrate that it is possible to observe gradients within the white matter bundles themselves. Together, the proposed framework presents a generalized way to assess both the topographical organization of structural brain connectivity and the anatomical features driving it.
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Affiliation(s)
- Guilherme Blazquez Freches
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
| | - Koen V. Haak
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Christian F. Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nufeld Department of Clinical NeurosciencesJohn Radclife Hospital, University of OxfordOxfordUK
| | - Rogier B. Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
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10
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Reid LB, Martínez‐Heras E, Manjón JV, Jeffree RL, Alexander H, Trinder J, Solana E, Llufriu S, Rose S, Prior M, Fripp J. Fully automated delineation of the optic radiation for surgical planning using clinically feasible sequences. Hum Brain Mapp 2021; 42:5911-5926. [PMID: 34547147 PMCID: PMC8596983 DOI: 10.1002/hbm.25658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/21/2021] [Accepted: 08/23/2021] [Indexed: 11/30/2022] Open
Abstract
Quadrantanopia caused by inadvertent severing of Meyer's Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer's Loop varies considerably between individuals. Quantifying this for individual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer's Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT: a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust pre-processing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 696 scans of predominantly healthy participants (539 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer's Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1 mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer's Loop with clinically feasible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods.
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Affiliation(s)
- Lee B. Reid
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Eloy Martínez‐Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Jose V. Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de ValènciaValenciaSpain
| | - Rosalind L. Jeffree
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
- School of Clinical MedicineUniversity of QueenslandHerstonQueenslandAustralia
| | - Hamish Alexander
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
| | - Julie Trinder
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Elisabeth Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Sara Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Stephen Rose
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Marita Prior
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
| | - Jurgen Fripp
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
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11
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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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12
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He J, Zhang F, Xie G, Yao S, Feng Y, Bastos DCA, Rathi Y, Makris N, Kikinis R, Golby AJ, O'Donnell LJ. Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI. Hum Brain Mapp 2021; 42:3887-3904. [PMID: 33978265 PMCID: PMC8288095 DOI: 10.1002/hbm.25472] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 04/24/2021] [Accepted: 04/25/2021] [Indexed: 12/31/2022] Open
Abstract
The retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. The RGVP has four subdivisions, including two decussating and two nondecussating pathways that cannot be identified on conventional structural magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for RGVP reconstruction. In this study, four tractography methods are compared, including constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) methods. Experiments use diffusion MRI data from 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Quantitative anatomical measurements and expert anatomical judgment are used to assess the advantages and limitations of the four tractography methods. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy and have the highest spatial overlap across subjects. Overall, we find that it is challenging for current tractography methods to both accurately track RGVP fibers that correspond to known anatomy and produce an approximately correct percentage of decussating fibers. We suggest that future algorithm development for RGVP tractography should take consideration of both of these two points.
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Affiliation(s)
- Jianzhong He
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of TechnologyHangzhouChina
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Guoqiang Xie
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurosurgeryNuclear Industry 215 Hospital of Shaanxi ProvinceXianyangChina
| | - Shun Yao
- Department of Neurosurgery, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Pituitary Tumor Surgery, Department of NeurosurgeryThe First Affiliated Hospital, Sun Yat‐sen UniversityGuangzhouChina
| | - Yuanjing Feng
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of TechnologyHangzhouChina
| | - Dhiego C. A. Bastos
- Department of Neurosurgery, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Psychiatry, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Nikos Makris
- Department of Psychiatry, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Departments of Psychiatry, Neurology and Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Ron Kikinis
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Alexandra J. Golby
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Neurosurgery, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Lauren J. O'Donnell
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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13
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Abstract
Tractography is an important technique that allows the in vivo reconstruction of structural connections in the brain using diffusion MRI. Although tracking algorithms have improved during the last two decades, results of validation studies and international challenges warn about the reliability of tractography and point out the need for improved algorithms. In propagation-based tracking, connections have traditionally been modeled as piece-wise linear segments. In this work, we propose a novel propagation-based tracker that is capable of generating geometrically smooth ( C1 ) curves using parallel transport frames. Notably, our approach does not increase the complexity of the propagation problem that remains two-dimensional. Moreover, our tracker has a novel mechanism to reduce noise related propagation errors by incorporating topographic regularity of connections, a neuroanatomic property of many brain pathways. We ran extensive experiments and compared our approach against deterministic and other probabilistic algorithms. Our experiments on FiberCup and ISMRM 2015 challenge datasets as well as on 56 subjects of the Human Connectome Project show highly promising results both visually and quantitatively. Open-source implementations of the algorithm are shared publicly.
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14
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Sun W, Tang Y, Qiao Y, Ge X, Mather M, Ringman JM, Shi Y. A probabilistic atlas of locus coeruleus pathways to transentorhinal cortex for connectome imaging in Alzheimer's disease. Neuroimage 2020; 223:117301. [PMID: 32861791 PMCID: PMC7797167 DOI: 10.1016/j.neuroimage.2020.117301] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 08/12/2020] [Accepted: 08/17/2020] [Indexed: 02/07/2023] Open
Abstract
According to the latest Braak staging of Alzheimer's disease (AD), tau pathology occurs earliest in the brain in the locus coeruleus (LC) of the brainstem, then propagates to the transentorhinal cortex (TEC), and later to other neocortical regions. Recent animal and in vivo human brain imaging research also support the trans-axonal propagation of tau pathology. In addition, neurochemical studies link norepinephrine to behavioral symptoms in AD. It is thus critical to examine the integrity of the LC-TEC pathway in studying the early development of the disease, but there has been limited work in this direction. By leveraging the high-resolution and multi-shell diffusion MRI data from the Human Connectome Project (HCP), in this work we develop a novel method for the reconstruction of the LC-TEC pathway in a cohort of 40 HCP subjects carefully selected based on rigorous quality control of the residual distortion artifacts in the brainstem. A probabilistic atlas of the LC-TEC pathway of both hemispheres is then developed in the MNI152 space and distributed publicly on the NITRC website. To apply our atlas on clinical imaging data, we develop an automated approach to calculate the medial core of the LC-TEC pathway for localized analysis of connectivity changes. In a cohort of 138 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we demonstrate the detection of the decreased fiber integrity in the LC-TEC pathways with increasing disease severity.
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Affiliation(s)
- Wei Sun
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave., Los Angeles 90033, CA, USA
| | - Yuchun Tang
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave., Los Angeles 90033, CA, USA
- Department of Anatomy and Neurobiology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuchuan Qiao
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave., Los Angeles 90033, CA, USA
| | - Xinting Ge
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave., Los Angeles 90033, CA, USA
| | - Mara Mather
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - John M. Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shi
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave., Los Angeles 90033, CA, USA
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15
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Honnedevasthana Arun A, Connelly A, Smith RE, Calamante F. Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis. Neuroimage 2020; 225:117505. [PMID: 33147511 DOI: 10.1016/j.neuroimage.2020.117505] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 09/18/2020] [Accepted: 10/22/2020] [Indexed: 12/13/2022] Open
Abstract
The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.
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Affiliation(s)
- Arush Honnedevasthana Arun
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Alan Connelly
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Robert E Smith
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Fernando Calamante
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia; The University of Sydney, Sydney Imaging, Sydney, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia.
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16
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Davion JB, Kuchcinski G, Viard R, Dumont J, Pruvo JP, Leclerc X, Outteryck O, Lopes R. A Fully Automatic Method for Optic Radiation Tractography Applicable to Multiple Sclerosis Patients. Brain Topogr 2020; 33:533-544. [PMID: 32303949 DOI: 10.1007/s10548-020-00771-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 04/09/2020] [Indexed: 11/25/2022]
Abstract
The optic radiations (OR) are white matter tracts forming the posterior part of the visual ways. As an important inter-individual variability exists, atlases may be inefficient to locate the OR in a given subject. We designed a fully automatic method to delimitate the OR on a magnetic resonance imaging using tractography. On 15 healthy subjects, we evaluated the validity of our method by comparing the outputs to the Jülich post-mortem histological atlas, and its reproducibility. We also evaluated its feasibility on 98 multiple sclerosis (MS) patients. We correlated different visual outcomes with the inflammatory lesions volume within the OR reconstructed with different methods (our method, atlas, TractSeg). Our method reconstructed the OR bundle in all healthy subjects (< 2 h for most of them), and was reproducible. It demonstrated good classification indexes: sensitivity up to 0.996, specificity up to 0.993, Dice coefficient up to 0.842, and an area under the receiver operating characteristic (ROC) curve of 0.981. Our method reconstructed the OR in 91 of the 98 MS patients (92.9%, < 6 h for most of patients). Compared to an atlas-based approach and the TractSeg method, the inflammatory lesions volume in the OR measured with our method better correlated with the visual cortex volume, visual acuity and mean peripapillar retinal nerve fiber layer thickness. Our method seems to be efficient to reconstruct the OR in healthy subjects, and seems applicable to MS patients. It may be more relevant than an atlas based approach.
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Affiliation(s)
- Jean-Baptiste Davion
- Centre de référence des Maladies Neuromusculaires, CHU Lille, 59000, Lille, France.
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France.
| | - Gregory Kuchcinski
- Department of Neuroradiology, CHU Lille, Univ. Lille, Inserm U1171, 59000, Lille, France
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Romain Viard
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Julien Dumont
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Jean-Pierre Pruvo
- Department of Neuroradiology, CHU Lille, Univ. Lille, Inserm U1171, 59000, Lille, France
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Xavier Leclerc
- Department of Neuroradiology, CHU Lille, Univ. Lille, Inserm U1171, 59000, Lille, France
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Olivier Outteryck
- Department of Neuroradiology, CHU Lille, Univ. Lille, Inserm U1171, 59000, Lille, France
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
| | - Renaud Lopes
- Department of Neuroradiology, CHU Lille, Univ. Lille, Inserm U1171, 59000, Lille, France
- Clinical Imaging Core Facility, CI2C Lille, 59000, Lille, France
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17
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Lacerda LM, Clayden JD, Handley SE, Winston GP, Kaden E, Tisdall M, Cross JH, Liasis A, Clark CA. Microstructural Investigations of the Visual Pathways in Pediatric Epilepsy Neurosurgery: Insights From Multi-Shell Diffusion Magnetic Resonance Imaging. Front Neurosci 2020; 14:269. [PMID: 32322185 PMCID: PMC7158873 DOI: 10.3389/fnins.2020.00269] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 03/10/2020] [Indexed: 01/12/2023] Open
Abstract
Background Surgery is a key approach for achieving seizure freedom in children with focal onset epilepsy. However, the resection can affect or be in the vicinity of the optic radiations. Multi-shell diffusion MRI and tractography can better characterize tissue structure and provide guidance to help minimize surgical related deficits. Whilst in adults tractography has been used to demonstrate that damage to the optic radiations leads to postoperative visual field deficits, this approach has yet to be properly explored in children. Objective To demonstrate the capabilities of multi-shell diffusion MRI and tractography in characterizing microstructural changes in children with epilepsy pre- and post-surgery affecting the occipital, parietal or temporal lobes. Methods Diffusion Tensor Imaging and the Spherical Mean Technique were used to investigate the microstructure of the optic radiations. Furthermore, tractography was used to evaluate whether pre-surgical reconstructions of the optic radiations overlap with the resection margin as measured using anatomical post-surgical T1-weighted MRI. Results Increased diffusivity in patients compared to controls at baseline was observed with evidence of decreased diffusivity, anisotropy, and neurite orientation distribution in contralateral hemisphere after surgery. Pre-surgical optic radiation tractography overlapped with post-surgical resection margins in 20/43 (46%) children, and where visual data was available before and after surgery, the presence of overlap indicated a visual field deficit. Conclusion This is the first report in a pediatric series which highlights the relevance of tractography for future pre-surgical evaluation in children undergoing epilepsy surgery and the usefulness of multi-shell diffusion MRI to characterize brain microstructure in these patients.
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Affiliation(s)
- Luís M Lacerda
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Jonathan D Clayden
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Sian E Handley
- Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Foundation Trust, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Division of Neurology, Department of Medicine, Queen's University, Kingston, ON, Canada
| | - Enrico Kaden
- Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Martin Tisdall
- Department of Neurosurgery, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - J Helen Cross
- Clinical Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Alki Liasis
- Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Foundation Trust, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.,Children's Hospital of Pittsburgh, University of Pittsburgh Medical Centre, Pittsburgh, PA, United States
| | - Chris A Clark
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
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18
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Nie X, Shi Y. Topographic Filtering of Tractograms as Vector Field Flows. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2019; 11766:564-572. [PMID: 33860289 PMCID: PMC8046176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
While diffusion MRI (dMRI) is currently the most widely used in vivo imaging tool for studying brain connectivity, the biological validity of the tractography techniques based on dMRI is often debated. The wide presence of topographic regularity in various brain circuits provides a unique opportunity to examine and improve the reliability of tractography results. In this work, we develop a novel framework for the analysis of the topographic regularity of brain connectivity generated by modern FOD-based tractography techniques. Our method is based on the consistency between the mathematical property of smooth vector field flows and topographically regular fiber tracts. The main idea of our method is that we compute a principal vector field (PVF) for a given tractogram from the FODs by solving a Markov Random Field problem. By quantifying the consistency between each tract and the PVF, we develop a Vector Flow Deviation (VFD) measure and apply it to filter out topographically irregular tracts. In our experiments, we successfully applied our method to remove irregular fiber tracts in two fiber bundles with known connectopy: the visual pathway and the colossal motor pathway, which were reconstructed from the multi-shell diffusion imaging data of the Human Connectome Project (HCP). We also performed quantitative evaluation based on a G2SD distance proposed in previous work to quantitatively demonstrate the effectiveness of our filtering method.
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Affiliation(s)
- Xinyu Nie
- USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90032, USA
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles CA 90089, USA
| | - Yonggang Shi
- USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90032, USA
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles CA 90089, USA
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19
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Takemura H, Pestilli F, Weiner KS. Comparative neuroanatomy: Integrating classic and modern methods to understand association fibers connecting dorsal and ventral visual cortex. Neurosci Res 2019; 146:1-12. [PMID: 30389574 PMCID: PMC6491271 DOI: 10.1016/j.neures.2018.10.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 10/19/2018] [Accepted: 10/25/2018] [Indexed: 12/13/2022]
Abstract
Comparative neuroanatomy studies improve understanding of brain structure and function and provide insight regarding brain development, evolution, and also what features of the brain are uniquely human. With modern methods such as diffusion MRI (dMRI) and quantitative MRI (qMRI), we are able to measure structural features of the brain with the same methods across human and non-human primates. In this review article, we discuss how recent dMRI measurements of vertical occipital connections in humans and macaques can be compared with previous findings from invasive anatomical studies that examined connectivity, including relatively forgotten classic strychnine neuronography studies. We then review recent progress in understanding the neuroanatomy of vertical connections within the occipitotemporal cortex by combining modern quantitative MRI and classical histological measurements in human and macaque. Finally, we a) discuss current limitations of dMRI and tractography and b) consider potential paths for future investigations using dMRI and tractography for comparative neuroanatomical studies of white matter tracts between species. While we focus on vertical association connections in visual cortex in the present paper, this same approach can be applied to other white matter tracts. Similar efforts are likely to continue to advance our understanding of the neuroanatomical features of the brain that are shared across species, as well as to distinguish the features that are uniquely human.
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Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.
| | - Franco Pestilli
- Departments of Psychological and Brain Sciences, Computer Science and Intelligent Systems Engineering, Programs in Neuroscience and Cognitive Science, School of Optometry, Indiana University, Bloomington, IN, USA
| | - Kevin S Weiner
- Department of Psychology, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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20
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Review: Using diffusion-weighted magnetic resonance imaging techniques to explore the microstructure and connectivity of subcortical white matter tracts in the human auditory system. Hear Res 2019; 377:1-11. [DOI: 10.1016/j.heares.2019.02.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 02/16/2019] [Accepted: 02/26/2019] [Indexed: 12/13/2022]
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21
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Aydogan DB, Shi Y. Tracking and validation techniques for topographically organized tractography. Neuroimage 2018; 181:64-84. [PMID: 29986834 PMCID: PMC6139055 DOI: 10.1016/j.neuroimage.2018.06.071] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 05/18/2018] [Accepted: 06/26/2018] [Indexed: 12/22/2022] Open
Abstract
Topographic regularity of axonal connections is commonly understood as the preservation of spatial relationships between nearby neurons and is a fundamental structural property of the brain. In particular the retinotopic mapping of the visual pathway can even be quantitatively computed. Inspired from this previously untapped anatomical knowledge, we propose a novel tractography method that preserves both topographic and geometric regularity. We make use of parameterized curves with Frenet-Serret frame and introduce a highly flexible mechanism for controlling geometric regularity. At the same time, we incorporate a novel local data support term in order to account for topographic organization. Unifying geometry with topographic regularity, we develop a Bayesian framework for generating highly organized streamlines that accurately follow neuroanatomy. We additionally propose two novel validation techniques to quantify topographic regularity. In our experiments, we studied the results of our approach with respect to connectivity, reproducibility and topographic regularity aspects. We present both qualitative and quantitative comparisons of our technique against three algorithms from MRtrix3. We show that our method successfully generates highly organized fiber tracks while capturing bundle anatomy that are geometrically challenging for other approaches.
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Affiliation(s)
- Dogu Baran Aydogan
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Schurr R, Duan Y, Norcia AM, Ogawa S, Yeatman JD, Mezer AA. Tractography optimization using quantitative T1 mapping in the human optic radiation. Neuroimage 2018; 181:645-658. [DOI: 10.1016/j.neuroimage.2018.06.060] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 06/03/2018] [Accepted: 06/20/2018] [Indexed: 12/31/2022] Open
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Zhang F, Wu Y, Norton I, Rigolo L, Rathi Y, Makris N, O'Donnell LJ. An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan. Neuroimage 2018; 179:429-447. [PMID: 29920375 PMCID: PMC6080311 DOI: 10.1016/j.neuroimage.2018.06.027] [Citation(s) in RCA: 106] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 05/01/2018] [Accepted: 06/08/2018] [Indexed: 12/15/2022] Open
Abstract
This work presents an anatomically curated white matter atlas to enable consistent white matter tract parcellation across different populations. Leveraging a well-established computational pipeline for fiber clustering, we create a tract-based white matter atlas including information from 100 subjects. A novel anatomical annotation method is proposed that leverages population-based brain anatomical information and expert neuroanatomical knowledge to annotate and categorize the fiber clusters. A total of 256 white matter structures are annotated in the proposed atlas, which provides one of the most comprehensive tract-based white matter atlases covering the entire brain to date. These structures are composed of 58 deep white matter tracts including major long range association and projection tracts, commissural tracts, and tracts related to the brainstem and cerebellar connections, plus 198 short and medium range superficial fiber clusters organized into 16 categories according to the brain lobes they connect. Potential false positive connections are annotated in the atlas to enable their exclusion from analysis or visualization. In addition, the proposed atlas allows for a whole brain white matter parcellation into 800 fiber clusters to enable whole brain connectivity analyses. The atlas and related computational tools are open-source and publicly available. We evaluate the proposed atlas using a testing dataset of 584 diffusion MRI scans from multiple independently acquired populations, across genders, the lifespan (1 day-82 years), and different health conditions (healthy control, neuropsychiatric disorders, and brain tumor patients). Experimental results show successful white matter parcellation across subjects from different populations acquired on multiple scanners, irrespective of age, gender or disease indications. Over 99% of the fiber tracts annotated in the atlas were detected in all subjects on average. One advantage in terms of robustness is that the tract-based pipeline does not require any cortical or subcortical segmentations, which can have limited success in young children and patients with brain tumors or other structural lesions. We believe this is the first demonstration of consistent automated white matter tract parcellation across the full lifespan from birth to advanced age.
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Affiliation(s)
- Fan Zhang
- Harvard Medical School, Boston, USA.
| | - Ye Wu
- Harvard Medical School, Boston, USA
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24
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Wang J, Shi Y. GIFE: Efficient and Robust Group-wise Isometric Fiber Embedding. CONNECTOMICS IN NEUROIMAGING : SECOND INTERNATIONAL WORKSHOP, CNI 2018, HELD IN CONJUNCTION WITH MICCAI 2018, GRANADA, SPAIN, SEPTEMBER 20, 2018 : PROCEEDINGS. CNI (WORKSHOP) (2ND : 2018 : GRANADA, SPAIN) 2018; 11083:20-28. [PMID: 31468034 PMCID: PMC6715136 DOI: 10.1007/978-3-030-00755-3_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Tractography is a prevalent technique for in vivo imaging of the white matter fibers (a.k.a. the tractograms), but it is also known to be error-prone. We previously propose the Group-wise Tractogram Analysis (GiTA) framework for identifying anatomically valid fibers across subjects according to cross-subject consistency. However, the original framework is based on computationally expensive brute-force KNN search. In this work, we propose a more general and efficient extension of GiTA. Our main idea is to find the finite dimensional vector-space representation of the fiber tracts of varied lengths across different subjects, and we call it the group-wise isometric fiber embedding (GIFE). This novel GIFE framework enables the application of the powerful and efficient vector space data analysis methods, such as the k-d tree KNN search, to GiTA. However, the conventional isometric embedding frameworks are not suitable for GIFE due to the massive fiber tracts and the registration errors in the original GiTA framework. To address these issues, we propose a novel method called multidimensional extrapolating (MDE) to achieve GIFE. In our experiment, simulation results show quantitatively that our method outperforms the other methods in terms of computational efficiency/tractability and robustness to errors in distance measurements for real fiber embedding. In addition, real experiment for group-wise optic radiation bundle reconstruction also shows clear improvement in anatomical validity of the results from our MDE method for 47 different subjects from the Human Connectome Project, compared to the results of other fiber embedding methods.
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Affiliation(s)
- Junyan Wang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
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25
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Chamberland M, Tax CMW, Jones DK. Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware. Neuroimage Clin 2018; 20:458-465. [PMID: 30128284 PMCID: PMC6096050 DOI: 10.1016/j.nicl.2018.08.021] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 07/31/2018] [Accepted: 08/10/2018] [Indexed: 12/19/2022]
Abstract
Introduction Surgical resection is an effective treatment for temporal lobe epilepsy but can result in visual field defects. This could be minimized if surgeons knew the exact location of the anterior part of the optic radiation (OR), the Meyer's loop. To this end, there is increasing prevalence of image-guided surgery using diffusion MRI tractography. Despite considerable effort in developing analysis methods, a wide discrepancy in Meyer's loop reconstructions is observed in the literature. Moreover, the impact of differences in image acquisition on Meyer's loop tractography remains unclear. Here, while employing the same state-of-the-art analysis protocol, we explored the extent to which variance in data acquisition leads to variance in OR reconstruction. Methods Diffusion MRI data were acquired for the same thirteen healthy subjects using standard and state-of-the-art protocols on three scanners with different maximum gradient amplitudes (MGA): Siemens Connectom (MGA = 300 mT/m); Siemens Prisma (MGA = 80 mT/m) and GE Excite-HD (MGA = 40 mT/m). Meyer's loop was reconstructed on all subjects and its distance to the temporal pole (ML-TP) was compared across protocols. Results A significant effect of data acquisition on the ML-TP distance was observed between protocols (p < .01 to 0.0001). The biggest inter-acquisition discrepancy for the same subject across different protocols was 16.5 mm (mean: 9.4 mm, range: 3.7-16.5 mm). Conclusion We showed that variance in data acquisition leads to substantive variance in OR tractography. This has direct implications for neurosurgical planning, where part of the OR is at risk due to an under-estimation of its location using conventional acquisition protocols.
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Affiliation(s)
- Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom; School of Psychology, Faculty of Health Sciences, Australian Catholic University, Victoria, Australia
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Wang J, Aydogan DB, Varma R, Toga AW, Shi Y. Modeling topographic regularity in structural brain connectivity with application to tractogram filtering. Neuroimage 2018; 183:87-98. [PMID: 30081193 DOI: 10.1016/j.neuroimage.2018.07.068] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 07/27/2018] [Accepted: 07/31/2018] [Indexed: 11/27/2022] Open
Abstract
Topographic regularity is an important biological principle in brain connections that has been observed in various anatomical studies. However, there has been limited research on mathematically characterizing this property and applying it in the analysis of in vivo connectome imaging data. In this work, we propose a general mathematical model of topographic regularity for white matter fiber bundles based on previous neuroanatomical understanding. Our model is based on a novel group spectral graph analysis (GSGA) framework motivated by spectral graph theory and tensor decomposition. The GSGA provides a common set of eigenvectors for the graphs formed by topographic proximity of nearby tracts, which gives rises to the group graph spectral distance, or G2SD, for measuring the topographic regularity of each fiber tract in a tractogram. Based on this novel model of topographic regularity in fiber tracts, we then develop a tract filtering algorithm that can generally be applied to remove outliers in tractograms generated by any tractography algorithm. In the experimental results, we show that our novel algorithm outperforms existing methods in both simulation data from ISMRM 2015 Tractography Challenge and real data from the Human Connectome Project (HCP). On a large-scale dataset from 215 HCP subjects, we quantitatively show our method can significantly improve the retinotopy in the reconstruction of the optic radiation bundle. The software for the tract filtering algorithm developed in this work has also been publicly released on NITRC (https://www.nitrc.org/projects/connectopytool).
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Affiliation(s)
- Junyan Wang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Dogu Baran Aydogan
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Rohit Varma
- USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
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27
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Aydogan DB, Jacobs R, Dulawa S, Thompson SL, Francois MC, Toga AW, Dong H, Knowles JA, Shi Y. When tractography meets tracer injections: a systematic study of trends and variation sources of diffusion-based connectivity. Brain Struct Funct 2018; 223:2841-2858. [PMID: 29663135 PMCID: PMC5997540 DOI: 10.1007/s00429-018-1663-8] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Accepted: 04/08/2018] [Indexed: 12/23/2022]
Abstract
Tractography is a powerful technique capable of non-invasively reconstructing the structural connections in the brain using diffusion MRI images, but the validation of tractograms is challenging due to lack of ground truth. Owing to recent developments in mapping the mouse brain connectome, high-resolution tracer injection-based axonal projection maps have been created and quickly adopted for the validation of tractography. Previous studies using tracer injections mainly focused on investigating the match in projections and optimal tractography protocols. Being a complicated technique, however, tractography relies on multiple stages of operations and parameters. These factors introduce large variabilities in tractograms, hindering the optimization of protocols and making the interpretation of results difficult. Based on this observation, in contrast to previous studies, in this work we focused on quantifying and ranking the amount of performance variation introduced by these factors. For this purpose, we performed over a million tractography experiments and studied the variability across different subjects, injections, anatomical constraints and tractography parameters. By using N-way ANOVA analysis, we show that all tractography parameters are significant and importantly performance variations with respect to the differences in subjects are comparable to the variations due to tractography parameters, which strongly underlines the importance of fully documenting the tractography protocols in scientific experiments. We also quantitatively show that inclusion of anatomical constraints is the most significant factor for improving tractography performance. Although this critical factor helps reduce false positives, our analysis indicates that anatomy-informed tractography still fails to capture a large portion of axonal projections.
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Affiliation(s)
- Dogu Baran Aydogan
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA.
| | - Russell Jacobs
- Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Stephanie Dulawa
- Department of Psychiatry, University of California at San Diego, San Diego, CA, 90089, USA
| | - Summer L Thompson
- Department of Psychiatry, University of California at San Diego, San Diego, CA, 90089, USA
- Committee on Neurobiology, University of Chicago, Chicago, IL, 60637, USA
| | - Maite Christi Francois
- Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Hongwei Dong
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - James A Knowles
- Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
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Lennartsson F, Nilsson M, Flodmark O, Jacobson L, Larsson J. Injuries to the Immature Optic Radiation Show Correlated Thinning of the Macular Ganglion Cell Layer. Front Neurol 2018; 9:321. [PMID: 29867730 PMCID: PMC5950728 DOI: 10.3389/fneur.2018.00321] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 04/23/2018] [Indexed: 12/13/2022] Open
Abstract
Injuries to the immature optic radiation (OR) are associated with thinning of the retinal nerve fiber layer and corresponding visual field (VF) defects. The aim of the current study was to seek evidence for causal retrograde trans-synaptic degeneration by exploring the correspondence between the localization and extension of the injury to the OR and the structure of the macular ganglion cell complex, and the relation to VF function. Seven adults (age range 18–35) with visual dysfunction secondary to white-matter damage of immaturity and six healthy adults (age range 22–33) underwent magnetic resonance imaging (MRI). Fiber tractography was used to generate the geniculate projections to the dorsal and ventral striate cortex, delineated by retinotopic functional MRI mapping. The structure of the macular ganglion cell complex was measured with optical coherence tomography. The tractography showed overlaps between the dorsal and ventral geniculo-striate projections. However, in four patients with inferior VF defects, the dorsal projections were to a large extent traversing the space normally solely occupied by ventral projections. This is consistent with structural changes to the OR and suggests of re-organization upon injury. Diffusion parameters were significantly different between patients and controls, and most pronounced in the dorsal geniculo-striate projections, with a pattern indicating primary injury. The macular ganglion cell complex was significantly thinner in the patients and most pronounced in the superior sectors; a pattern particularly evident in the four patients with inferior VF defects. The ratio of the mean thickness of the macular ganglion cell complex in the superior and inferior sectors significantly correlated with the axial and mean diffusivities in the contra- and ipsilateral dorsal striate projections. The results suggest a causal link between injuries to the superior portion of the immature OR and secondary thinning in the macular ganglion cell complex, resulting in inferior VF defects.
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Affiliation(s)
- Finn Lennartsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Maria Nilsson
- Unit of Optometry, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Olof Flodmark
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Lena Jacobson
- Ophthalmology and Vision, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jonas Larsson
- Department of Psychology, Royal Holloway, University of London, Egham, United Kingdom
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Tang Y, Sun W, Toga AW, Ringman JM, Shi Y. A probabilistic atlas of human brainstem pathways based on connectome imaging data. Neuroimage 2018; 169:227-239. [PMID: 29253653 PMCID: PMC5856609 DOI: 10.1016/j.neuroimage.2017.12.042] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 12/05/2017] [Accepted: 12/14/2017] [Indexed: 11/26/2022] Open
Abstract
The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways.
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Affiliation(s)
- Yuchun Tang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Jinan, Shandong, China
| | - Wei Sun
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Wang C, Klistorner A, Ly L, Barnett MH. White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques. PLoS One 2018; 13:e0191131. [PMID: 29342192 PMCID: PMC5771610 DOI: 10.1371/journal.pone.0191131] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2017] [Accepted: 12/28/2017] [Indexed: 11/23/2022] Open
Abstract
The posterior visual pathway is commonly affected by multiple sclerosis (MS) pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS. Therefore, a reliable and robust imaging segmentation method for in-vivo delineation of the optic radiations (OR) is needed. However, diffusion-based tractography approaches, which are typically used for OR segmentation are confounded by the presence of focal white matter lesions. Current solutions require complex acquisition paradigms and demand expert image analysis, limiting application in both clinical trials and clinical practice. In the current study, using data acquired in a clinical setting on a 3T scanner, we optimised and compared two approaches for optic radiation (OR) reconstruction: individual probabilistic tractography-based and template-based methods. OR segmentation results were applied to subjects with MS and volumetric and diffusivity parameters were compared between OR segmentation techniques. Despite differences in reconstructed OR volumes, both OR lesion volume and OR diffusivity measurements in MS subjects were highly comparable using optimised probabilistic tractography-based, and template-based, methods. The choice of OR reconstruction technique should be determined primarily by the research question and the nature of the available dataset. Template-based approaches are particularly suited to the semi-automated analysis of large image datasets and have utility even in the absence of dMRI acquisitions. Individual tractography methods, while more complex than template based OR reconstruction, permit measurement of diffusivity changes along fibre bundles that are affected by specific MS lesions or other focal pathologies.
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Affiliation(s)
- Chenyu Wang
- Sydney Neuroimaging Analysis Centre, Sydney, New South Wales, Australia
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Alexander Klistorner
- Sydney Neuroimaging Analysis Centre, Sydney, New South Wales, Australia
- Department of Ophthalmology, Save Sight Institute, University of Sydney, Sydney, New South Wales, Australia
- Australian School of Advanced Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Linda Ly
- Sydney Neuroimaging Analysis Centre, Sydney, New South Wales, Australia
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Michael H. Barnett
- Sydney Neuroimaging Analysis Centre, Sydney, New South Wales, Australia
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
- * E-mail:
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Bollaerts I, Veys L, Geeraerts E, Andries L, De Groef L, Buyens T, Salinas-Navarro M, Moons L, Van Hove I. Complementary research models and methods to study axonal regeneration in the vertebrate retinofugal system. Brain Struct Funct 2017; 223:545-567. [DOI: 10.1007/s00429-017-1571-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Accepted: 11/15/2017] [Indexed: 01/18/2023]
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32
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Shi Y, Toga AW. Connectome imaging for mapping human brain pathways. Mol Psychiatry 2017; 22:1230-1240. [PMID: 28461700 PMCID: PMC5568931 DOI: 10.1038/mp.2017.92] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 02/06/2017] [Accepted: 02/24/2017] [Indexed: 01/23/2023]
Abstract
With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research.
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Affiliation(s)
- Y Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Meesters S, Ossenblok P, Wagner L, Schijns O, Boon P, Florack L, Vilanova A, Duits R. Stability metrics for optic radiation tractography: Towards damage prediction after resective surgery. J Neurosci Methods 2017; 288:34-44. [PMID: 28648721 PMCID: PMC5538260 DOI: 10.1016/j.jneumeth.2017.05.029] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Revised: 04/25/2017] [Accepted: 05/31/2017] [Indexed: 11/28/2022]
Abstract
BACKGROUND An accurate delineation of the optic radiation (OR) using diffusion MR tractography may reduce the risk of a visual field deficit after temporal lobe resection. However, tractography is prone to generate spurious streamlines, which deviate strongly from neighboring streamlines and hinder a reliable distance measurement between the temporal pole and the Meyer's loop (ML-TP distance). NEW METHOD Stability metrics are introduced for the automated removal of spurious streamlines near the Meyer's loop. Firstly, fiber-to-bundle coherence (FBC) measures can identify spurious streamlines by estimating their alignment with the surrounding streamline bundle. Secondly, robust threshold selection removes spurious streamlines while preventing an underestimation of the extent of the Meyer's loop. Standardized parameter selection is realized through test-retest evaluation of the variability in ML-TP distance. RESULTS The variability in ML-TP distance after parameter selection was below 2mm for each of the healthy volunteers studied (N=8). The importance of the stability metrics is illustrated for epilepsy surgery candidates (N=3) for whom the damage to the Meyer's loop was evaluated by comparing the pre- and post-operative OR reconstruction. The difference between predicted and observed damage is in the order of a few millimeters, which is the error in measured ML-TP distance. COMPARISON WITH EXISTING METHOD(S) The stability metrics are a novel method for the robust estimate of the ML-TP distance. CONCLUSIONS The stability metrics are a promising tool for clinical trial studies, in which the damage to the OR can be related to the visual field deficit that may occur after epilepsy surgery.
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Affiliation(s)
- Stephan Meesters
- Academic Center for Epileptology Kempenhaeghe & Maastricht University Medical Center, Netherlands; Department of Mathematics & Computer Science, Eindhoven University of Technology, Netherlands.
| | - Pauly Ossenblok
- Academic Center for Epileptology Kempenhaeghe & Maastricht University Medical Center, Netherlands; Department of Biomedical Engineering, Eindhoven University of Technology, Netherlands
| | - Louis Wagner
- Academic Center for Epileptology Kempenhaeghe & Maastricht University Medical Center, Netherlands
| | - Olaf Schijns
- Academic Center for Epileptology Kempenhaeghe & Maastricht University Medical Center, Netherlands; Department of Neurosurgery, Maastricht University Medical Center, Netherlands
| | - Paul Boon
- Academic Center for Epileptology Kempenhaeghe & Maastricht University Medical Center, Netherlands
| | - Luc Florack
- Department of Mathematics & Computer Science, Eindhoven University of Technology, Netherlands
| | - Anna Vilanova
- Department of Mathematics and Computer Science, Delft University of Technology, Netherlands; Department of Mathematics & Computer Science, Eindhoven University of Technology, Netherlands
| | - Remco Duits
- Department of Mathematics & Computer Science, Eindhoven University of Technology, Netherlands
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Essayed WI, Zhang F, Unadkat P, Cosgrove GR, Golby AJ, O'Donnell LJ. White matter tractography for neurosurgical planning: A topography-based review of the current state of the art. Neuroimage Clin 2017; 15:659-672. [PMID: 28664037 PMCID: PMC5480983 DOI: 10.1016/j.nicl.2017.06.011] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 04/17/2017] [Accepted: 06/08/2017] [Indexed: 12/13/2022]
Abstract
We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods. We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.
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Affiliation(s)
- Walid I Essayed
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Fan Zhang
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Prashin Unadkat
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - G Rees Cosgrove
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexandra J Golby
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lauren J O'Donnell
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Wang J, Aydogan DB, Varma R, Toga AW, Shi Y. Topographic Regularity for Tract Filtering in Brain Connectivity. INFORMATION PROCESSING IN MEDICAL IMAGING : PROCEEDINGS OF THE ... CONFERENCE 2017; 10265:263-274. [PMID: 28943732 DOI: 10.1007/978-3-319-59050-9_21] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The preservation of the spatial relationships among axonal pathways has long been studied and known to be critical for many functions of the brain. Being a fundamental property of the brain connections, there is an intuitive understanding of topographic regularity in neuroscience but yet to be systematically explored in connectome imaging research. In this work, we propose a general mathematical model for topographic regularity of fiber bundles that is consistent with its neuroanatomical understanding. Our model is based on a novel group spectral graph analysis (GSGA) framework motivated by spectral graph theory and tensor decomposition. GSGA provides a common set of eigenvectors for the graphs formed by topographic proximity measures whose preservation along individual tracts in return is modeled as topographic regularity. To demonstrate the application of this novel measure of topographic regularity, we apply it to filter fiber tracts from connectome imaging. Using large-scale data from the Human Connectome Project (HCP), we show that our novel algorithm can achieve better performance than existing methods on the filtering of both individual bundles and whole brain tractograms.
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Affiliation(s)
- Junyan Wang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033
| | - Dogu Baran Aydogan
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033
| | - Rohit Varma
- USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033
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Rokem A, Takemura H, Bock AS, Scherf KS, Behrmann M, Wandell BA, Fine I, Bridge H, Pestilli F. The visual white matter: The application of diffusion MRI and fiber tractography to vision science. J Vis 2017; 17:4. [PMID: 28196374 PMCID: PMC5317208 DOI: 10.1167/17.2.4] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Accepted: 12/12/2016] [Indexed: 12/19/2022] Open
Abstract
Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data.
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Affiliation(s)
- Ariel Rokem
- The University of Washington eScience Institute, Seattle, WA, ://arokem.org
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita-shi, JapanGraduate School of Frontier Biosciences, Osaka University, Suita-shi,
| | | | | | | | | | - Ione Fine
- University of Washington, Seattle, WA,
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Chamberland M, Scherrer B, Prabhu SP, Madsen J, Fortin D, Whittingstall K, Descoteaux M, Warfield SK. Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET). Hum Brain Mapp 2017; 38:509-527. [PMID: 27647682 PMCID: PMC5333642 DOI: 10.1002/hbm.23399] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Revised: 08/04/2016] [Accepted: 08/31/2016] [Indexed: 12/19/2022] Open
Abstract
Streamline tractography algorithms infer connectivity from diffusion MRI (dMRI) by following diffusion directions which are similarly aligned between neighboring voxels. However, not all white matter (WM) fascicles are organized in this manner. For example, Meyer's loop is a highly curved portion of the optic radiation (OR) that exhibits a narrow turn, kissing and crossing pathways, and changes in fascicle dispersion. From a neurosurgical perspective, damage to Meyer's loop carries a potential risk of inducing vision deficits to the patient, especially during temporal lobe resection surgery. To prevent such impairment, achieving an accurate delineation of Meyer's loop with tractography is thus of utmost importance. However, current algorithms tend to under-estimate the full extent of Meyer's loop, mainly attributed to the aforementioned rule for connectivity which requires a direction to be chosen across a field of orientations. In this article, it was demonstrated that MAGNEtic Tractography (MAGNET) can benefit Meyer's loop delineation by incorporating anatomical knowledge of the expected fiber orientation to overcome local ambiguities. A new ROI-mechanism was proposed which supplies additional information to streamline reconstruction algorithms by the means of oriented priors. Their results showed that MAGNET can accurately generate Meyer's loop in all of our 15 child subjects (8 males; mean age 10.2 years ± 3.1). It effectively improved streamline coverage when compared with deterministic tractography, and significantly reduced the distance between the anterior-most portion of Meyer's loop and the temporal pole by 16.7 mm on average, a crucial landmark used for preoperative planning of temporal lobe surgery. Hum Brain Mapp 38:509-527, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Maxime Chamberland
- Centre de Recherche CHUSUniversity of SherbrookeSherbrookeCanada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of ScienceUniversity of SherbrookeSherbrookeCanada
- Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health ScienceUniversity of SherbrookeSherbrookeCanada
| | - Benoit Scherrer
- Department of RadiologyBoston Children's Hospital and Harvard Medical School300 Longwood AvenueBostonMassachusettsUSA
| | - Sanjay P. Prabhu
- Department of RadiologyBoston Children's Hospital and Harvard Medical School300 Longwood AvenueBostonMassachusettsUSA
| | - Joseph Madsen
- Department of RadiologyBoston Children's Hospital and Harvard Medical School300 Longwood AvenueBostonMassachusettsUSA
| | - David Fortin
- Centre de Recherche CHUSUniversity of SherbrookeSherbrookeCanada
- Division of Neurosurgery and Neuro‐Oncology, Faculty of Medicine and Health ScienceUniversity of SherbrookeSherbrookeCanada
| | - Kevin Whittingstall
- Centre de Recherche CHUSUniversity of SherbrookeSherbrookeCanada
- Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health ScienceUniversity of SherbrookeSherbrookeCanada
- Department of Diagnostic Radiology, Faculty of Medicine and Health ScienceUniversity of SherbrookeSherbrookeCanada
| | - Maxime Descoteaux
- Centre de Recherche CHUSUniversity of SherbrookeSherbrookeCanada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of ScienceUniversity of SherbrookeSherbrookeCanada
| | - Simon K. Warfield
- Department of RadiologyBoston Children's Hospital and Harvard Medical School300 Longwood AvenueBostonMassachusettsUSA
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Sivakanthan S, Neal E, Murtagh R, Vale FL. The evolving utility of diffusion tensor tractography in the surgical management of temporal lobe epilepsy: a review. Acta Neurochir (Wien) 2016; 158:2185-2193. [PMID: 27566714 DOI: 10.1007/s00701-016-2910-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 07/27/2016] [Indexed: 11/29/2022]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) is a relatively new imaging modality that has found many peri-operative applications in neurosurgery. METHODS A comprehensive survey of the applications of diffusion tensor imaging (DTI) in planning for temporal lobe epilepsy surgery was conducted. The presentation of this literature is supplemented by a case illustration. RESULTS The authors have found that DTI is well utilized in epilepsy surgery, primarily in the tractography of Meyer's loop. DTI has also been used to demonstrate extratemporal connections that may be responsible for surgical failure as well as perioperative planning. The tractographic anatomy of the temporal lobe is discussed and presented with original DTI pictures. CONCLUSIONS The uses of DTI in epilepsy surgery are varied and rapidly evolving. A discussion of the technology, its limitations, and its applications is well warranted and presented in this article.
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Affiliation(s)
- Sananthan Sivakanthan
- Department of Neurosurgery and Brain Repair, University of South Florida, Morsani College of Medicine, 2 Tampa General Circle, 7th Floor, Tampa, FL, 33606, USA.
| | - Elliot Neal
- Department of Neurosurgery and Brain Repair, University of South Florida, Morsani College of Medicine, 2 Tampa General Circle, 7th Floor, Tampa, FL, 33606, USA
- Brainlab Inc, Westchester, IL, USA
| | - Ryan Murtagh
- Department of Radiology, University of South Florida, Morsani College of Medicine, Tampa, FL, USA
| | - Fernando L Vale
- Department of Neurosurgery and Brain Repair, University of South Florida, Morsani College of Medicine, 2 Tampa General Circle, 7th Floor, Tampa, FL, 33606, USA
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Abstract
While tractography is widely used in brain imaging research, its quantitative validation is highly difficult. Many fiber systems, however, have well-known topographic organization which can even be quantitatively mapped such as the retinotopy of visual pathway. Motivated by this previously untapped anatomical knowledge, we develop a novel tractography method that preserves both topographic and geometric regularity of fiber systems. For topographic preservation, we propose a novel likelihood function that tests the match between parallel curves and fiber orientation distributions. For geometric regularity, we use Gaussian distributions of Frenet-Serret frames. Taken together, we develop a Bayesian framework for generating highly organized tracks that accurately follow neuroanatomy. Using multi-shell diffusion images of 56 subjects from Human Connectome Project, we compare our method with algorithms from MRtrix. By applying regression analysis between retinotopic eccentricity and tracks, we quantitatively demonstrate that our method achieves superior performance in preserving the retinotopic organization of optic radiation.
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Renauld E, Descoteaux M, Bernier M, Garyfallidis E, Whittingstall K. Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves. PLoS One 2016; 11:e0156436. [PMID: 27383146 PMCID: PMC4934857 DOI: 10.1371/journal.pone.0156436] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 05/13/2016] [Indexed: 12/13/2022] Open
Abstract
At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI.
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Affiliation(s)
- Emmanuelle Renauld
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, Qc, Canada
- Centre d’Imagerie Moléculaire de Sherbrooke (CIMS), Centre de Recherche du CHUS, Sherbrooke, Qc, Canada
| | - Michaël Bernier
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Eleftherios Garyfallidis
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Kevin Whittingstall
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Department of Diagnostic Radiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, Qc, Canada
- Centre d’Imagerie Moléculaire de Sherbrooke (CIMS), Centre de Recherche du CHUS, Sherbrooke, Qc, Canada
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Cunningham SI, Shi Y, Weiland JD, Falabella P, Olmos de Koo LC, Zacks DN, Tjan BS. Feasibility of Structural and Functional MRI Acquisition with Unpowered Implants in Argus II Retinal Prosthesis Patients: A Case Study. Transl Vis Sci Technol 2015; 4:6. [PMID: 26693097 DOI: 10.1167/tvst.4.6.6] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 09/27/2015] [Indexed: 11/24/2022] Open
Abstract
PURPOSE Magnetic resonance imaging (MRI) can measure the effects of vision loss and recovery on brain function and structure. In this case study, we sought to determine the feasibility of acquiring anatomical and functional MRI data in recipients of the Argus II epiretinal prosthesis system. METHODS Following successful implantation with the Argus II device, two retinitis pigmentosa (RP) patients completed MRI scans with their implant unpowered to measure primary visual cortex (V1) functional responses to a tactile task, whole-brain morphometry, V1 cortical thickness, and diffusion properties of the optic tract and optic radiation. Measurements in the subjects with the Argus II implant were compared to measurements obtained previously from RP patients and sighted individuals. RESULTS The presence of the Argus II implant resulted in artifacts that were localized around the patient's implanted eye and did not extend into cortical regions or white matter tracts associated with the visual system. Structural data on V1 cortical thickness and the retinofugal tract obtained from the two Argus II subjects fell within the ranges of sighted and RP groups. When compared to the RP and sighted subjects, Argus II patients' tactile-evoked cross-modal functional MRI (fMRI) blood oxygen level-dependent (BOLD) responses in V1 also fell within the range of either sighted or RP groups, apparently depending on time since implantation. CONCLUSIONS This study demonstrates that successful acquisition and quantification of structural and functional MR images are feasible in the presence of the inactive implant and provides preliminary information on functional changes in the brain that may follow sight restoration treatments. TRANSITIONAL RELEVANCE Successful MRI and fMRI acquisition in Argus II recipients demonstrates feasibility of using MRI to study the effect of retinal prosthesis use on brain structure and function.
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Affiliation(s)
- Samantha I Cunningham
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - James D Weiland
- USC Eye Institute, University of Southern California, Los Angeles, CA, USA
| | - Paulo Falabella
- USC Eye Institute, University of Southern California, Los Angeles, CA, USA ; Department of Ophthalmology and Visual Sciences, Federal University of São Paulo, São Paulo, Brazil
| | | | - David N Zacks
- Kellogg Eye Center, University of Michigan, Ann Arbor, MI, USA
| | - Bosco S Tjan
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA ; Department of Psychology, University of Southern California, Los Angeles, CA, USA
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