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Pawar PR, Booth J, Neely A, McIlwaine G, Lueck CJ. Nerve fibre organisation in the human optic nerve and chiasm: what do we really know? Eye (Lond) 2024; 38:2457-2471. [PMID: 38849598 PMCID: PMC11306597 DOI: 10.1038/s41433-024-03137-7] [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: 12/21/2023] [Revised: 04/30/2024] [Accepted: 05/07/2024] [Indexed: 06/09/2024] Open
Abstract
A recent anatomical study of the human optic chiasm cast doubt on the widespread assumption that nerve fibres travelling in the human optic nerve and chiasm are arranged retinotopically. Accordingly, a scoping literature review was performed to determine what is known about the nerve fibre arrangement in these structures. Meta-analysis suggested that the average number of fibres in each optic nerve was 1.023 million with an inter-individual range of approximately 50% of the mean. Loss of nerve fibres with age (approximately 3,400 fibres/year) could not account for this variability. The review suggested that there might be a retinotopic arrangement of nerve fibres in the orbital portion of the optic nerve but that this arrangement is most likely to be lost posteriorly with a more random distribution of nerve fibres at the chiasm. Limited studies have looked at nerve fibre arrangement in the chiasm. In summary, the chiasm is more 'H-shaped' than 'X-shaped': nerve fibre crossings occur paracentrally with nerves in the centre of the chiasm travelling coronally and in parallel. There is interaction between crossed and uncrossed fibres which are widely distributed. The review supports the non-existence of Wilbrand's knee. Considerable further work is required to provide more precise anatomical information, but this review suggests that the assumed preservation of retinotopy in the human optic nerve and chiasm is probably not correct.
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Affiliation(s)
- Pratap R Pawar
- School of Engineering and Technology, University of New South Wales, Canberra, NSW, Australia
| | - Joshua Booth
- School of Medicine and Psychology, Australian National University, Canberra, NSW, Australia
| | - Andrew Neely
- School of Engineering and Technology, University of New South Wales, Canberra, NSW, Australia
| | - Gawn McIlwaine
- Department of Ophthalmology, Mater Hospital, Belfast, Northern, Ireland
| | - Christian J Lueck
- School of Medicine and Psychology, Australian National University, Canberra, NSW, Australia.
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2
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Brownsett SLE, Carey LM, Copland D, Walsh A, Sihvonen AJ. Structural brain networks correlating with poststroke cognition. Hum Brain Mapp 2024; 45:e26665. [PMID: 38520376 PMCID: PMC10960554 DOI: 10.1002/hbm.26665] [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: 12/20/2023] [Revised: 03/03/2024] [Accepted: 03/08/2024] [Indexed: 03/25/2024] Open
Abstract
Cognitive deficits are a common and debilitating consequence of stroke, yet our understanding of the structural neurobiological biomarkers predicting recovery of cognition after stroke remains limited. In this longitudinal observational study, we set out to investigate the effect of both focal lesions and structural connectivity on poststroke cognition. Sixty-two patients with stroke underwent advanced brain imaging and cognitive assessment, utilizing the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), at 3-month and 12-month poststroke. We first evaluated the relationship between lesions and cognition at 3 months using voxel-based lesion-symptom mapping. Next, a novel correlational tractography approach, using multi-shell diffusion-weighted magnetic resonance imaging (MRI) data collected at both time points, was used to evaluate the relationship between the white matter connectome and cognition cross-sectionally at 3 months, and longitudinally (12 minus 3 months). Lesion-symptom mapping did not yield significant findings. In turn, correlational tractography analyses revealed positive associations between both MoCA and MMSE scores and bilateral cingulum and the corpus callosum, both cross-sectionally at the 3-month stage, and longitudinally. These results demonstrate that rather than focal neural structures, a consistent structural connectome underpins the performance of two frequently used cognitive screening tools, the MoCA and the MMSE, in people after stroke. This finding should encourage clinicians and researchers to not only suspect cognitive decline when lesions affect these tracts, but also to refine their investigation of novel approaches to differentially diagnosing pathology associated with cognitive decline, regardless of the aetiology.
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Affiliation(s)
- Sonia L. E. Brownsett
- Centre of Research Excellence in Aphasia Recovery and RehabilitationLa Trobe UniversityMelbourneVictoriaAustralia
- Queensland Aphasia Research CentreSurgical, Treatment and Rehabilitation Service, University of QueenslandBrisbaneQueenslandAustralia
- School of Health and Rehabilitation SciencesUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Leeanne M. Carey
- Occupational Therapy, School of Allied Health Human Services and SportLa Trobe UniversityMelbourneVictoriaAustralia
- Neurorehabilitation and Recovery GroupThe FloreyMelbourneVictoriaAustralia
| | - David Copland
- Centre of Research Excellence in Aphasia Recovery and RehabilitationLa Trobe UniversityMelbourneVictoriaAustralia
- Queensland Aphasia Research CentreSurgical, Treatment and Rehabilitation Service, University of QueenslandBrisbaneQueenslandAustralia
- School of Health and Rehabilitation SciencesUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Alistair Walsh
- Occupational Therapy, School of Allied Health Human Services and SportLa Trobe UniversityMelbourneVictoriaAustralia
- Neurorehabilitation and Recovery GroupThe FloreyMelbourneVictoriaAustralia
| | - Aleksi J. Sihvonen
- Centre of Research Excellence in Aphasia Recovery and RehabilitationLa Trobe UniversityMelbourneVictoriaAustralia
- Queensland Aphasia Research CentreSurgical, Treatment and Rehabilitation Service, University of QueenslandBrisbaneQueenslandAustralia
- School of Health and Rehabilitation SciencesUniversity of QueenslandBrisbaneQueenslandAustralia
- Centre of Excellence in Music, Mind, Body and Brain, Cognitive Brain Research Unit (CBRU)University of HelsinkiHelsinkiFinland
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Phillips JS, Adluru N, Chung MK, Radhakrishnan H, Olm CA, Cook PA, Gee JC, Cousins KAQ, Arezoumandan S, Wolk DA, McMillan CT, Grossman M, Irwin DJ. Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease. Front Neurosci 2024; 18:1353306. [PMID: 38567286 PMCID: PMC10986184 DOI: 10.3389/fnins.2024.1353306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.
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Affiliation(s)
- Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Moo K. Chung
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Hamsanandini Radhakrishnan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip A. Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - James C. Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A. Q. Cousins
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanaz Arezoumandan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Memory Center, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Modo M, Sparling K, Novotny J, Perry N, Foley LM, Hitchens TK. Mapping mesoscale connectivity within the human hippocampus. Neuroimage 2023; 282:120406. [PMID: 37827206 PMCID: PMC10623761 DOI: 10.1016/j.neuroimage.2023.120406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/28/2023] [Accepted: 10/10/2023] [Indexed: 10/14/2023] Open
Abstract
The connectivity of the hippocampus is essential to its functions. To gain a whole system view of intrahippocampal connectivity, ex vivo mesoscale (100 μm isotropic resolution) multi-shell diffusion MRI (11.7T) and tractography were performed on entire post-mortem human right hippocampi. Volumetric measurements indicated that the head region was largest followed by the body and tail regions. A unique anatomical organization in the head region reflected a complex organization of the granule cell layer (GCL) of the dentate gyrus. Tractography revealed the volumetric distribution of the perforant path, including both the tri-synaptic and temporoammonic pathways, as well as other well-established canonical connections, such as Schaffer collaterals. Visualization of the perforant path provided a means to verify the borders between the pro-subiculum and CA1, as well as between CA1/CA2. A specific angularity of different layers of fibers in the alveus was evident across the whole sample and allowed a separation of afferent and efferent connections based on their origin (i.e. entorhinal cortex) or destination (i.e. fimbria) using a cluster analysis of streamlines. Non-canonical translamellar connections running along the anterior-posterior axis were also discerned in the hilus. In line with "dentations" of the GCL, mossy fibers were bunching together in the sagittal plane revealing a unique lamellar organization and connections between these. In the head region, mossy fibers projected to the origin of the fimbria, which was distinct from the body and tail region. Mesoscale tractography provides an unprecedented systems view of intrahippocampal connections that underpin cognitive and emotional processing.
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Affiliation(s)
- Michel Modo
- Department of Radiology; Department of BioEngineering; McGowan Institute for Regenerative Medicine; Centre for Neuroscience University of Pittsburgh (CNUP); Centre for the Neural Basis of Cognition (CNBC).
| | | | | | | | | | - T Kevin Hitchens
- Small Animal Imaging Center; Departmnet of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15203, USA
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Park KM, Kim KT, Lee DA, Cho YW. Correlation of Diffusion Tensor Tractography with Restless Legs Syndrome Severity. Brain Sci 2023; 13:1560. [PMID: 38002520 PMCID: PMC10670044 DOI: 10.3390/brainsci13111560] [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: 10/17/2023] [Revised: 10/31/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
This prospective study investigated white matter tracts associated with restless legs syndrome (RLS) severity in 69 patients with primary RLS using correlational tractography based on diffusion tensor imaging. Fractional anisotropy (FA) and quantitative anisotropy (QA) were analyzed separately to understand white matter abnormalities in RLS patients. Connectometry analysis revealed positive correlations between RLS severity and FA values in various white matter tracts, including the left and right cerebellum, corpus callosum forceps minor and major, corpus callosum body, right cingulum, and frontoparietal tract. In addition, connectometry analysis revealed that the FA of the middle cerebellar peduncle, left inferior longitudinal fasciculus, left corticospinal tract, corpus callosum forceps minor, right cerebellum, left frontal aslant tract, left dentatorubrothalamic tract, right inferior longitudinal fasciculus, left corticostriatal tract superior, and left cingulum parahippocampoparietal tract was negatively correlated with RLS severity in patients with RLS. However, there were no significant correlations between QA values and RLS severity. It is implied that RLS symptoms may be potentially reversible with appropriate treatment. This study highlights the importance of considering white matter alterations in understanding the pathophysiology of RLS and in developing effective treatment strategies.
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Affiliation(s)
- Kang Min Park
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan 48108, Republic of Korea; (K.M.P.); (D.A.L.)
| | - Keun Tae Kim
- Department of Neurology, Keimyung University School of Medicine, Daegu 42601, Republic of Korea;
| | - Dong Ah Lee
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan 48108, Republic of Korea; (K.M.P.); (D.A.L.)
| | - Yong Won Cho
- Department of Neurology, Keimyung University School of Medicine, Daegu 42601, Republic of Korea;
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6
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Bayoumi A, Hasan KM, Patino J, Keser Z, Thomas JA, Gabr RE, Pedroza C, Kamali A. Identifying the white matter pathways involved in multiple sclerosis-related tremor using diffusion tensor imaging. Mult Scler J Exp Transl Clin 2023; 9:20552173231208271. [PMID: 38021452 PMCID: PMC10631316 DOI: 10.1177/20552173231208271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/02/2023] [Indexed: 12/01/2023] Open
Abstract
Background Tremor affects up to 45% of patients with Multiple Sclerosis (PwMS). Current understanding is based on insights from other neurological disorders, thus, not fully addressing the distinctive aspects of MS pathology. Objective To characterize the brain white matter (WM) correlates of MS-related tremor using diffusion tensor imaging (DTI). Methods In a prospective case-control study, PwMS with tremor were assessed for tremor severity and underwent MRI scans including DTI. PwMS without tremor served as matched controls. After tract selection and segmentation, the resulting diffusivity measures were used to calculate group differences and correlations with tremor severity. Results This study included 72 PwMS. The tremor group (n = 36) exhibited significant changes in several pathways, notably in the right inferior longitudinal fasciculus (Cohen's d = 1.53, q < 0.001) and left corticospinal tract (d = 1.32, q < 0.001), compared to controls (n = 36). Furthermore, specific tracts showed a significant correlation with tremor severity, notably in the left medial lemniscus (Spearman's coefficient [rsp] = -0.56, p < 0.001), and forceps minor of corpus callosum (rsp = -0.45, p < 0.01). Conclusion MS-related tremor is associated with widespread diffusivity changes in WM pathways and its severity correlates with commissural and sensory projection pathways, which suggests a role for proprioception or involvement of the dentato-rubro-olivary circuit.
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Affiliation(s)
- Ahmed Bayoumi
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Khader M. Hasan
- Department of Radiology, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Jorge Patino
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Zafer Keser
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Joseph A. Thomas
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Refaat E. Gabr
- Department of Radiology, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Claudia Pedroza
- Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Arash Kamali
- Department of Radiology, McGovern Medical School at UTHealth, Houston, TX, USA
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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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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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9
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Ortug A, Yuzbasioglu N, Akalan N, Levman J, Takahashi E. Preoperative and postoperative high angular resolution diffusion imaging tractography of cerebellar pathways in posterior fossa tumors. Clin Anat 2022; 35:1085-1099. [PMID: 35560729 PMCID: PMC9547814 DOI: 10.1002/ca.23914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 11/12/2022]
Abstract
This study aimed to utilize high angular resolution diffusion magnetic resonance imaging (HARDI) tractography in the mapping of the pathways of the cerebellum associated with posterior fossa tumors (infratentorial neoplasms) and to determine whether it is useful for preoperative and postoperative evaluation. Retrospective data from 30 patients (age 2-16 yr) with posterior fossa tumor (17 low grade, 13 high grade) and 30 age-sex-matched healthy controls were used. Structural and diffusion-weighted images were collected at a 3-tesla scanner. Tractography was performed using Diffusion Toolkit software, Q-ball model, FACT algorithm, and angle threshold of 45 degrees. Manually assessed regions of interest were placed to identify reconstructed fiber pathways passing through the superior, medial, and inferior cerebellar peduncles for the preoperative, postoperative, and healthy control groups. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), and track volume measures were obtained and analyzed. Statistically significant differences were found between the preop/postop, preop/control, and postop/control comparisons for the volume of the tracts in both groups. Displacement and disruption of the pathways seemed to differ in relation to the severity of the tumor. The loss of pathways after the operation was associated with selective resection during surgery due to tumor infiltration. There were no FA differences but significantly higher ADC in low-grade tumors, and no difference in both FA and ADC in high-grade tumors. The effects of posterior fossa tumors on cerebellar peduncles and reconstructed pathways were successfully evaluated by HARDI tractography. The technique appears to be useful not only for preoperative but also for postoperative evaluation.
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Affiliation(s)
- A. Ortug
- Department of Anatomy, School of Medicine, Istanbul Medipol University, Istanbul, 34815, Turkey
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - N. Yuzbasioglu
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - N. Akalan
- Department of Neurosurgery, School of Medicine, Istanbul Medipol University, Istanbul, 34815, Turkey
| | - J. Levman
- Department of Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, B2G 2W5, Canada
| | - E. Takahashi
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
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Peterson BS, Liu J, Dantec L, Newman C, Sawardekar S, Goh S, Bansal R. Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder. J Child Psychol Psychiatry 2022; 63:855-870. [PMID: 34762311 PMCID: PMC9091058 DOI: 10.1111/jcpp.13531] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/08/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. METHODS We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. RESULTS Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. CONCLUSIONS Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.
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Affiliation(s)
- Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
| | - Jiaqi Liu
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | - Louis Dantec
- École Polytechnique Universitaire de Marseille, France
| | | | - Siddhant Sawardekar
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | | | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
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11
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White Matter Microstructural Alterations in Newly Diagnosed Parkinson’s Disease: A Whole-Brain Analysis Using dMRI. Brain Sci 2022; 12:brainsci12020227. [PMID: 35203990 PMCID: PMC8870150 DOI: 10.3390/brainsci12020227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/31/2022] [Accepted: 02/03/2022] [Indexed: 11/17/2022] Open
Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD’s pathophysiology.
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12
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Luo SP, Chen FF, Zhang HW, Lin F, Huang GD, Lei Y. Trigeminal Nerve White Matter Fiber Abnormalities in Primary Trigeminal Neuralgia: A Diffusion Spectrum Imaging Study. Front Neurol 2022; 12:798969. [PMID: 35126296 PMCID: PMC8810829 DOI: 10.3389/fneur.2021.798969] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 12/06/2021] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE Diffusion spectrum imaging (DSI) was used to quantitatively study the changes in the trigeminal cistern segment in patients with trigeminal neuralgia (TN) and to further explore the value of acquiring DSI data from patients with TN. METHODS To achieve high-resolution fiber tracking, 60 patients with TN and 35 healthy controls (HCs) were scanned with conventional magnetic resonance imaging (MRI) and DSI. The patients and the members of the control group were compared within and between groups. The correlations between quantitative parameters of DSI and the visual analog scale (VAS), and symptom duration and responsible vessel types were analyzed. RESULTS Compared with unaffected side of patients in the TN group, the affected side showed significantly decreased quantitative anisotropy (QA) (p < 0.001), fractional anisotropy (FA) (p = 0.001), and general FA (GFA) (p < 0.001). The unaffected side exhibited significantly decreased QA (p + 0.001), FA (p = 0.001), and GFA (p < 0.001) and significantly increased axial diffusivity (AD) (p = 0.036) compared with the affected side of patients in the TN group and the average values of HCs. There were significantly decreased QA (p = 0.046) and FA (p = 0.008) between the unaffected side of patients and the average values of HCs. GFA can evidently distinguish arteries, veins, and features of unaffected side in TN patients. CONCLUSION Using high-resolution fiber tracking technology, DSI can provide quantitative information that can be used to detect the integrity of trigeminal white matter in patients with TN and can improve the understanding of the disease mechanism.
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Affiliation(s)
- Si-ping Luo
- College of Medicine, Shantou University, Shantou, China
- Department of Radiology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
| | - Fan-fan Chen
- Department of Neurosurgery, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
| | - Han-wen Zhang
- Department of Radiology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
| | - Fan Lin
- Department of Radiology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
| | - Guo-dong Huang
- Department of Neurosurgery, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
| | - Yi Lei
- Department of Radiology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, China
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13
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Bigham B, Zamanpour SA, Zare H. Features of the superficial white matter as biomarkers for the detection of Alzheimer's disease and mild cognitive impairment: A diffusion tensor imaging study. Heliyon 2022; 8:e08725. [PMID: 35071808 PMCID: PMC8761704 DOI: 10.1016/j.heliyon.2022.e08725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 10/02/2021] [Accepted: 01/05/2022] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND With the development of medical imaging and processing tools, accurate diagnosis of diseases has been made possible by intelligent systems. Owing to the remarkable ability of support vector machines (SVMs) for diseases diagnosis, extensive research has been conducted using the SVM algorithm for the classification of Alzheimer's disease (AD) and mild cognitive impairment (MCI). OBJECTIVES In this study, we applied an automated method to classify patients with AD and MCI and healthy control (HC) subjects based on the diffusion tensor imaging (DTI) features in the superficial white matter (SWM). PARTICIPANTS For this purpose, DTI data were downloaded from the Alzheimer's Disease Neuroimaging Initiative (ADNI). This method employed DTI data from 72 subjects: 24 subjects as HC, 24 subjects with MCI, and 24 subjects with AD. MEASURE ments: DTI processing was performed using DSI Studio software and all machine learning analyses were performed using MATLAB software. RESULTS The linear kernel of SVM was the best classifier, with an accuracy of 95.8% between the AD and HC groups, followed by the quadratic kernel of SVM with an accuracy of 83.3% between the MCI and HC groups and the Gaussian kernel of SVM with an accuracy of 83.3% between the AD and MCI groups. CONCLUSIONS Given the importance of diagnosing AD and MCI as well as the role of superficial white matter in the diagnosis of neurodegenerative diseases, in this study, the features of different DTI methods of the SWM are discussed, which could be a useful tool to assist in the diagnosis of AD and MCI.
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Affiliation(s)
- Bahare Bigham
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyed Amir Zamanpour
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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14
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Chen VCH, Kao CJ, Tsai YH, Cheok MT, McIntyre RS, Weng JC. Assessment of Disrupted Brain Structural Connectome in Depressive Patients With Suicidal Ideation Using Generalized Q-Sampling MRI. Front Hum Neurosci 2021; 15:711731. [PMID: 34512298 PMCID: PMC8430248 DOI: 10.3389/fnhum.2021.711731] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/30/2021] [Indexed: 11/13/2022] Open
Abstract
Suicide is one of the leading causes of mortality worldwide. Various factors could lead to suicidal ideation (SI), while depression is the predominant cause among all mental disorders. Studies have shown that alterations in brain structures and networks may be highly associated with suicidality. This study investigated both neurological structural variations and network alterations in depressed patients with suicidal ideation by using generalized q-sampling imaging (GQI) and Graph Theoretical Analysis (GTA). This study recruited 155 participants and divided them into three groups: 44 depressed patients with suicidal ideation (SI+; 20 males and 24 females with mean age = 42, SD = 12), 56 depressed patients without suicidal ideation (Depressed; 24 males and 32 females with mean age = 45, SD = 11) and 55 healthy controls (HC; nine males and 46 females with mean age = 39, SD = 11). Both the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values were evaluated in a voxel-based statistical analysis by GQI. We analyzed different topological parameters in the graph theoretical analysis and the subnetwork interconnections in the Network-based Statistical (NBS) analysis. In the voxel-based statistical analysis, both the GFA and NQA values in the SI+ group were generally lower than those in the Depressed and HC groups in the corpus callosum and cingulate gyrus. Furthermore, we found that the SI+ group demonstrated higher global integration and lower local segregation among the three groups of participants. In the network-based statistical analysis, we discovered that the SI+ group had stronger connections of subnetworks in the frontal lobe than the HC group. We found significant structural differences in depressed patients with suicidal ideation compared to depressed patients without suicidal ideation and healthy controls and we also found several network alterations among these groups of participants, which indicated that white matter integrity and network alterations are associated with patients with depression as well as suicidal ideation.
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Affiliation(s)
- Vincent Chin-Hung Chen
- School of Medicine, Chang Gung University, Taoyuan, Taiwan.,Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Chun-Ju Kao
- Department of Medical Imaging and Radiological Sciences, Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan
| | - Yuan-Hsiung Tsai
- School of Medicine, Chang Gung University, Taoyuan, Taiwan.,Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Man Teng Cheok
- Department of Medical Imaging and Radiological Sciences, Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Roger S McIntyre
- Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Jun-Cheng Weng
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan.,Department of Medical Imaging and Radiological Sciences, Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan.,Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
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15
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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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16
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Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks. Diagnostics (Basel) 2021; 11:diagnostics11060970. [PMID: 34072192 PMCID: PMC8227047 DOI: 10.3390/diagnostics11060970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 05/07/2021] [Accepted: 05/26/2021] [Indexed: 12/15/2022] Open
Abstract
The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.
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17
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Jiang R, Hu X, Deng K, Jiang S, Chen W, Zhang Z. Neurite orientation dispersion and density imaging in evaluation of high-grade glioma-induced corticospinal tract injury. Eur J Radiol 2021; 140:109750. [PMID: 33991969 DOI: 10.1016/j.ejrad.2021.109750] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 04/03/2021] [Accepted: 04/29/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE To evaluate the application of neurite orientation dispersion and density imaging (NODDI) to brain glioma-induced corticospinal tract (CST) injury. MATERIAL AND METHODS Twenty-four patients with high-grade glioma (HGG) in or adjacent to the CST pathway and 12 matched healthy subjects underwent structural and diffusion MRI. The CSTs were reconstructed on the both sides. The CST features including morphological features (track number, average track length and track volume) and the diffusion parameter values including fractional anisotraphy (FA), mean diffusivity (MD), intracellular volume fraction (ICVF), isotropic or free water volume fraction (ISOVF) and orientation dispersion index (ODI) along the CST were calculated. The CST features were compared between the affected and healthy side for HGG patients and between the left and right side for healthy subjects. The relative CST features were compared across the healthy subjects, patients with motor weakness and patients with normal muscle strength. Receiver operating characteristic (ROC) curve was applied to evaluate the performance of each relative CST characteristic for HGG-induced CST changes. RESULTS Compared with the CST features on the healthy side, the track number, track volume and FA along the CST changed significantly on the affected side for HGG patients (p < 0.05 for all), whereas MD and ICVF changed significantly on the affected side only for HGG patients with motor weakness (p = 0.012 for both). In patients with motor weakness, the relative MD was significantly higher (p < 0.001), whereas the relative FA and ICVF was significantly lower (p = 0.002 and <0.001) than those in patients with normal muscle strength. The relative ICVF had a similar area under curve (AUC) to that of MD (AUC=0.953 and 0.969). Compared with the relative CST features in the healthy subjects, only the relative ICVF was significantly lower in HGG patients with normal muscle strength (p = 0.012). CONCLUSIONS NODDI seems to be useful in reflecting the HGG infiltration to CST, and can evaluate the CST destruction with a performance similar to DTI by providing additional information about neurite density for HGG-induced CST injury.
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Affiliation(s)
- Rifeng Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
| | - Xiaomei Hu
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Kaiji Deng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Shaofan Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Weitao Chen
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Zhongshuai Zhang
- MR Scientific Marketing, Siemens Healthcare, Shanghai, 201318, China
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18
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Chen VCH, Kao CJ, Tsai YH, McIntyre RS, Weng JC. Mapping Brain Microstructure and Network Alterations in Depressive Patients with Suicide Attempts Using Generalized Q-Sampling MRI. J Pers Med 2021; 11:jpm11030174. [PMID: 33802354 PMCID: PMC7998726 DOI: 10.3390/jpm11030174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 02/25/2021] [Accepted: 02/25/2021] [Indexed: 12/28/2022] Open
Abstract
Depressive disorder is one of the leading causes of disability worldwide, with a high prevalence and chronic course. Depressive disorder carries an increased risk of suicide. Alterations in brain structure and networks may play an important role in suicidality among depressed patients. Diffusion magnetic resonance imaging (MRI) is a noninvasive method to map white-matter fiber orientations and provide quantitative parameters. This study investigated the neurological structural differences and network alterations in depressed patients with suicide attempts by using generalized q-sampling imaging (GQI). Our study recruited 155 participants and assigned them into three groups: 44 depressed patients with a history of suicide attempts (SA), 56 depressed patients without a history of suicide attempts (D) and 55 healthy controls (HC). We used the GQI to analyze the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values in voxel-based statistical analysis, topological parameters in graph theoretical analysis and subnetwork connectivity in network-based statistical analysis. GFA indicates the measurement of neural anisotropy and represents white-matter integrity; NQA indicates the amount of anisotropic spins that diffuse along fiber orientations and represents white-matter compactness. In the voxel-based statistical analysis, we found lower GFA and NQA values in the SA group than in the D and HC groups and lower GFA and NQA values in the D group than in the HC group. In the graph theoretical analysis, the SA group demonstrated higher local segregation and lower global integration among the three groups. In the network-based statistical analysis, the SA group showed stronger subnetwork connections in the frontal and parietal lobes, and the D group showed stronger subnetwork connections in the parietal lobe than the HC group. Alternations were found in the structural differences and network measurements in healthy controls and depressed patients with and without a history of suicide attempt.
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Affiliation(s)
- Vincent Chin-Hung Chen
- School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan; (V.C.-H.C.); (Y.-H.T.)
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi 61363, Taiwan
| | - Chun-Ju Kao
- Department of Medical Imaging and Radiological Sciences, Bachelor Program in Artificial Intelligence, Chang Gung University, No. 259, Wenhua 1st Rd., Taoyuan 33302, Taiwan;
| | - Yuan-Hsiung Tsai
- School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan; (V.C.-H.C.); (Y.-H.T.)
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi 61363, Taiwan
| | - Roger S. McIntyre
- Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, University of Toronto, Toronto, ON M5S, Canada;
- Institute of Medical Science, University of Toronto, Toronto, ON M5S, Canada
- Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, ON M5S, Canada
| | - Jun-Cheng Weng
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi 61363, Taiwan
- Department of Medical Imaging and Radiological Sciences, Bachelor Program in Artificial Intelligence, Chang Gung University, No. 259, Wenhua 1st Rd., Taoyuan 33302, Taiwan;
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
- Correspondence: ; Tel.: +886-3-2118800 (ext. 5394)
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19
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Jiang R, Jiang S, Song S, Wei X, Deng K, Zhang Z, Xue Y. Laplacian-Regularized Mean Apparent Propagator-MRI in Evaluating Corticospinal Tract Injury in Patients with Brain Glioma. Korean J Radiol 2020; 22:759-769. [PMID: 33289364 PMCID: PMC8076836 DOI: 10.3348/kjr.2020.0949] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/25/2020] [Accepted: 08/09/2020] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. MATERIALS AND METHODS This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), return-to-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. RESULTS The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). CONCLUSION MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.
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Affiliation(s)
- Rifeng Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
| | - Shaofan Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Shiwei Song
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiaoqiang Wei
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Kaiji Deng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | | | - Yunjing Xue
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
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The superior frontal longitudinal tract: a connection between the dorsal premotor and the dorsolateral prefrontal cortices. Sci Rep 2020; 10:15855. [PMID: 32985573 PMCID: PMC7522085 DOI: 10.1038/s41598-020-73001-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 09/09/2020] [Indexed: 11/16/2022] Open
Abstract
A few studies have identified the structural connection between the premotor area and the lateral prefrontal cortex (DLPFC) as the frontal longitudinal system (FLS). This study investigated the existence of a direct segment (none U-fibre) of the superior part of the FLS (sFLS), which connects the dorsal premotor cortex (PMd) and DLPFC and analysed its asymmetry and termination point patterns. A dataset of diffusion-weighted images from 48 subjects was used for generalised q-sampling imaging tractography. Additionally, a white-fibre dissection was conducted in two right hemispheres. An analysis of spatial location, termination points, laterality, and correlation with the subjects’ gender or handedness was performed. The sFLS was found to have a deeper longitudinal bundle directly connecting the PMd and DLPFC. The bundle is referred to hereafter as the superior frontal longitudinal tract (SFLT). The SFLT was reconstructed in 100% of right and 88% of left hemispheres. It exhibited variable patterns in different subjects in their posterior terminations. In addition, it was found to possess a complicated spatial relationship with the adjacent bundles. The SFLT was revealed successfully in two cadaveric right hemispheres, where the posterior terminations were found to originate in the PMd independent of the superior longitudinal fasciculus.
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Jin Z, Li Z. Clinical Application of Diffusion Tensor Imaging in Diagnosis and Prognosis of Hemifacial Spasm. World Neurosurg 2020; 145:e14-e20. [PMID: 32791215 DOI: 10.1016/j.wneu.2020.08.049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/04/2020] [Accepted: 08/05/2020] [Indexed: 11/28/2022]
Abstract
OBJECTIVE The purpose of this study was to test the application of diffusion tensor imaging (DTI) in patients with hemifacial spasm (HFS), to make more accurate diagnoses before surgery and to judge the degree of recovery more accurately after surgical microvascular decompression. To our knowledge, this is the first study to test the validity of DTI for diagnosis and postsurgical evaluation of HFS. METHODS We included 40 patients with HFS who underwent DTI scanning before microvascular decompression. They were followed up with DTI 6 months and 1 year after surgery. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were obtained and compared. RESULTS In patients with HFS, the FA value of the affected side (mean FA, 0.46 ± 0.03) was significantly lower than that of the healthy side (mean FA, 0.43 ± 0.04; P < 0.05), and the ADC value of the affected side (mean FA, 1.60 ± 0.14) was significantly higher than that of the healthy side (mean ADC, 1.50 ± 0.12; P < 0.05). Compared with those before surgery, the FA values of both follow-up patients increased significantly, whereas their ADC values decreased significantly. CONCLUSIONS The use of DTI improves diagnosis and treatment of HFS.
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Affiliation(s)
- Zhuoru Jin
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Zhipeng Li
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China.
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