1
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Andrew RD, Hartings JA, Ayata C, Brennan KC, Dawson-Scully KD, Farkas E, Herreras O, Kirov SA, Müller M, Ollen-Bittle N, Reiffurth C, Revah O, Robertson RM, Shuttleworth CW, Ullah G, Dreier JP. The Critical Role of Spreading Depolarizations in Early Brain Injury: Consensus and Contention. Neurocrit Care 2022; 37:83-101. [PMID: 35257321 PMCID: PMC9259543 DOI: 10.1007/s12028-021-01431-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 12/29/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND When a patient arrives in the emergency department following a stroke, a traumatic brain injury, or sudden cardiac arrest, there is no therapeutic drug available to help protect their jeopardized neurons. One crucial reason is that we have not identified the molecular mechanisms leading to electrical failure, neuronal swelling, and blood vessel constriction in newly injured gray matter. All three result from a process termed spreading depolarization (SD). Because we only partially understand SD, we lack molecular targets and biomarkers to help neurons survive after losing their blood flow and then undergoing recurrent SD. METHODS In this review, we introduce SD as a single or recurring event, generated in gray matter following lost blood flow, which compromises the Na+/K+ pump. Electrical recovery from each SD event requires so much energy that neurons often die over minutes and hours following initial injury, independent of extracellular glutamate. RESULTS We discuss how SD has been investigated with various pitfalls in numerous experimental preparations, how overtaxing the Na+/K+ ATPase elicits SD. Elevated K+ or glutamate are unlikely natural activators of SD. We then turn to the properties of SD itself, focusing on its initiation and propagation as well as on computer modeling. CONCLUSIONS Finally, we summarize points of consensus and contention among the authors as well as where SD research may be heading. In an accompanying review, we critique the role of the glutamate excitotoxicity theory, how it has shaped SD research, and its questionable importance to the study of early brain injury as compared with SD theory.
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Affiliation(s)
- R. David Andrew
- grid.410356.50000 0004 1936 8331Queen’s University, Kingston, ON Canada
| | - Jed A. Hartings
- grid.24827.3b0000 0001 2179 9593University of Cincinnati, Cincinnati, OH USA
| | - Cenk Ayata
- grid.38142.3c000000041936754XHarvard Medical School, Harvard University, Boston, MA USA
| | - K. C. Brennan
- grid.223827.e0000 0001 2193 0096The University of Utah, Salt Lake City, UT USA
| | | | - Eszter Farkas
- grid.9008.10000 0001 1016 96251HCEMM-USZ Cerebral Blood Flow and Metabolism Research Group, and the Department of Cell Biology and Molecular Medicine, Faculty of Science and Informatics & Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Oscar Herreras
- grid.419043.b0000 0001 2177 5516Instituto de Neurobiologia Ramon Y Cajal (Consejo Superior de Investigaciones Científicas), Madrid, Spain
| | - Sergei. A. Kirov
- grid.410427.40000 0001 2284 9329Medical College of Georgia, Augusta, GA USA
| | - Michael Müller
- grid.411984.10000 0001 0482 5331University of Göttingen, University Medical Center Göttingen, Göttingen, Germany
| | - Nikita Ollen-Bittle
- grid.39381.300000 0004 1936 8884University of Western Ontario, London, ON Canada
| | - Clemens Reiffurth
- grid.7468.d0000 0001 2248 7639Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; and the Department of Experimental Neurology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health., Berlin, Germany
| | - Omer Revah
- grid.168010.e0000000419368956School of Medicine, Stanford University, Stanford, CA USA
| | | | | | - Ghanim Ullah
- grid.170693.a0000 0001 2353 285XUniversity of South Florida, Tampa, FL USA
| | - Jens P. Dreier
- grid.7468.d0000 0001 2248 7639Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; and the Department of Experimental Neurology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health., Berlin, Germany
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2
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Wu C, Ferreira F, Fox M, Harel N, Hattangadi-Gluth J, Horn A, Jbabdi S, Kahan J, Oswal A, Sheth SA, Tie Y, Vakharia V, Zrinzo L, Akram H. Clinical applications of magnetic resonance imaging based functional and structural connectivity. Neuroimage 2021; 244:118649. [PMID: 34648960 DOI: 10.1016/j.neuroimage.2021.118649] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 12/23/2022] Open
Abstract
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, 909 Walnut Street, Third Floor, Philadelphia, PA 19107, USA; Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut Street, First Floor, Philadelphia, PA 19107, USA.
| | - Francisca Ferreira
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Michael Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota, 2021 Sixth Street S.E., Minneapolis, MN 55455, USA.
| | - Jona Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, Center for Precision Radiation Medicine, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA.
| | - Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Charitéplatz 1, D-10117, Berlin, Germany.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Joshua Kahan
- Department of Neurology, Weill Cornell Medicine, 525 East 68th Street, New York, NY, 10065, USA.
| | - Ashwini Oswal
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Mansfield Rd, Oxford OX1 3TH, UK.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge, Ninth Floor, Houston, TX 77030, USA.
| | - Yanmei Tie
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA; Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Vejay Vakharia
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK.
| | - Ludvic Zrinzo
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Harith Akram
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
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3
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Fox ME, Turner JA, Crosson B, Morris RD, King TZ. Functional Connectivity Networks and Their Recruitment During Working Memory Tasks in Adult Survivors of Childhood Brain Tumors. Brain Connect 2021; 11:822-837. [PMID: 33858201 DOI: 10.1089/brain.2020.0800] [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] [Indexed: 10/21/2022] Open
Abstract
Background: Assessments of functional connectivity of default mode network (DMN) and positive task-related networks (TRNs) using independent component analysis (ICA) may help describe long-term effects of childhood brain tumors and adjuvant treatments. Methods: Aiming to identify potential neuronal markers that may aid in prognosis and inform interventions to optimize outcomes, this study used ICA to evaluate the presence of functional connectivity networks and their recruitment during a letter n-back task in 23 adult survivors of childhood posterior fossa tumors (9 low grade, 14 high grade) at least 5 years past diagnosis compared with 40 age- and sex-matched healthy peers. Results: DMN components generally demonstrated increasing disengagement as task difficulty increased, and relationships between effective DMN disengagement and improved performance were observed in healthy controls (HCs). Low-grade brain tumor survivors (LGS) demonstrated unique patterns in DMN recruitment that suggested increased involvement of the medial prefrontal cortex in LGS during tasks. TRN components generally demonstrated increasing engagement, which was related to improved task performance in HCs for one executive control network (ECN) component. High-grade brain tumor survivors (HGS) demonstrated distinct challenges recruiting an ECN component at more difficult task levels and showed a relationship between recruitment of another ECN component and task performance, indicating a potential compensatory mechanism for some HGS. Conclusions: Findings suggest the importance of cognitive intervention in both survivor groups and the necessity to track LGS despite their cognitive abilities often resembling those of their healthy peers. Impact statement Distinct functional connectivity patterns were identified between both adult survivor of childhood brain tumor groups and peers during attention and working memory tasks, reflecting different damage and recovery from treatment. Survivors of low-grade tumors demonstrated unique patterns of recruitment of default mode network components in the context of similar cognitive abilities, whereas survivors of high-grade tumors demonstrated poorer cognitive abilities and may be utilizing compensatory executive control network components in the face of challenging tasks. Long-term clinical follow-up and cognitive remediation is warranted for both groups, including low grade cerebellar tumor patients who have traditionally not been monitored as closely.
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Affiliation(s)
- Michelle E Fox
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA.,Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Bruce Crosson
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA.,Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA.,Departments of Neurology and of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA.,Atlanta VA Center of Excellence for Visual and Neurocognitive Rehabilitation, Decatur, Georgia, USA
| | - Robin D Morris
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA.,Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Tricia Z King
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA.,Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
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Yu T, Yu S, Zuo Z, Lin N, Wang J, Zhao Y, Lin S. Dexmedetomidine inhibits unstable motor network in patients with primary motor area gliomas. Aging (Albany NY) 2021; 13:15139-15150. [PMID: 34032606 PMCID: PMC8221338 DOI: 10.18632/aging.203077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/13/2021] [Indexed: 12/04/2022]
Abstract
Background: Sedative agents such as dexmedetomidine have been found to transiently exacerbate or unmask limb motor dysfunction in patients with eloquent area brain gliomas. The present study aims to investigate whether dexmedetomidine can inhibit motor plasticity in patients with glioma via fMRI. Methods: 21 patients with brain glioma were prospectively recruited between September 2017 and December 2018. Patients were classified into pre-M1 (primary motor cortex) group (n=9), post-M1 group (n=6), and non-eloquent group (control group) (n=6) according to the tumor position related to M1. The hand movement task-fMRI and resting state fMRI (rs-fMRI) were performed before and after sedation using dexmedetomidine. The lateralization index (LI) of activation voxels and magnitude and the functional connectivity (FC) of motor network were compared before and after sedation and among different groups. Results: Permanent postoperative motor deficit of the upper limb was found in 5 of 6 patients in the pre-M1 group, and none in other groups (P < .01). Task-fMRI showed the LI of activation volume and activation magnitude at M1 significantly increased only in the pre-M1 group after sedation (P < .05). Rs-fMRI showed 60.0% (27 of 45) FCs of motor network decreased in pre-M1 group after sedation (p[FDR] < .05); whereas there was no FC reduction in post-M1 and control groups (p[FDR] > .05). Conclusions: In patients with eloquent area gliomas, dexmedetomidine can inhibit the unstable compensative motor plasticity on both task- and rs-fMRI. fMRI may be a promising method for elucidating the effect of sedative agents on motor plasticity.
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Affiliation(s)
- Tao Yu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Songlin Yu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Nan Lin
- Department of Anesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Jing Wang
- Department of Neurosurgery, Peking University International Hospital, Peking University Health Science Center, Beijing 102206, China
| | - Yuanli Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.,Department of Neurosurgery, Peking University International Hospital, Peking University Health Science Center, Beijing 102206, China
| | - Song Lin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
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5
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Tordjman M, Madelin G, Gupta PK, Cordova C, Kurz SC, Orringer D, Golfinos J, Kondziolka D, Ge Y, Wang RL, Lazar M, Jain R. Functional connectivity of the default mode, dorsal attention and fronto-parietal executive control networks in glial tumor patients. J Neurooncol 2021; 152:347-355. [PMID: 33528739 DOI: 10.1007/s11060-021-03706-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 01/20/2021] [Indexed: 10/22/2022]
Abstract
PURPOSE Resting state functional magnetic resonance imaging (rsfMRI) is an emerging tool to explore the functional connectivity of different brain regions. We aimed to assess the disruption of functional connectivity of the Default Mode Network (DMN), Dorsal Attention Network(DAN) and Fronto-Parietal Network (FPN) in patients with glial tumors. METHODS rsfMRI data acquired on 3T-MR of treatment-naive glioma patients prospectively recruited (2015-2019) and matched controls from the 1000 functional-connectomes-project were analyzed using the CONN functional toolbox. Seed-Based Connectivity Analysis (SBCA) and Independent Component Analysis (ICA, with 10 to 100 components) were performed to study reliably the three networks of interest. RESULTS 35 patients with gliomas (17 WHO grade I-II, 18 grade III-IV) and 70 controls were included. Global increased DMN connectivity was consistently found with SBCA and ICA in patients compared to controls (Cluster1: Precuneus, height: p < 10-6; Cluster2: subcallosum; height: p < 10-5). However, an area of decreased connectivity was found in the posterior corpus callosum, particularly in high-grade gliomas (height: p < 10-5). The DAN demonstrated small areas of increased connectivity in frontal and occipital regions (height: p < 10-6). For the FPN, increased connectivity was noted in the precuneus, posterior cingulate gyrus, and frontal cortex. No difference in the connectivity of the networks of interest was demonstrated between low- and high-grade gliomas, as well as when stratified by their IDH1-R132H (isocitrate dehydrogenase) mutation status. CONCLUSION Altered functional connectivity is reliably found with SBCA and ICA in the DMN, DAN, and FPN in glioma patients, possibly explained by decreased connectivity between the cerebral hemispheres across the corpus callosum due to disruption of the connections.
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Affiliation(s)
- Mickael Tordjman
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA.
| | - Guillaume Madelin
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Pradeep Kumar Gupta
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Christine Cordova
- Perlmutter Cancer Center, Brain and Spine Tumor Center, NYU Langone Health, 240 E 38th Street, New York, NY, 10016, USA
| | - Sylvia C Kurz
- Perlmutter Cancer Center, Brain and Spine Tumor Center, NYU Langone Health, 240 E 38th Street, New York, NY, 10016, USA
| | - Daniel Orringer
- Department of Neurosurgery, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - John Golfinos
- Department of Neurosurgery, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Douglas Kondziolka
- Department of Neurosurgery, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Yulin Ge
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Ruoyu Luie Wang
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Mariana Lazar
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
| | - Rajan Jain
- Department of Radiology, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA.,Department of Neurosurgery, New York University Grossman School of Medicine, 650 First Avenue, New York, NY, 10022, USA
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6
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Duffau H. Functional Mapping before and after Low-Grade Glioma Surgery: A New Way to Decipher Various Spatiotemporal Patterns of Individual Neuroplastic Potential in Brain Tumor Patients. Cancers (Basel) 2020; 12:E2611. [PMID: 32933174 PMCID: PMC7565450 DOI: 10.3390/cancers12092611] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 09/07/2020] [Accepted: 09/11/2020] [Indexed: 12/21/2022] Open
Abstract
Intraoperative direct electrostimulation mapping (DEM) is currently the gold-standard for glioma surgery, since functional-based resection allows an optimization of the onco-functional balance (increased resection with preserved quality of life). Besides intrasurgical awake mapping of conation, cognition, and behavior, preoperative mapping by means of functional neuroimaging (FNI) and transcranial magnetic stimulation (TMS) has increasingly been utilized for surgical selection and planning. However, because these techniques suffer from several limitations, particularly for direct functional mapping of subcortical white matter pathways, DEM remains crucial to map neural connectivity. On the other hand, non-invasive FNI and TMS can be repeated before and after surgical resection(s), enabling longitudinal investigation of brain reorganization, especially in slow-growing tumors like low-grade gliomas. Indeed, these neoplasms generate neuroplastic phenomena in patients with usually no or only slight neurological deficits at diagnosis, despite gliomas involving the so-called "eloquent" structures. Here, data gained from perioperative FNI/TMS mapping methods are reviewed, in order to decipher mechanisms underpinning functional cerebral reshaping induced by the tumor and its possible relapse, (re)operation(s), and postoperative rehabilitation. Heterogeneous spatiotemporal patterns of rearrangement across patients and in a single patient over time have been evidenced, with structural changes as well as modifications of intra-hemispheric (in the ipsi-lesional and/or contra-lesional hemisphere) and inter-hemispheric functional connectivity. Such various fingerprints of neural reconfiguration were correlated to different levels of cognitive compensation. Serial multimodal studies exploring neuroplasticity might lead to new management strategies based upon multistage therapeutic approaches adapted to the individual profile of functional reallocation.
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Affiliation(s)
- Hugues Duffau
- Department of Neurosurgery, Montpellier University Medical Center, 34295 Montpellier, France; ; Tel.: +33-4-67-33-66-12; Fax: +33-4-67-33-69-12
- Institute of Functional Genomics, INSERM U-1191, University of Montpellier, 34298 Montpellier, France
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7
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Catalino MP, Yao S, Green D, Laws ER, Golby AJ, Tie Y. Mapping cognitive and emotional networks in neurosurgical patients using resting-state functional magnetic resonance imaging. Neurosurg Focus 2020; 48:E9. [PMID: 32006946 PMCID: PMC7712886 DOI: 10.3171/2019.11.focus19773] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 11/13/2019] [Indexed: 01/15/2023]
Abstract
Neurosurgery has been at the forefront of a paradigm shift from a localizationist perspective to a network-based approach to brain mapping. Over the last 2 decades, we have seen dramatic improvements in the way we can image the human brain and noninvasively estimate the location of critical functional networks. In certain patients with brain tumors and epilepsy, intraoperative electrical stimulation has revealed direct links between these networks and their function. The focus of these techniques has rightfully been identification and preservation of so-called "eloquent" brain functions (i.e., motor and language), but there is building momentum for more extensive mapping of cognitive and emotional networks. In addition, there is growing interest in mapping these functions in patients with a broad range of neurosurgical diseases. Resting-state functional MRI (rs-fMRI) is a noninvasive imaging modality that is able to measure spontaneous low-frequency blood oxygen level-dependent signal fluctuations at rest to infer neuronal activity. Rs-fMRI may be able to map cognitive and emotional networks for individual patients. In this review, the authors give an overview of the rs-fMRI technique and associated cognitive and emotional resting-state networks, discuss the potential applications of rs-fMRI, and propose future directions for the mapping of cognition and emotion in neurosurgical patients.
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Affiliation(s)
- Michael P Catalino
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School Boston, MA
- Department of Neurosurgery, University of North Carolina Hospitals, Chapel Hill, NC
| | - Shun Yao
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School Boston, MA
- Department of Neurosurgery and Pituitary Tumor Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Deborah Green
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Edward R Laws
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School Boston, MA
| | - Alexandra J Golby
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School Boston, MA
| | - Yanmei Tie
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School Boston, MA
- Corresponding Author: Yanmei Tie, Ph.D., Assistant Professor, Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Hale Building for Transformative Medicine, 8016G, 60 Fenwood Road, Boston, MA 02115, USA, , Tel: 617-732-8249
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8
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Fox ME, King TZ. Functional Connectivity in Adult Brain Tumor Patients: A Systematic Review. Brain Connect 2019; 8:381-397. [PMID: 30141339 DOI: 10.1089/brain.2018.0623] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Brain tumor (BT) patients often experience reduced cognitive abilities and disrupted adaptive functioning before and after treatment. An innovative approach to understanding the underlying brain networks associated with these outcomes has been to study the brain's functional connectivity (FC), the spatially distributed and temporally correlated activity throughout the brain, and how it can be affected by a tumor. The present review synthesized the extant BT FC literature that utilizes functional magnetic resonance imaging to study FC strength of commonly observed networks during rest and task. A systematic review of English articles using PubMed was conducted. Search terms included brain tumor OR glioma AND functional connectivity, independent component analysis, ICA, psychophysiological interaction, OR PPI. Studies in which participants were diagnosed with BTs as adults that evaluated specific networks of interest using independent component analysis or seed-based component analysis were included. Twenty-five studies met inclusion criteria. BT patients often presented with decreases in FC strength within well-established networks and increases in atypical FC patterns. Network differences were tumor adjacent and distal, and left hemisphere tumors generally had a greater impact on FC. FC alterations often correlated with behavioral or cognitive outcomes when assessed. Overall, BTs appear to lead to various alterations in FC across different functional networks, and the most common change is a decrease in expected FC strength. More longitudinal studies are needed to determine the time course of network alterations across treatment and recovery, the role of medical treatments in BT survivors' FC, and the potential of FC patterns as biomarkers of cognitive outcomes.
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Affiliation(s)
- Michelle E Fox
- 1 Department of Psychology, Georgia State University , Atlanta, Georgia
| | - Tricia Z King
- 1 Department of Psychology, Georgia State University , Atlanta, Georgia .,2 Neuroscience Institute, Georgia State University , Atlanta, Georgia
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9
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Mutiso VN, Musyimi CW, Krolinski P, Neher CM, Musau AM, Tele A, Ndetei DM. Relationship between Bullying, Substance Use, Psychiatric Disorders, and Social Problems in a Sample of Kenyan Secondary Schools. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2019; 20:544-554. [PMID: 30993591 DOI: 10.1007/s11121-019-01014-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We aimed to investigate how direct bullying and victimization relate with substance use, the presence of psychiatric disorders, poor school performance, disruptive behaviors, and social problems among secondary school students. A cross-sectional study was conducted in 20 randomly selected mixed-day secondary school students in forms one to three in Machakos County, equivalent to students in grades 1 to 11. From a random starting point, every sixth student in the class was invited to participate. The Drug Use Screening Inventory (revised) (DUSI-R) and the Olweus Bully/Victim Questionnaire (OBVQ) were administered in a classroom-setting by trained research assistants with experience in data collection. Four categories, i.e., bully only, bully-victim, victim only, and neither bully nor victims (neutrals) were developed and problem density scores computed. Descriptive statistics, bivariate, and multinomial logistic regression analysis summarized the findings. Of the 471 students, 13.6% had not experienced bullying problems. Bully-victim was the most prevalent form of bullying. No significant gender differences were reported across categories. Bully-victims reported significant higher problem density scores in eight out of the nine problem domains, and effect sizes of the differences in problem scores between neutrals and bully-victims were larger compared with other categories. Behavioral and family system problem scores retained a significant relationship with bully-victim category (p < 0.001). A high prevalence of bullying problems was documented in both genders. However, bully-victims had a higher risk of multiple negative individual and environmental and social problems. Assessment of bullying problems is an indirect route to identifying significant youth problems. Bullying interventions should be multifaceted to address psycho-socio-behavioral problems.
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Affiliation(s)
- Victoria N Mutiso
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon road, Mawensi Garden, Nairobi, Kenya
| | - Christine W Musyimi
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon road, Mawensi Garden, Nairobi, Kenya.,Vrije Universiteit, Amsterdam, Netherlands
| | | | | | - Abednego M Musau
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon road, Mawensi Garden, Nairobi, Kenya
| | - Albert Tele
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon road, Mawensi Garden, Nairobi, Kenya
| | - David M Ndetei
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon road, Mawensi Garden, Nairobi, Kenya. .,University of Nairobi, Nairobi, Kenya.
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10
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Rosazza C, Zacà D, Bruzzone MG. Pre-surgical Brain Mapping: To Rest or Not to Rest? Front Neurol 2018; 9:520. [PMID: 30018589 PMCID: PMC6038713 DOI: 10.3389/fneur.2018.00520] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 06/12/2018] [Indexed: 12/16/2022] Open
Affiliation(s)
- Cristina Rosazza
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico “Carlo Besta,”, Milan, Italy
| | - Domenico Zacà
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Maria G. Bruzzone
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico “Carlo Besta,”, Milan, Italy
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11
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Hsu AL, Hou P, Johnson JM, Wu CW, Noll KR, Prabhu SS, Ferguson SD, Kumar VA, Schomer DF, Hazle JD, Chen JH, Liu HL. IClinfMRI Software for Integrating Functional MRI Techniques in Presurgical Mapping and Clinical Studies. Front Neuroinform 2018; 12:11. [PMID: 29593520 PMCID: PMC5854683 DOI: 10.3389/fninf.2018.00011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 02/23/2018] [Indexed: 01/25/2023] Open
Abstract
Task-evoked and resting-state (rs) functional magnetic resonance imaging (fMRI) techniques have been applied to the clinical management of neurological diseases, exemplified by presurgical localization of eloquent cortex, to assist neurosurgeons in maximizing resection while preserving brain functions. In addition, recent studies have recommended incorporating cerebrovascular reactivity (CVR) imaging into clinical fMRI to evaluate the risk of lesion-induced neurovascular uncoupling (NVU). Although each of these imaging techniques possesses its own advantage for presurgical mapping, a specialized clinical software that integrates the three complementary techniques and promptly outputs the analyzed results to radiology and surgical navigation systems in a clinical format is still lacking. We developed the Integrated fMRI for Clinical Research (IClinfMRI) software to facilitate these needs. Beyond the independent processing of task-fMRI, rs-fMRI, and CVR mapping, IClinfMRI encompasses three unique functions: (1) supporting the interactive rs-fMRI mapping while visualizing task-fMRI results (or results from published meta-analysis) as a guidance map, (2) indicating/visualizing the NVU potential on analyzed fMRI maps, and (3) exporting these advanced mapping results in a Digital Imaging and Communications in Medicine (DICOM) format that are ready to export to a picture archiving and communication system (PACS) and a surgical navigation system. In summary, IClinfMRI has the merits of efficiently translating and integrating state-of-the-art imaging techniques for presurgical functional mapping and clinical fMRI studies.
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Affiliation(s)
- Ai-Ling Hsu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Changwei W Wu
- Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kyle R Noll
- Section of Neuropsychology, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vinodh A Kumar
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - John D Hazle
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jyh-Horng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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12
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Huang H, Ding Z, Mao D, Yuan J, Zhu F, Chen S, Xu Y, Lou L, Feng X, Qi L, Qiu W, Zhang H, Zang YF. PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI. Neuroinformatics 2018; 14:421-38. [PMID: 27221107 DOI: 10.1007/s12021-016-9304-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.
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Affiliation(s)
- Huiyuan Huang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, 58 Haishu Road, Hangzhou, 311121, People's Republic of China.,School of Education Science, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, People's Republic of China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, 310015, People's Republic of China
| | - Zhongxiang Ding
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Dewang Mao
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Jianhua Yuan
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Fangmei Zhu
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Shuda Chen
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Yan Xu
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Lin Lou
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Xiaoyan Feng
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Le Qi
- Department of Radiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, 310015, People's Republic of China
| | - Wusi Qiu
- Department of Neurosurgery, Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, 310015, People's Republic of China
| | - Han Zhang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, 58 Haishu Road, Hangzhou, 311121, People's Republic of China. .,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, 310015, People's Republic of China.
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, 58 Haishu Road, Hangzhou, 311121, People's Republic of China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, 310015, People's Republic of China
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13
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Cochereau J, Deverdun J, Herbet G, Charroud C, Boyer A, Moritz-Gasser S, Le Bars E, Molino F, Bonafé A, Menjot de Champfleur N, Duffau H. Comparison between resting state fMRI networks and responsive cortical stimulations in glioma patients. Hum Brain Mapp 2018; 37:3721-3732. [PMID: 27246771 DOI: 10.1002/hbm.23270] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Revised: 05/01/2016] [Accepted: 05/17/2016] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To validate the functional relevance of resting state networks (RSNs) by means of a comparison of resting state connectivity (RSC) between language regions elicited by direct cortical stimulation versus RSC between random regions; and to evaluate the accuracy of resting state fMRI in surgical planning by assessing the overlap between RSNs and intraoperative functional mapping results. METHODS Sensorimotor and language eloquent sites were identified by direct electrical cortical stimulation in 98 patients with a diffuse low-grade glioma. A seed to voxel analysis with inter-language stimulation point connectivity versus inter-random ROIs connectivity was performed (19 patients). An independant component analysis (ICA) was also applied to rsfMRI data. Language and sensorimotor components were selected over 20 independent components and compared to the corresponding stimulation points and resected cortex masks (31 and 90 patients, respectively). RESULTS Mean connectivity value between language seeds was significantly higher than the one between random seeds (0.68 ± 0.39 and 0.12 ± 0.21 respectively, P < 10-10 ). 96 ± 11% of sensorimotor stimulation points were located within 10 mm from sensorimotor ICA maps versus 92 ± 21% for language. 3.1 and 15% of resected cortex overlapped sensorimotor and language networks, respectively. Mean sensorimotor stimulation points and resected cortex z-scores were 2.0 ± 1.2 and -0.050 ± 0.60, respectively (P < 10-10 ). Mean language stimulation points and resected cortex z-scores were 1.6 ± 1.9 and 0.68 ± 0.91, respectively, P < 0.005. CONCLUSION The significantly higher RSC between language seeds than between random seeds validated the functional relevance of RSC. ICA partly succeeded to distinguish eloquent versus surgically removable areas and may be possibly used as a complementary tool to intraoperative mapping. Hum Brain Mapp 37:3721-3732, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jérôme Cochereau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Jérémy Deverdun
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Guillaume Herbet
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Céline Charroud
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Anthony Boyer
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,University of Montpellier 2, LIRMM laboratory, DEMAR Team, CNRS, INRIA, Montpellier, 34095, France
| | - Sylvie Moritz-Gasser
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Emmanuelle Le Bars
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - François Molino
- Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Alain Bonafé
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Nicolas Menjot de Champfleur
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Hugues Duffau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
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14
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Ghinda DC, Wu JS, Duncan NW, Northoff G. How much is enough-Can resting state fMRI provide a demarcation for neurosurgical resection in glioma? Neurosci Biobehav Rev 2017; 84:245-261. [PMID: 29198588 DOI: 10.1016/j.neubiorev.2017.11.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 11/20/2017] [Accepted: 11/27/2017] [Indexed: 01/09/2023]
Abstract
This study represents a systematic review of the insights provided by resting state functional MRI (rs-fMRI) use in the glioma population. Following PRISMA guidelines, 45 studies were included in the review and were classified in glioma-related neuronal changes (n=28) and eloquent area localization (n=17). Despite the heterogeneous nature of the studies, there is considerable evidence of diffuse functional reorganization occurring in the setting of gliomas with local and interhemispheric functional connectivity alterations involving different functional networks. The studies showed evidence of decreased long distance functional connectivity and increased global local efficiency occurring in the setting of gliomas. The tumour grade seems to correlate with distinct functional connectivity changes. Overall, there is a potential clinical utility of rs-fMRI for identifying the functional brain network disruptions occurring in the setting of gliomas. Further studies utilizing standardized analytical methods are required to elucidate the mechanism through which gliomas induce global changes in brain connectivity.
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Affiliation(s)
- Diana C Ghinda
- Ottawa Hospital Research Institute, University of Ottawa, Division of Neurosurgery, The Ottawa Hospital, 1053 Carling Avenue, Ottawa, ON, K1Y 4E9, Canada; Mind, Brain Imaging and Neuroethics, Canada Research Chair, EJLB-Michael Smith Chair for Neuroscience and Mental Health, Royal Ottawa Mental Health Centre, University of Ottawa Institute of Mental Health Research, 1145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada.
| | - Jin-Song Wu
- Glioma Surgery Division, Department of Neurological Surgery, Huashan Hospital, Fudan University, 518 Wuzhong E Rd, Shanghai, China.
| | - Niall W Duncan
- Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, 250 Wu-Xing Street, Taipei, 11031, Taiwan.
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics, Canada Research Chair, EJLB-Michael Smith Chair for Neuroscience and Mental Health, Royal Ottawa Mental Health Centre, University of Ottawa Institute of Mental Health Research, 1145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada; Mental Health Center/7th Hospital, Zhejiang University School of Medicine, 305 Tianmu Road, Hangzhou, Zhejiang Province, 310013, China.
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15
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Bakhshmand SM, Eagleson R, de Ribaupierre S. Multimodal connectivity based eloquence score computation and visualisation for computer-aided neurosurgical path planning. Healthc Technol Lett 2017; 4:152-156. [PMID: 29184656 PMCID: PMC5683204 DOI: 10.1049/htl.2017.0073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Accepted: 07/31/2017] [Indexed: 11/20/2022] Open
Abstract
Non-invasive assessment of cognitive importance has been a major challenge for planning of neurosurgical procedures. In the past decade, in vivo brain imaging modalities have been considered for estimating the ‘eloquence’ of brain areas. In order to estimate the impact of damage caused by an access path towards a target region inside of the skull, multi-modal metrics are introduced in this paper. Accordingly, this estimated damage is obtained by combining multi-modal metrics. In other words, this damage is an aggregate of intervened grey matter volume and axonal fibre numbers, weighted by their importance within the assigned anatomical and functional networks. To validate these metrics, an exhaustive search algorithm is implemented for characterising the solution space and visually representing connectional cost associated with a path initiated from underlying points. In this presentation, brain networks are built from resting state functional magnetic resonance imaging (fMRI) and deterministic tractography. their results demonstrate that the proposed approach is capable of refining traditional heuristics, such as choosing the minimal distance from the lesion, by supplementing connectional importance of the resected tissue. This provides complementary information to help the surgeon in avoiding important functional hubs and their anatomical linkages; which are derived from neuroimaging modalities and incorporated to the related anatomical landmarks.
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Affiliation(s)
- Saeed M Bakhshmand
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada
| | - Roy Eagleson
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada.,Department of Electrical and Computer Engineering, University of Western Ontario, London, ON, Canada
| | - Sandrine de Ribaupierre
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada.,Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
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16
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Dierker D, Roland JL, Kamran M, Rutlin J, Hacker CD, Marcus DS, Milchenko M, Miller-Thomas MM, Benzinger TL, Snyder AZ, Leuthardt EC, Shimony JS. Resting-state Functional Magnetic Resonance Imaging in Presurgical Functional Mapping: Sensorimotor Localization. Neuroimaging Clin N Am 2017; 27:621-633. [PMID: 28985933 PMCID: PMC5773116 DOI: 10.1016/j.nic.2017.06.011] [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] [Indexed: 10/18/2022]
Abstract
This article compares resting-state functional magnetic resonance (fMR) imaging with task fMR imaging for presurgical functional mapping of the sensorimotor (SM) region. Before tumor resection, 38 patients were scanned using both methods. The SM area was anatomically defined using 2 different software tools. Overlap of anatomic regions of interest with task activation maps and resting-state networks was measured in the SM region. A paired t-test showed higher overlap between resting-state maps and anatomic references compared with task activation when using a maximal overlap criterion. Resting state-derived maps are more comprehensive than those derived from task fMR imaging.
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Affiliation(s)
- Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Jarod L Roland
- Department of Neurological Surgery, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Mudassar Kamran
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Jerrel Rutlin
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Carl D Hacker
- Department of Neurological Surgery, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Daniel S Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Mikhail Milchenko
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Michelle M Miller-Thomas
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Tammie L Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA; Department of Neurological Surgery, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA; Department of Biomedical Imaging, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, Saint Louis, MO 63110, USA.
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17
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Abstract
Graph theoretic analyses applied to examine the brain at rest have played a critical role in clarifying the foundations of the brain's intrinsic and task-related activity. There are many opportunities for clinical scientists to describe and predict dysfunction using a network perspective. This primer describes the theoretic basis and practical application of graph theoretic analysis to resting state functional MR imaging data. Major practices, concepts, and findings are concisely reviewed. The theoretic and practical frontiers of resting state functional MR imaging are highlighted with observations about major avenues for conceptual advances and clinical translation.
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Affiliation(s)
- John D Medaglia
- Department of Psychology, University of Pennsylvania, 306 Goddard Building, Philadelphia, PA 19104, USA.
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18
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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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19
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Hart MG, Price SJ, Suckling J. Functional connectivity networks for preoperative brain mapping in neurosurgery. J Neurosurg 2016; 126:1941-1950. [PMID: 27564466 DOI: 10.3171/2016.6.jns1662] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Resection of focal brain lesions involves maximizing the resection while preserving brain function. Mapping brain function has entered a new era focusing on distributed connectivity networks at "rest," that is, in the absence of a specific task or stimulus, requiring minimal participant engagement. Central to this frame shift has been the development of methods for the rapid assessment of whole-brain connectivity with functional MRI (fMRI) involving blood oxygenation level-dependent imaging. The authors appraised the feasibility of fMRI-based mapping of a repertoire of functional connectivity networks in neurosurgical patients with focal lesions and the potential benefits of resting-state connectivity mapping for surgical planning. METHODS Resting-state fMRI sequences with a 3-T scanner and multiecho echo-planar imaging coupled to independent component analysis were acquired preoperatively from 5 study participants who had a right temporoparietooccipital glioblastoma. Seed-based functional connectivity analysis was performed with InstaCorr. Network identification focused on 7 major functional connectivity networks described in the literature and a putative language network centered on Broca's area. RESULTS All 8 functional connectivity networks were identified in each participant. Tumor-related topological changes to the default mode network were observed in all participants. In addition, each participant had at least 1 other abnormal network, and each network was abnormal in at least 1 participant. Individual patterns of network irregularities were identified with a qualitative approach and included local displacement due to mass effect, loss of a functional network component, and recruitment of new regions. CONCLUSIONS Resting-state fMRI can reliably and rapidly detect common functional connectivity networks in patients with glioblastoma and also has sufficient sensitivity for identifying patterns of network alterations. Mapping of functional connectivity networks offers the possibility to expand investigations to less commonly explored neuropsychological processes, such as executive control, attention, and salience. Changes in these networks may allow insights into mechanisms underlying the functional consequences of tumor growth, surgical intervention, and patient rehabilitation.
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Affiliation(s)
- Michael G Hart
- Brain Mapping Unit, Department of Psychiatry, and.,Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, United Kingdom
| | - Stephen J Price
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, United Kingdom
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Schneider FC, Pailler M, Faillenot I, Vassal F, Guyotat J, Barral FG, Boutet C. Presurgical Assessment of the Sensorimotor Cortex Using Resting-State fMRI. AJNR Am J Neuroradiol 2015; 37:101-7. [PMID: 26381564 DOI: 10.3174/ajnr.a4472] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 05/29/2015] [Indexed: 02/06/2023]
Abstract
BACKGROUND AND PURPOSE The functional characterization of the motor cortex is an important issue in the presurgical evaluation of brain lesions. fMRI noninvasively identifies motor areas while patients are asked to move different body parts. This task-based approach has some drawbacks in clinical settings: long scanning times and exclusion of patients with severe functional or neurologic disabilities and children. Resting-state fMRI can avoid these difficulties because patients do not perform any goal-directed tasks. MATERIALS AND METHODS Nineteen patients with diverse brain pathologies were prospectively evaluated by using task-based and resting-state fMRI to localize sensorimotor function. Independent component analyses were performed to generate spatial independent components reflecting functional brain networks or noise. Three radiologists identified the motor components and 3 portions of the motor cortex corresponding to the hand, foot, and face representations. Selected motor independent components were compared with task-based fMRI activation maps resulting from movements of the corresponding body parts. RESULTS The motor cortex was successfully and consistently identified by using resting-state fMRI by the 3 radiologists for all patients. When they subdivided the motor cortex into 3 segments, the sensitivities of resting-state and task-based fMRI were comparable. Moreover, we report a good spatial correspondence with the task-based fMRI activity estimates. CONCLUSIONS Resting-state fMRI can reliably image sensorimotor function in a clinical preoperative routine. It is a promising opportunity for presurgical localization of sensorimotor function and has the potential to benefit a large number of patients affected by a wide range of pathologies.
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Affiliation(s)
- F C Schneider
- From the Departments of Radiology (F.C.S., M.P., F.-G.B., C.B.) Thrombosis Research Group EA 3065 (F.C.S., F.-G.B., C.B.)
| | - M Pailler
- From the Departments of Radiology (F.C.S., M.P., F.-G.B., C.B.)
| | - I Faillenot
- Neurology (I.F.) Central Integration of Pain Institut National de la Santé et de la Recherche Médicale U1028 (I.F.), Jean Monnet University, Saint-Etienne, France
| | - F Vassal
- Neurosurgery (F.V.), University Hospital of Saint-Etienne, Saint-Etienne, France Image-Guided Clinical Neurosciences and Connectomics EA 7282 (F.V.), Auvergne University, Clermont-Ferrand, France
| | - J Guyotat
- Department of Neurosurgery (J.G.), Hospices Civils de Lyon, Claude Bernard University, Lyon, France
| | - F-G Barral
- From the Departments of Radiology (F.C.S., M.P., F.-G.B., C.B.) Thrombosis Research Group EA 3065 (F.C.S., F.-G.B., C.B.)
| | - C Boutet
- From the Departments of Radiology (F.C.S., M.P., F.-G.B., C.B.) Thrombosis Research Group EA 3065 (F.C.S., F.-G.B., C.B.)
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Chamberland M, Bernier M, Fortin D, Whittingstall K, Descoteaux M. 3D interactive tractography-informed resting-state fMRI connectivity. Front Neurosci 2015; 9:275. [PMID: 26321901 PMCID: PMC4531323 DOI: 10.3389/fnins.2015.00275] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 07/22/2015] [Indexed: 01/01/2023] Open
Abstract
In the past decade, the fusion between diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) has opened the way for exploring structure-function relationships in vivo. As it stands, the common approach usually consists of analysing fMRI and dMRI datasets separately or using one to inform the other, such as using fMRI activation sites to reconstruct dMRI streamlines that interconnect them. Moreover, given the large inter-individual variability of the healthy human brain, it is possible that valuable information is lost when a fixed set of dMRI/fMRI analysis parameters such as threshold values are assumed constant across subjects. By allowing one to modify such parameters while viewing the results in real-time, one can begin to fully explore the sensitivity of structure-function relations and how they differ across brain areas and individuals. This is especially important when interpreting how structure-function relationships are altered in patients with neurological disorders, such as the presence of a tumor. In this study, we present and validate a novel approach to achieve this: First, we present an interactive method to generate and visualize tractography-driven resting-state functional connectivity, which reduces the bias introduced by seed size, shape and position. Next, we demonstrate that structural and functional reconstruction parameters explain a significant portion of intra- and inter-subject variability. Finally, we demonstrate how our proposed approach can be used in a neurosurgical planning context. We believe this approach will promote the exploration of structure-function relationships in a subject-specific aspect and will open new opportunities for connectomics.
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Affiliation(s)
- Maxime Chamberland
- Centre de Recherche CHUS, University of Sherbrooke Sherbrooke, QC, Canada ; Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, University of Sherbrooke Sherbrooke, QC, Canada ; Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke Sherbrooke, QC, Canada
| | - Michaël Bernier
- Centre de Recherche CHUS, University of Sherbrooke Sherbrooke, QC, Canada ; Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche CHUS, University of Sherbrooke Sherbrooke, QC, Canada ; Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, University of Sherbrooke Sherbrooke, QC, Canada
| | - Kevin Whittingstall
- Centre de Recherche CHUS, University of Sherbrooke Sherbrooke, QC, Canada ; Department of Nuclear Medicine 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
| | - Maxime Descoteaux
- Centre de Recherche CHUS, University of Sherbrooke Sherbrooke, QC, Canada ; Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, University of Sherbrooke Sherbrooke, QC, Canada
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Lang S, Duncan N, Northoff G. Resting-state functional magnetic resonance imaging: review of neurosurgical applications. Neurosurgery 2014; 74:453-64; discussion 464-5. [PMID: 24492661 DOI: 10.1227/neu.0000000000000307] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Recent research in brain imaging has highlighted the role of different neural networks in the resting state (ie, no task) in which the brain displays spontaneous low-frequency neuronal oscillations. These can be indirectly measured with resting-state functional magnetic resonance imaging, and functional connectivity can be inferred as the spatiotemporal correlations of this signal. This technique has proliferated in recent years and has allowed the noninvasive investigation of large-scale, distributed functional networks. In this review, we give a brief overview of resting-state networks and examine the use of resting-state functional magnetic resonance imaging in neurosurgical contexts, specifically with respect to neurooncology, epilepsy surgery, and deep brain stimulation. We discuss the advantages and disadvantages compared with task-based functional magnetic resonance imaging, the limitations of resting-state functional magnetic resonance imaging, and the emerging directions of this relatively new technology.
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Affiliation(s)
- Stefan Lang
- *Department of Neurosurgery, University of Calgary, Calgary, Alberta, Canada; ‡Mind, Brain Imaging, and Neuroethics Unit, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada; §Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
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Böttger J, Schurade R, Jakobsen E, Schaefer A, Margulies DS. Connexel visualization: a software implementation of glyphs and edge-bundling for dense connectivity data using brainGL. Front Neurosci 2014; 8:15. [PMID: 24624052 PMCID: PMC3941704 DOI: 10.3389/fnins.2014.00015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Accepted: 01/21/2014] [Indexed: 01/21/2023] Open
Abstract
The visualization of brain connectivity becomes progressively more challenging as analytic and computational advances begin to facilitate connexel-wise analyses, which include all connections between pairs of voxels. Drawing full connectivity graphs can result in depictions that, rather than illustrating connectivity patterns in more detail, obfuscate patterns owing to the data density. In an effort to expand the possibilities for visualization, we describe two approaches for presenting connexels: edge-bundling, which clarifies structure by grouping geometrically similar connections; and, connectivity glyphs, which depict a condensed connectivity map at each point on the cortical surface. These approaches can be applied in the native brain space, facilitating interpretation of the relation of connexels to brain anatomy. The tools have been implemented as part of brainGL, an extensive open-source software for the interactive exploration of structural and functional brain data.
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Affiliation(s)
- Joachim Böttger
- Max Planck Research Group for Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Ralph Schurade
- MEG and Cortical Networks Unit, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Estrid Jakobsen
- Max Planck Research Group for Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Alexander Schaefer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Daniel S Margulies
- Max Planck Research Group for Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
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Böttger J, Schäfer A, Lohmann G, Villringer A, Margulies DS. Three-dimensional mean-shift edge bundling for the visualization of functional connectivity in the brain. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2014; 20:471-480. [PMID: 23959625 DOI: 10.1109/tvcg.2013.114] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Functional connectivity, a flourishing new area of research in human neuroscience, carries a substantial challenge for visualization: while the end points of connectivity are known, the precise path between them is not. Although a large body of work already exists on the visualization of anatomical connectivity, the functional counterpart lacks similar development. To optimize the clarity of whole-brain and complex connectivity patterns in three-dimensional brain space, we develop mean-shift edge bundling, which reveals the multitude of connections as derived from correlations in the brain activity of cortical regions.
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Kollndorfer K, Furtner J, Krajnik J, Prayer D, Schöpf V. Attention shifts the language network reflecting paradigm presentation. Front Hum Neurosci 2013; 7:809. [PMID: 24324429 PMCID: PMC3838991 DOI: 10.3389/fnhum.2013.00809] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 11/07/2013] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES Functional magnetic resonance imaging (fMRI) is a reliable and non-invasive method with which to localize language function in pre-surgical planning. In clinical practice, visual stimulus presentation is often difficult or impossible, due to the patient's restricted language or attention abilities. Therefore, our aim was to investigate modality-specific differences in visual and auditory stimulus presentation. METHODS Ten healthy subjects participated in an fMRI study comprising two experiments with visual and auditory stimulus presentation. In both experiments, two language paradigms (one for language comprehension and one for language production) used in clinical practice were investigated. In addition to standard data analysis by the means of the general linear model (GLM), independent component analysis (ICA) was performed to achieve more detailed information on language processing networks. RESULTS GLM analysis revealed modality-specific brain activation for both language paradigms for the contrast visual > auditory in the area of the intraparietal sulcus and the hippocampus, two areas related to attention and working memory. Using group ICA, a language network was detected for both paradigms independent of stimulus presentation modality. The investigation of language lateralization revealed no significant variations. Visually presented stimuli further activated an attention-shift network, which could not be identified for the auditory presented language. CONCLUSION The results of this study indicate that the visually presented language stimuli additionally activate an attention-shift network. These findings will provide important information for pre-surgical planning in order to preserve reading abilities after brain surgery, significantly improving surgical outcomes. Our findings suggest that the presentation modality for language paradigms should be adapted on behalf of individual indication.
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Affiliation(s)
- Kathrin Kollndorfer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna Vienna, Austria
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Castellanos FX, Di Martino A, Craddock RC, Mehta AD, Milham MP. Clinical applications of the functional connectome. Neuroimage 2013; 80:527-40. [PMID: 23631991 PMCID: PMC3809093 DOI: 10.1016/j.neuroimage.2013.04.083] [Citation(s) in RCA: 213] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2013] [Revised: 04/18/2013] [Accepted: 04/20/2013] [Indexed: 12/26/2022] Open
Abstract
Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.
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Affiliation(s)
- F. Xavier Castellanos
- Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, NY 10016, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Adriana Di Martino
- Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, NY 10016, USA
| | - R. Cameron Craddock
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Ashesh D. Mehta
- Department of Neurosurgery, Hofstra North Shore LIJ School of Medicine and Feinstein Institute for Medical Research, Manhasset, NY 11030, USA, (F.X. Castellanos)
| | - Michael P. Milham
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
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Kollndorfer K, Fischmeister FPS, Kasprian G, Prayer D, Schöpf V. A systematic investigation of the invariance of resting-state network patterns: is resting-state fMRI ready for pre-surgical planning? Front Hum Neurosci 2013; 7:95. [PMID: 23532457 PMCID: PMC3607808 DOI: 10.3389/fnhum.2013.00095] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2012] [Accepted: 03/07/2013] [Indexed: 11/28/2022] Open
Abstract
Objectives: Measurements of resting-state networks (RSNs) have been used to investigate a wide range of diseases, such as dementia or epilepsy. This raises the question whether this method could also serve as a pre-surgical planning tool. Generating reliable functional connectivity patterns is of crucial importance, particularly for pre-surgical planning, as these patterns may directly affect the outcome. Methods: This study investigated the reproducibility of four commonly used resting-state conditions: fixation of a black crosshair on a white screen; fixation of the center of a black screen; eyes-closed and fixation of the words “Entspann dich!” (Engl., “relax”). Ten healthy, right-handed male subjects (mean age, 25 years; SD 2) participated in the experiment. The spatial overlap for different RSNs across the four conditions was calculated. Results: The spatial overlap across all four conditions was calculated for each seed region on a single subject and at the group level. Activation maps at the single-subject and group levels were highly stable, especially for the reading network (RNW). The lowest consistency measures were found for the visual network (VIN). At the single-subject level spatial overlap values ranged from 0.31 (VIN) to 0.45 (RNW). Conclusion: These findings suggest that RSN measurements are a reliable tool to assess language-related networks in clinical settings. Generally, resting-state conditions showed comparable activation patterns, therefore no specific conditions appears to be preferable.
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Affiliation(s)
- K Kollndorfer
- Department of Radiology, Division of Neuro- and Musculoskeletal Radiology, Medical University of Vienna Vienna, Austria
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