Imaging Mechanisms of Disease Progression in Multiple Sclerosis: Beyond Brain Atrophy
Corresponding Author
Francesca Bagnato
Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
These individuals were workshop organizers and are equal contributors to this work.
Correspondence: Address correspondence to Francesca Bagnato, Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, 2201 Children's Way, Suite 1222, Nashville, TN 37212. E-mail: [email protected].
Search for more papers by this authorSusan A. Gauthier
Judith Jaffe Multiple Sclerosis Center, Department of Neurology, Feil Family Brain and Mind Institute, and Department of Radiology, Weill Cornell Medicine, New York, NY
These individuals were workshop organizers and are equal contributors to this work.
Search for more papers by this authorCornelia Laule
Department of Radiology, Pathology, and Laboratory Medicine, Department of Physics and Astronomy, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
These individuals were workshop organizers and are equal contributors to this work.
Search for more papers by this authorGeorge R. Wayne Moore
Department of Pathology and Laboratory Medicine, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
Search for more papers by this authorRiley Bove
Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA
Search for more papers by this authorZhengxin Cai
Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, CT
Search for more papers by this authorJulien Cohen-Adad
NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal and Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
Search for more papers by this authorDaniel M. Harrison
Department of Neurology, University of Maryland School of Medicine, Baltimore, MD
Search for more papers by this authorEric C. Klawiter
Massachusetts General Hospital, Harvard Medical School, Boston, MA
Search for more papers by this authorSarah A. Morrow
Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
Search for more papers by this authorGülin Öz
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
Search for more papers by this authorWilliam D. Rooney
Advanced Imaging Research Center, Departments of Biomedical Engineering, Neurology, and Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
Search for more papers by this authorSeth A. Smith
Radiology and Radiological Sciences and Vanderbilt University Imaging Institute, Vanderbilt University Medical Center, and Biomedical Engineering, Vanderbilt University, Nashville, TN
Search for more papers by this authorPeter A. Calabresi
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
Search for more papers by this authorRoland G. Henry
Departments of Neurology, Radiology and Biomedical Imaging, and the UC San Francisco & Berkeley Bioengineering Graduate Group, University of California San Francisco, San Francisco, CA
Search for more papers by this authorJiwon Oh
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
Division of Neurology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
Search for more papers by this authorDaniel Ontaneda
Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH
Search for more papers by this authorDaniel Pelletier
Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA
Search for more papers by this authorDaniel S. Reich
Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD
Search for more papers by this authorRussell T. Shinohara
Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA
Search for more papers by this authorNancy L. Sicotte
Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
Search for more papers by this authorNAIMS Cooperative
Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
Search for more papers by this authorCorresponding Author
Francesca Bagnato
Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
These individuals were workshop organizers and are equal contributors to this work.
Correspondence: Address correspondence to Francesca Bagnato, Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, 2201 Children's Way, Suite 1222, Nashville, TN 37212. E-mail: [email protected].
Search for more papers by this authorSusan A. Gauthier
Judith Jaffe Multiple Sclerosis Center, Department of Neurology, Feil Family Brain and Mind Institute, and Department of Radiology, Weill Cornell Medicine, New York, NY
These individuals were workshop organizers and are equal contributors to this work.
Search for more papers by this authorCornelia Laule
Department of Radiology, Pathology, and Laboratory Medicine, Department of Physics and Astronomy, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
These individuals were workshop organizers and are equal contributors to this work.
Search for more papers by this authorGeorge R. Wayne Moore
Department of Pathology and Laboratory Medicine, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
Search for more papers by this authorRiley Bove
Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA
Search for more papers by this authorZhengxin Cai
Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, CT
Search for more papers by this authorJulien Cohen-Adad
NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal and Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
Search for more papers by this authorDaniel M. Harrison
Department of Neurology, University of Maryland School of Medicine, Baltimore, MD
Search for more papers by this authorEric C. Klawiter
Massachusetts General Hospital, Harvard Medical School, Boston, MA
Search for more papers by this authorSarah A. Morrow
Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
Search for more papers by this authorGülin Öz
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
Search for more papers by this authorWilliam D. Rooney
Advanced Imaging Research Center, Departments of Biomedical Engineering, Neurology, and Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
Search for more papers by this authorSeth A. Smith
Radiology and Radiological Sciences and Vanderbilt University Imaging Institute, Vanderbilt University Medical Center, and Biomedical Engineering, Vanderbilt University, Nashville, TN
Search for more papers by this authorPeter A. Calabresi
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
Search for more papers by this authorRoland G. Henry
Departments of Neurology, Radiology and Biomedical Imaging, and the UC San Francisco & Berkeley Bioengineering Graduate Group, University of California San Francisco, San Francisco, CA
Search for more papers by this authorJiwon Oh
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
Division of Neurology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
Search for more papers by this authorDaniel Ontaneda
Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH
Search for more papers by this authorDaniel Pelletier
Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA
Search for more papers by this authorDaniel S. Reich
Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD
Search for more papers by this authorRussell T. Shinohara
Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA
Search for more papers by this authorNancy L. Sicotte
Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
Search for more papers by this authorNAIMS Cooperative
Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
Search for more papers by this authorWe thank Amalie Chen from the Medical School at Vanderbilt University (currently Resident Physician, PGY-1 Departments of Internal Medicine and Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School) for her assistance in organizing the references and Dr. Karina Ciccone (Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center) for assistance with editorial changes during the revisions of the manuscript.
A full list of members of the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative at the time of the workshop is provided in the acknowledgment and disclosure section.
Dr. Bagnato serves in the Editorial Board of Journal of Neuroimaging, served on advisory boards for EMD Serono, acted as site PI for multi-center trial funded by Novartis, acts as site PI for a multi-center trial funded by EMD Serono, serves as consultant for Novartis. Dr. Bagnato receives funds from NIH: RO1 NS109114-01; NMSS: PP-1801-29686 and RG 1807-31051; and Biogen Idec. Dr. Gauthier serves in the Editorial Board of Journal of Neuroimaging and served as a consultant for Celgene. Dr. Gauthier receives funds from NIH: RO1 NS104283, RO1 NS105144, and R01 NS090464. Dr. Laule serves in the Editorial Board of Journal of Neuroimaging. Dr. Laule receives funds from the MS Society of Canada and the Natural Sciences and Engineering Research Council of Canada. Dr. Moore has received a grant-in-aid of research from Berlex Canada and a teaching honorarium from Teva, and served as a consultant to Schering. Dr. Moore receives funds from the MS Society of Canada: EGID 3248. Dr. Bove served as a consultant for EMD-Serono, Novartis, Roche Genentech, and Sanofi-Genzyme. Dr. Bove receives funds from NMSS CA TA 3062-A-3; California Institute to Advance Precision Medicine and Hilton Foundation Grant 16850. Dr. Cai has no conflicts to declare. Dr. Cai receives funds from NIH: K01 EB023312 and R01 AG058773. Dr. Cohen-Adad has no conflicts to declare. Dr. Cohen-Adad receives funds from the Canada Research Chair in Quantitative Magnetic Resonance Imaging: 950–230815; the Canadian Institute of Health Research: CIHR FDN-143263; the Canada Foundation for Innovation (32454, 34824); the Fonds de Recherche du Québec: Santé 28826; the Fonds de Recherche du Québec - Nature et Technologies: 2015-PR-182754; Natural Sciences and Engineering Research Council of Canada: RGPIN-2019-07244; Canada First Research Excellence Fund IVADO and TransMedTech; Quebec BioImaging Network: 5886, 35450. Dr. Harrison received consulting fees from EMD-Serono, Genzyme, Biogen, and Genentech. Dr. Harrison receives funds from NIH: 1K23NS072366-01A1 and 1R01NS104403-01, NMSS: PP-1804-30760, EMD Serono, and Roche Genentech. Dr. Klawiter receives consulting fees from Alexion, Biogen, EMD Serono, and Genentech. Dr. Klawiter receives funds from NIH K23NS078044, Abbvie, Biogen, EMD Serono, Genzyme, and Roche Genentech. Dr. Morrow served on advisory boards for Biogen Idec, EMD Serono, Genzyme Canada, Novartis, and Roche. Dr. Morrow received Investigator Initiated Grant Funds from Biogen Idec, Novartis, and Roche, and has acted as site PI for multi-center trials funded by Novartis, Genzyme, Roche, and AbbVie. Dr. Oz has no conflicts to declare. Dr. Oz receives funds from NIH: R01 NS080816 and P41 EB015894; the Institutional Center Cores for Advanced Neuroimaging: P30 NS076408. Dr. Rooney has no conflicts to declare. Dr. Rooney receives funds from the NIH: R01-EB007258 and R01NS40801; NMSS: RG 3168A1; C.N. Hilton Foundation MS Innovation Fund 20140260. Dr. Smith serves in the Board of Trustees for the Southeast NMSS. Dr. Smith receives funds from NIH: R01NS104149 and R01NS109114-01; NMSS: RG 1501–02840; C.N. Hilton Foundation MS Innovation Fund 17237; Novartis IIRP-1456. Dr. Calabresi received personal compensation for serving on scientific advisory boards from Disarm Therapeutics and Biogen Idec. Dr. Calabresi receives funds from NIH: R01NS082347, R37NS041435, and the NMSS. He is PI on grants from Biogen and Annexon to JHU. Dr. Oh serves on the Editorial Board of J Neuroimaging and receives funding from the MS Society of Canada, NMSS, Brain Canada, Biogen-Idec, Roche, and Sanofi-Genzyme. Dr. Oh has received personal compensation for consulting for Biogen-Idec, Celgene, Novartis, Sanofi-Genzyme, Roche, and EMD-Serono. Dr. Ontaneda received consulting fees from Biogen Idec, Genentech/Roche, Genzyme, Novartis, and Merck. Dr. Ontaneda has received research support from the NIH (R01NS091683 and R21NS106522), Patient Centered Outcomes Research Institute (PCORI MS-1610-37047) and the Department of Defense DOD (W81XWH-16-1-0446), the Race to Erase MS Foundation, Genentech, Genzyme, and Novartis. Dr. Pelletier received consulting fees from Alexion, Biogen, Genzyme, Novartis, and Roche. Dr. Reich received research funds via a Cooperative Research and Development Agreement with Vertex Pharmaceuticals, not connected to this paper. Dr. Reich is funded by the Intramural Research Program of NINDS. Dr. Shinohara has received consulting income from Genentech/Roche and compensation for editorial/reviewing duties from Research Square and the American Medical Association. Dr. Shinohara receives funds from NIH: R01 NS085211, R01 MH112847 and R01 NS060910) and the NMSS: RG-1707-28586 and PP-1901-33080. Dr. Sicotte has no conflicts to declare. Dr. Sicotte receives funds from the NMSS: RG1507-05418, PCORI: MS-1610-37115 and the Race to Erase MS: CAVS in Early MS.
The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies.
Members of the NAIMS at the time of the workshop and not listed as authors in the manuscript include: Drs. Brenda Banwell (Children's Hospital of Pennsylvania), Amit Bar-Or (University of Pennsylvania), Alex Brandt (University of California at Irvine), Phil De Jager (Columbia University), Leorah Freeman (University of Texas at Houston), Rohit Bakshi and Charles Guttmann (Brigham and Women's Hospital), Roland Henry (University of California San Francisco), Matilde Inglese (Icahn School of Medicine at Mount Sinai), Caterina Mainero (Massachusetts General Hospital), Naila Makhani (Yale University), Ravi Menon (Western University), Robert Naismith, (Washington University), Sridar Narayanan (McGill University), Bart Rympa (University of Texas South Western), Andrew Solomon (University of Vermont), Anthony Traboulsee (University of British Columbia), Alan Wilman (University of Alberta), Yunyan Zhang (University of Calgary), Robert Zivadinov (Buffalo Neuroimaging Analysis Center, State University of New York), Zongqi Xia (University of Pittsburgh).
ABSTRACT
Clinicians involved with different aspects of the care of persons with multiple sclerosis (MS) and scientists with expertise on clinical and imaging techniques convened in Dallas, TX, USA on February 27, 2019 at a North American Imaging in Multiple Sclerosis Cooperative workshop meeting. The aim of the workshop was to discuss cardinal pathobiological mechanisms implicated in the progression of MS and novel imaging techniques, beyond brain atrophy, to unravel these pathologies. Indeed, although brain volume assessment demonstrates changes linked to disease progression, identifying the biological mechanisms leading up to that volume loss are key for understanding disease mechanisms. To this end, the workshop focused on the application of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques to assess and measure disease progression in both the brain and the spinal cord. Clinical translation of quantitative MRI was recognized as of vital importance, although the need to maintain a relatively short acquisition time mandated by most radiology departments remains the major obstacle toward this effort. Regarding PET, the panel agreed upon its utility to identify ongoing pathological processes. However, due to costs, required expertise, and the use of ionizing radiation, PET was not considered to be a viable option for ongoing care of persons with MS. Collaborative efforts fostering robust study designs and imaging technique standardization across scanners and centers are needed to unravel disease mechanisms leading to progression and discovering medications halting neurodegeneration and/or promoting repair.
References
- 1Lassmann H. Multiple sclerosis pathology. Cold Spring Harb Perspect Med 2018; 8:a028936.
- 2Bermel R, Bakshi R. The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol 2006; 5: 158-70.
- 3Oh J, Ontaneda D, Azevedo C, et al. Imaging outcome measures of neuroprotection and repair in MS: a consensus statement from NAIMS. Neurology 2019; 92: 519-33.
- 4Fox R, Thompson A, Baker D, et al. Setting a research agenda for progressive multiple sclerosis: the International Collaborative on Progressive MS. Mult Scler 2012; 18: 1534-40.
- 5Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983; 33: 1444-52.
- 6Polman CH, Rudick RA. The multiple sclerosis functional composite: a clinically meaningful measure of disability. Neurology 2010; 74(Suppl 3): S8-15.
- 7Bove R, Garcha P, Bevan CJ, et al. Clinic to in-home telemedicine reduces barriers to care for patients with MS or other neuroimmunologic conditions. Neurol Neuroimmunol Neuroinflammation 2018; 5:e505.
- 8Bove R, White CC, Giovannoni G, et al. Evaluating more naturalistic outcome measures: a 1-year smartphone study in multiple sclerosis. Neurol Neuroimmunol Neuroinflammation 2015; 2:e162.
- 9Block VJ, Bove R, Zhao C, et al. Association of continuous assessment of step count by remote monitoring with disability progression among adults with multiple sclerosis. JAMA Netw Open 2019; 2:e190570.
- 10Rao SM, Losinski G, Mourany L, et al. Processing speed test: validation of a self-administered, iPad®-based tool for screening cognitive dysfunction in a clinic setting. Mult Scler 2017; 23: 1929-37.
- 11Strober LB, Rao SM, Lee J-C, et al. Cognitive impairment in multiple sclerosis: an 18 year follow-up study. Mult Scler Relat Disord 2014; 3: 473-81.
- 12Chiaravalloti ND, DeLuca J. Cognitive impairment in multiple sclerosis. Lancet Neurol 2008; 7: 1139-51.
- 13Morrow SA, O'Connor PW, Polman CH, et al. Evaluation of the symbol digit modalities test (SDMT) and MS neuropsychological screening questionnaire (MSNQ) in natalizumab-treated MS patients over 48 weeks. Mult Scler 2010; 16: 1385-92.
- 14Strober L, DeLuca J, Benedict RH, et al. Symbol digit modalities test: a valid clinical trial endpoint for measuring cognition in multiple sclerosis. Mult Scler 2019; 25: 1781-90.
- 15Benedict RH, DeLuca J, Phillips G, et al. Validity of the symbol digit modalities test as a cognition performance outcome measure for multiple sclerosis. Mult Scler 2017; 23: 721-33.
- 16Langdon DW, Amato MP, Boringa J, et al. Recommendations for a brief international cognitive assessment for multiple sclerosis (BICAMS). Mult Scler 2012; 18: 891-8.
- 17Katz D, Taubenberger JK, Cannella B, et al. Correlation between magnetic resonance imaging findings and lesion development in chronic, active multiple sclerosis. Ann Neurol 1993; 34: 661-9.
- 18McFarland HF, Frank JA, Albert PS, et al. Using gadolinium-enhanced magnetic resonance imaging lesions to monitor disease activity in multiple sclerosis. Ann Neurol 1992; 32: 758-66.
- 19Hoftberger R, Lassmann H. Inflammatory demyelinating diseases of the central nervous system. Handb Clin Neuro 2017; 145: 263-83.
- 20Raine C. Demyelinating disease. In: R Davis, D Robertson, eds. Textbook of Neuropathology. 3rd ed. Baltimore, MD: Williams & Wilkins; 1997: 627-714.
- 21Prineas J, McDonald W, Franklin R. Demyelinating diseases. In: D Graham, P Lantos, eds. Greenfield's Neuropathology. 7th ed. London, UK: Arnold; 2002: 471-550.
- 22Ludwin S, Raine C. The neuropathology of multiple sclerosis. In: C Raine, H McFarland, R Hohlfeld, eds. Multiple Sclerosis: A Comprehensive Text. Philadelphia, PA: Saunders Elsevier; 2008: 151-7.
- 23Moore G, Stadelmann-Nessler C. Demyelinating diseases. In: S Love, A Perry, J Ironside, H Budka, eds. Greenfield's Neuropathology. 9th ed. Boca Raton, FL: CRC Press; 2015: 1297-412.
- 24van der Valk P, Amor S. Preactive lesions in multiple sclerosis. Curr Opin Neurol 2009; 22: 207-13.
- 25Kuhlmann T, Ludwin S, Prat A, et al. An updated histological classification system for multiple sclerosis lesions. Acta Neuropathol 2017; 133: 13-24.
- 26Kutzelnigg A, Lucchinetti CF, Stadelmann C, et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 2005; 128: 2705-12.
- 27Plumb J, McQuaid S, Mirakhur M, et al. Abnormal endothelial tight junctions in active lesions and normal-appearing white matter in multiple sclerosis. Brain Pathol 2002; 12: 154-69.
- 28Howell OW, Rundle JL, Garg A, et al. Activated microglia mediate axoglial disruption that contributes to axonal injury in multiple sclerosis. J Neuropathol Exp Neurol 2010; 69: 1017-33.
- 29Lucchinetti CF, Popescu BFG, Bunyan RF, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med 2011; 365: 2188-97.
- 30Bø L, Vedeler CA, Nyland H, et al. Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Mult Scler 2003; 9: 323-31.
- 31Howell OW, Reeves CA, Nicholas R, et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain 2011; 134: 2755-71.
- 32Vercellino M, Masera S, Lorenzatti M, et al. Demyelination, inflammation, and neurodegeneration in multiple sclerosis deep gray matter. J Neuropathol Exp Neurol 2009; 68: 489-502.
- 33Haider L, Simeonidou C, Steinberger G, et al. Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron. J Neurol Neurosurg Psychiatry 2014; 85: 1386-95.
- 34Banati RB, Newcombe J, Gunn RN, et al. The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain 2000; 123: 2321-37.
- 35Cosenza-Nashat M, Zhao ML, Suh HS, et al. Expression of the translocator protein of 18 kDa by microglia, macrophages and astrocytes based on immunohistochemical localization in abnormal human brain. Neuropathol Appl Neurobiol 2009; 35: 306-28.
- 36Politis M, Giannetti P, Su P, et al. Increased PK11195 PET binding in the cortex of patients with MS correlates with disability. Neurology 2012; 79: 523-30.
- 37Rissanen E, Tuisku J, Rokka J, et al. In vivo detection of diffuse inflammation in secondary progressive multiple sclerosis using PET imaging and the radioligand 11C-PK11195. J Nucl Med 2014; 55: 939-44.
- 38Giannetti P, Politis M, Su P, et al. Microglia activation in multiple sclerosis black holes predicts outcome in progressive patients: an in vivo [(11)C](R)-PK11195-PET pilot study. Neurobiol Dis 2014; 65: 203-10.
- 39Kaunzner UW, Kang Y, Monohan E, et al. Reduction of PK11195 uptake observed in multiple sclerosis lesions after natalizumab initiation. Mult Scler Relat Disord 2017; 15: 27-33.
- 40Sucksdorff M, Rissanen E, Tuisku J, et al. Evaluation of the effect of fingolimod treatment on microglial activation using serial PET imaging in multiple sclerosis. J Nucl Med 2017; 58: 1646-51.
- 41Ratchford JN, Endres CJ, Hammoud DA, et al. Decreased microglial activation in MS patients treated with glatiramer acetate. J Neurol 2012; 259: 1199-205.
- 42Rissanen E, Tuisku J, Vahlberg T, et al. Microglial activation, white matter tract damage, and disability in MS. Neurol Neuroimmunol Neuroinflammation 2018; 5:e443.
- 43Hagens MHJ, Golla SV, Wijburg MT, et al. In vivo assessment of neuroinflammation in progressive multiple sclerosis: a proof of concept study with [18F]DPA714 PET. J Neuroinflammation 2018; 15: 314-23.
- 44Endres CJ, Pomper MG, James M, et al. Initial evaluation of 11C-DPA-713, a novel TSPO PET ligand, in humans. J Nucl Med 2009; 50: 1276-82.
- 45Park E, Gallezot J-D, Delgadillo A, et al. (11)C-PBR28 imaging in multiple sclerosis patients and healthy controls: test-retest reproducibility and focal visualization of active white matter areas. Eur J Nucl Med Mol Imaging 2015; 42: 1081-92.
- 46Singhal T, OʼConnor K, Dubey S, et al. 18F-PBR06 Versus 11C-PBR28 PET for assessing white matter translocator protein binding in multiple sclerosis. Clin Nucl Med 2018; 43: e289-95.
- 47Unterrainer M, Mahler C, Vomacka L, et al. TSPO PET with [18F]GE-180 sensitively detects focal neuroinflammation in patients with relapsing-remitting multiple sclerosis. Eur J Nucl Med Mol Imaging 2018; 45: 1423-31.
- 48Ikawa M, Lohith TG, Shrestha S, et al. 11C-ER176, a Radioligand for 18-kDa translocator protein, has adequate sensitivity to robustly image all three affinity genotypes in human brain. J Nucl Med 2017; 58: 320-5.
- 49Beaino W, Janssen B, Kooij G, et al. Purinergic receptors P2Y12R and P2X7R: potential targets for PET imaging of microglia phenotypes in multiple sclerosis. J Neuroinflammation 2017; 14: 259.
- 50Horti AG, Naik R, Foss CA, et al. PET imaging of microglia by targeting macrophage colony-stimulating factor 1 receptor (CSF1R). Proc Natl Acad Sci USA 2019; 116: 1686-91.
- 51Hametner S, Wimmer I, Haider L, et al. Iron and neurodegeneration in the multiple sclerosis brain. Ann Neurol 2013; 74: 848-61.
- 52Dal-Bianco A, Grabner G, Kronnerwetter C, et al. Slow expansion of multiple sclerosis iron rim lesions: pathology and 7 T magnetic resonance imaging. Acta Neuropathol 2017; 133: 25-42.
- 53Popescu BF, Frischer JM, Webb SM, et al. Pathogenic implications of distinct patterns of iron and zinc in chronic MS lesions. Acta Neuropathol 2017; 134: 45-64.
- 54Langkammer C, Krebs N, Goessler W, et al. Quantitative MR imaging of brain iron: a postmortem validation study. Radiology 2010; 257: 455-62.
- 55Hammond KE, Metcalf M, Carvajal L, et al. Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron. Ann Neurol 2008; 64: 707-13.
- 56Bagnato F, Hametner S, Welch EB. Visualizing iron in multiple sclerosis. Magn Reson Imaging 2013; 31: 376-84.
- 57Yao B, Ikonomidou VN, Cantor FK, et al. Heterogeneity of multiple sclerosis white matter lesions detected with T2*-weighted imaging at 7.0 tesla. J Neuroimaging 2015; 25: 799-806.
- 58Absinta M, Sati P, Schindler M, et al. Persistent 7-tesla phase rim predicts poor outcome in new multiple sclerosis patient lesions. J Clin Invest 2016; 126: 2597-609.
- 59Mehta V, Pei W, Yang G, et al. Iron is a sensitive biomarker for inflammation in multiple sclerosis lesions. PLoS ONE 2013; 8:e57573.
- 60Chen W, Gauthier S, Gupta A, et al. Dynamic magnetic property of multiple sclerosis lesions at various ages measured by quantitative susceptibility mapping. Proc Intl Soc Mag Reson Med 2012; 59: 0692.
- 61Wang Y, Liu T. Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med 2015; 73: 82-101.
- 62Kaunzner UW, Kang Y, Zhang S, et al. Quantitative susceptibility mapping identifies inflammation in a subset of chronic multiple sclerosis lesions. Brain 2019; 142: 133-45.
- 63Yao Y, Nguyen TD, Pandya S, et al. Combining quantitative susceptibility mapping with automatic zero reference (QSM0) and myelin water fraction imaging to quantify iron-related myelin damage in chronic active MS lesions. AJNR Am J Neuroradiol 2018; 39: 303-10.
- 64Absinta M, Sati P, Reich D. Advanced MRI and staging of multiple sclerosis lesions. Nat Rev Neurol 2016; 12: 358-68.
- 65Absinta M, Sati P, Masuzzo F, et al. Association of chronic active multiple sclerosis lesions with disability in vivo. JAMA neurology 2019; 76: 1474-83.
- 66Abbott NJ, Patabendige AAK, Dolman DEM, et al. Structure and function of the blood-brain barrier. Neurobiol Dis 2010; 37: 13-25.
- 67Kirk J, Plumb J, Mirakhur M, et al. Tight junctional abnormality in multiple sclerosis white matter affects all calibres of vessel and is associated with blood-brain barrier leakage and active demyelination. J Pathol 2003; 201: 319-27.
- 68Njus JM, Li X, Springer CS, et al. DCE-MRI Ktrans mapping of MS lesion evolution in individuals. Proc Int Soc Magn Reson Med 2008; 16: 3434.
- 69Goodkin DE, Rooney WD, Sloan R, et al. A serial study of new MS lesions and the white matter from which they arise. Neurology 1998; 51: 1689-97.
- 70Kermode AG, Thompson AJ, Tofts P, et al. Breakdown of the blood-brain barrier precedes symptoms and other MRI signs of new lesions in multiple sclerosis: Pathogenetic and clinical implications. Brain 1990; 113: 1477-9.
- 71Preston E, Foster DO. Evidence for pore-like opening of the blood-brain barrier following forebrain ischemia in rats. Brain Res 1997; 761: 4-10.
- 72Patlak CS, Blasberg RG, Fenstermacher JD. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 1983; 3: 1-7.
- 73Gaitán MI, Shea CD, Evangelou IE, et al. Evolution of the blood-brain barrier in newly forming multiple sclerosis lesions. Ann Neurol 2011; 70: 22-9.
- 74Gaitán MI, Sati P, Inati SJ, et al. Initial investigation of the blood-brain barrier in MS lesions at 7 tesla. Mult Scler 2013; 19: 1068-73.
- 75Yankeelov TE, Rooney WD, Huang W, et al. Evidence for shutter-speed variation in CR bolus-tracking studies of human pathology. NMR Biomed 2005; 18: 173-85.
- 76Rooney WD, Li X, Sammi MK, et al. Mapping human brain capillary water lifetime: high-resolution metabolic neuroimaging. NMR Biomed 2015; 28: 607-23.
- 77Wengler K, Bangiyev L, Canli T, et al. 3D MRI of whole-brain water permeability with intrinsic diffusivity encoding of arterial labeled spin (IDEALS). Neuroimage 2019; 189: 401-14.
- 78Shao X, Ma SJ, Casey M, et al. Mapping water exchange across the blood-brain barrier using 3D diffusion-prepared arterial spin labeled perfusion MRI. Magn Reson Med 2019; 81: 3065-79.
- 79Lin Z, Li Y, Su P, et al. Non-contrast MR imaging of blood-brain barrier permeability to water. Magn Reson Med 2018; 80: 1507-20.
- 80Mamourian AC, Hoopes PJ, Lewis LD. Visualization of intravenously administered contrast material in the CSF on fluid-attenuated inversion-recovery MR images: an in vitro and animal-model investigation. AJNR Am J Neuroradiol 2000; 21: 105-11.
- 81Eisele P, Griebe M, Szabo K, et al. Investigation of leptomeningeal enhancement in MS: a postcontrast FLAIR MRI study. Neurology 2015; 84: 770-5.
- 82Absinta M, Vuolo L, Rao A, et al. Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis. Neurology 2015; 85: 18-28.
- 83Zivadinov R, Ramasamy DP, Vaneckova M, et al. Leptomeningeal contrast enhancement is associated with progression of cortical atrophy in MS: a retrospective, pilot, observational longitudinal study. Mult Scler 2017; 23: 1336-45.
- 84Makshakov G, Magonov E, Totolyan N, et al. Leptomeningeal contrast enhancement is associated with disability progression and grey matter atrophy in multiple sclerosis. Neurol Res Int 2017; 2017: 1-7.
- 85Zurawski J, Tauhid S, Chu R, et al. 7T MRI cerebral leptomeningeal enhancement is common in relapsing-remitting multiple sclerosis and is associated with cortical and thalamic lesions. Mult Scler 2020; 26: 177-87.
- 86Harrison DM, Wang KY, Fiol J, et al. Leptomeningeal enhancement at 7T in multiple sclerosis: frequency, morphology, and relationship to cortical volume. J Neuroimaging 2017; 27: 461-8.
- 87Jonas SN, Izbudak I, Frazier AA, et al. Longitudinal persistence of meningeal enhancement on postcontrast 7T 3D-FLAIR MRI in multiple sclerosis. Am J Neuroradiol 2018; 39: 1799-805.
- 88Ighani M, Jonas S, Izbudak I, et al. No association between cortical lesions and leptomeningeal enhancement on 7-Tesla MRI in multiple sclerosis. Mult Scler J 2020; 26: 165-76.
- 89Bhargava P, Wicken C, Smith MD, et al. Trial of intrathecal rituximab in progressive multiple sclerosis patients with evidence of leptomeningeal contrast enhancement. Mult Scler Relat Disord 2019; 30: 136-40.
- 90Tallantyre EC, Bø L, Al-Rawashdeh O, et al. Clinico-pathological evidence that axonal loss underlies disability in progressive multiple sclerosis. Mult Scler 2010; 16: 406-11.
- 91Compston A, Lassmann H, McDonald I. The Story of Multiple Sclerosis. In: A Compston, C Confavreux, H Lassmann, et al., eds. McAlpine's Multiple Sclerosis. Philadelphia, PA: Churchill Livingstone Elsevier; 2005: 3–68.
- 92Ferguson B, Matyszak MK, Esiri MM, et al. Axonal damage in acute multiple sclerosis lesions. Brain J Neurol 1997; 120: 393-9.
- 93Trapp BD, Peterson J, Ransohoff RM, et al. Axonal transection in the lesions of multiple sclerosis. N Engl J Med 1998; 338: 278-85.
- 94Lu J-Q, Fan Y, Mitha AP, et al. Association of alpha-synuclein immunoreactivity with inflammatory activity in multiple sclerosis lesions. J Neuropathol Exp Neurol 2009; 68: 179-89.
- 95McQuaid S, Cunnea P, McMahon J, et al. The effects of blood-brain barrier disruption on glial cell function in multiple sclerosis. Biochem Soc Trans 2009; 37: 329-31.
- 96Werner P, Pitt D, Raine CS. Multiple sclerosis: altered glutamate homeostasis in lesions correlates with oligodendrocyte and axonal damage. Ann Neurol 2001; 50: 169-80.
- 97Christensen PC, Samadi-Bahrami Z, Pavlov V, et al. Ionotropic glutamate receptor expression in human white matter. Neurosci Lett 2016; 630: 1-8.
- 98Prineas JW, Connell F. The fine structure of chronically active multiple sclerosis plaques. Neurology 1978; 28: S68-75.
- 99Craner MJ, Newcombe J, Black JA, et al. Molecular changes in neurons in multiple sclerosis: altered axonal expression of Nav1.2 and Nav1.6 sodium channels and Na+/Ca2+ exchanger. Proc Natl Acad Sci USA 2004; 101: 8168-73.
- 100Smith KJ, McDonald WI. The pathophysiology of multiple sclerosis: the mechanisms underlying the production of symptoms and the natural history of the disease. Philos Trans R Soc Lond B Biol Sci 1999; 354: 1649-73.
- 101Kornek B, Storch MK, Bauer J, et al. Distribution of a calcium channel subunit in dystrophic axons in multiple sclerosis and experimental autoimmune encephalomyelitis. Brain 2001; 124: 1114-24.
- 102Young EA, Fowler CD, Kidd GJ, et al. Imaging correlates of decreased axonal Na+/K+ ATPase in chronic multiple sclerosis lesions. Ann Neurol 2008; 63: 428-35.
- 103Mahad DJ, Ziabreva I, Campbell G, et al. Mitochondrial changes within axons in multiple sclerosis. Brain 2009; 132: 1161-74.
- 104Evangelou N, Esiri MM, Smith S, et al. Quantitative pathological evidence for axonal loss in normal appearing white matter in multiple sclerosis. Ann Neurol 2000; 47: 391-5.
- 105Evangelou N, Konz D, Esiri MM, et al. Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis. Brain 2000; 123: 1845-9.
- 106Singh S, Metz I, Amor S, et al. Microglial nodules in early multiple sclerosis white matter are associated with degenerating axons. Acta Neuropathol 2013; 125: 595-608.
- 107Zhao GJ, Li DKB, Cheng Y, et al. MRI dirty-appearing white matter in MS. (Abstract). Neurology 2000; 54(Suppl 3): A121.
- 108Laule C, Pavlova V, Leung E, et al. Diffusely abnormal white matter in multiple sclerosis: further histologic studies provide evidence for a primary lipid abnormality with neurodegeneration. J Neuropathol Exp Neurol 2013; 72: 42-52.
- 109Peterson JW, Bö L, Mörk S, et al. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol 2001; 50: 389-400.
- 110Klaver R, Popescu V, Voorn P, et al. Neuronal and axonal loss in normal-appearing gray matter and subpial lesions in multiple sclerosis. J Neuropathol Exp Neurol 2015; 74: 453-8.
- 111Stys PK, Zamponi GW, van Minnen J, et al. Will the real multiple sclerosis please stand up? Nat Rev Neurosci 2012; 13: 507-14.
- 112Duarte JMN, Lei H, Mlynárik V, et al. The neurochemical profile quantified by in vivo 1H NMR spectroscopy. Neuroimage 2012; 61: 342-62.
- 113Oz G, Alger JR, Barker PB, et al. Clinical proton MR spectroscopy in central nervous system disorders. Radiology 2014; 270: 658-79.
- 114Cawley N, Ciccarelli O. MR Spectroscopy in Multiple Sclerosis. In: G Öz, ed. Magnetic Resonance Spectroscopy of Degenerative Brain Diseases. Cham, Switzerland: Springer International Publishing; 2016: 151-78.
10.1007/978-3-319-33555-1_8 Google Scholar
- 115Srinivasan R, Sailasuta N, Hurd R, et al. Evidence of elevated glutamate in multiple sclerosis using magnetic resonance spectroscopy at 3 T. Brain 2005; 128: 1016-25.
- 116Baranzini SE, Srinivasan R, Khankhanian P, et al. Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis. Brain 2010; 133: 2603-11.
- 117Klauser AM, Wiebenga OT, Eijlers AJ, et al. Metabolites predict lesion formation and severity in relapsing-remitting multiple sclerosis. Mult Scler 2018; 24: 491-500.
- 118MacMillan E, Tam R, Zhao Y, et al. Progressive multiple sclerosis exhibits decreasing glutamate and glutamine over two years. Mult Scler J 2016; 22: 112-6.
- 119Muhlert N, Atzori M, De Vita E, et al. Memory in multiple sclerosis is linked to glutamate concentration in grey matter regions. J Neurol Neurosurg Psychiatry 2014; 85: 833-9.
- 120Cawley N, Solanky BS, Muhlert N, et al. Reduced gamma-aminobutyric acid concentration is associated with physical disability in progressive multiple sclerosis. Brain 2015; 138: 2584-95.
- 121Bhattacharyya PK, Phillips MD, Stone LA, et al. Sensorimotor cortex gamma-aminobutyric acid concentration correlates with impaired performance in patients with MS. Am J Neuroradiol 2013; 34: 1733-9.
- 122Gao F, Yin X, Edden RAE, et al. Altered hippocampal GABA and glutamate levels and uncoupling from functional connectivity in multiple sclerosis. Hippocampus 2018; 28: 813-23.
- 123Cao G, Edden RAE, Gao F, et al. Reduced GABA levels correlate with cognitive impairment in patients with relapsing-remitting multiple sclerosis. Eur Radiol 2018; 28: 1140-8.
- 124Deelchand DK, Kantarci K, Öz G. Improved localization, spectral quality, and repeatability with advanced MRS methodology in the clinical setting. Magn Reson Med 2018; 79: 1241-50.
- 125Tkác I, Oz G, Adriany G, et al. In vivo 1H NMR spectroscopy of the human brain at high magnetic fields: metabolite quantification at 4T vs. 7T. Magn Reson Med 2009; 62: 868-79.
- 126Terpstra M, Cheong I, Lyu T, et al. Test-retest reproducibility of neurochemical profiles with short-echo, single-voxel MR spectroscopy at 3T and 7T. Magn Reson Med 2016; 76: 1083-91.
- 127Prinsen H, de Graaf RA, Mason GF, et al. Reproducibility measurement of glutathione, GABA, and glutamate: Towards in vivo neurochemical profiling of multiple sclerosis with MR spectroscopy at 7T. J Magn Reson Imaging JMRI 2017; 45: 187-98.
- 128van Munster CEP, Jonkman LE, Weinstein HC, et al. Gray matter damage in multiple sclerosis: impact on clinical symptoms. Neuroscience 2015; 303: 446-61.
- 129Vinters H, Kleinschmidt-DeMasters B. General pathology of the central nervous system. In: S Love, A Perry, J Ironside, et al., eds. Greenfield's Neuropathology. 9th ed. Boca Raton, FL: CRC Press; 2015: 1-58.
- 130Gray E, Thomas TL, Betmouni S, et al. Elevated matrix metalloproteinase-9 and degradation of perineuronal nets in cerebrocortical multiple sclerosis plaques. J Neuropathol Exp Neurol 2008; 67: 888-99.
- 131Haider L, Zrzavy T, Hametner S, et al. The topography of demyelination and neurodegeneration in the multiple sclerosis brain. Brain 2016; 139: 807-15.
- 132Papadopoulos D, Dukes S, Patel R, et al. Substantial archaeocortical atrophy and neuronal loss in multiple sclerosis. Brain Pathol 2009; 19: 238-53.
- 133Vercellino M, Plano F, Votta B, et al. Grey matter pathology in multiple sclerosis. J Neuropathol Exp Neurol 2005; 64: 1101-7.
- 134Wegner C, Esiri MM, Chance SA, et al. Neocortical neuronal, synaptic, and glial loss in multiple sclerosis. Neurology 2006; 67: 960-7.
- 135Magliozzi R, Howell OW, Reeves C, et al. A Gradient of neuronal loss and meningeal inflammation in multiple sclerosis. Ann Neurol 2010; 68: 477-93.
- 136Gray E, Rice C, Nightingale H, et al. Accumulation of cortical hyperphosphorylated neurofilaments as a marker of neurodegeneration in multiple sclerosis. Mult Scler 2013; 19: 153-61.
- 137Dutta R, McDonough J, Chang A, et al. Activation of the ciliary neurotrophic factor (CNTF) signalling pathway in cortical neurons of multiple sclerosis patients. Brain 2007; 130: 2566-76.
- 138Schirmer L, Merkler D, König FB, et al. Neuroaxonal regeneration is more pronounced in early multiple sclerosis than in traumatic brain injury lesions. Brain Pathol 2013; 23: 2-12.
- 139Evangelou N, Konz D, Esiri MM, et al. Size-selective neuronal changes in the anterior optic pathways suggest a differential susceptibility to injury in multiple sclerosis. Brain 2001; 124: 1813-20.
- 140Cifelli A, Arridge M, Jezzard P, et al. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002; 52: 650-3.
- 141Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 2007; 8: 700-11.
- 142Tahedl M, Levine SM, Greenlee MW, et al. Functional connectivity in multiple sclerosis: recent findings and future directions. Front Neurol 2018; 9: 828-46.
- 143Roosendaal SD, Schoonheim MM, Hulst HE, et al. Resting state networks change in clinically isolated syndrome. Brain 2010; 133: 1612-21.
- 144Patel KR, Tobyne S, Porter D, et al. Structural disconnection is responsible for increased functional connectivity in multiple sclerosis. Brain Struct Funct 2018; 223: 2519-26.
- 145Rocca MA, Valsasina P, Leavitt VM, et al. Functional network connectivity abnormalities in multiple sclerosis: correlations with disability and cognitive impairment. Mult Scler 2018; 24: 459-71.
- 146Faivre A, Robinet E, Guye M, et al. Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: a longitudinal resting-state fMRI study. Mult Scler 2016; 22: 1695-708.
- 147Tavazzi E, Bergsland N, Cattaneo D, et al. Effects of motor rehabilitation on mobility and brain plasticity in multiple sclerosis: a structural and functional MRI study. J Neurol 2018; 265: 1393-401.
- 148Schwartz DL, Tagge I, Powers K, et al. Multisite reliability and repeatability of an advanced brain MRI protocol. J Magn Reson Imaging JMRI 2019; 50: 878-88.
- 149Birn RM, Molloy EK, Patriat R, et al. The effect of scan length on the reliability of resting-state fMRI connectivity estimates. Neuroimage 2013; 83: 550-8.
- 150Braga RM, Dijk KRAV, Polimeni JR, et al. Parallel distributed networks resolved at high resolution reveal close juxtaposition of distinct regions. bioRxiv 2018:475806.
- 151De Giglio L, Tona F, De Luca F, et al. Multiple Sclerosis: changes in thalamic resting-state functional connectivity induced by a home-based cognitive rehabilitation program. Radiology 2016; 280: 202-11.
- 152Calhoun ME, Jucker M, Martin LJ, et al. Comparative evaluation of synaptophysin-based methods for quantification of synapses. J Neurocytol 1996; 25: 821-8.
- 153Phelps ME. PET: the merging of biology and imaging into molecular imaging. J Nucl Med 2000; 41: 661-81.
- 154James ML, Gambhir SS. A molecular imaging primer: modalities, imaging agents, and applications. Physiol Rev 2012; 92: 897-965.
- 155Bajjalieh SM, Frantz GD, Weimann JM, et al. Differential expression of synaptic vesicle protein 2 (SV2) isoforms. J Neurosci 1994; 14: 5223-35.
- 156Lynch BA, Lambeng N, Nocka K, et al. The synaptic vesicle protein SV2A is the binding site for the antiepileptic drug levetiracetam. Proc Natl Acad Sci USA 2004; 101: 9861-6.
- 157Mercier J, Archen L, Bollu V, et al. Discovery of heterocyclic nonacetamide synaptic vesicle protein 2A (SV2A) ligands with single-digit nanomolar potency: opening avenues towards the first SV2A positron emission tomography (PET) ligands. Chem Med Chem 2014; 9: 693-8.
- 158Cai Z, Li S, Matuskey D, et al. PET imaging of synaptic density: a new tool for investigation of neuropsychiatric diseases. Neurosci Lett 2019; 691: 44-50.
- 159Nabulsi NB, Mercier J, Holden D, et al. Synthesis and preclinical evaluation of 11C-UCB-J as a PET tracer for imaging the synaptic vesicle glycoprotein 2A in the brain. J Nucl Med 2016; 57: 777-84.
- 160Finnema SJ, Nabulsi NB, Eid T, et al. Imaging synaptic density in the living human brain. Sci Transl Med 2016; 8: 348-96.
- 161Warnock GI, Aerts J, Bahri MA, et al. Evaluation of 18F-UCB-H as a novel PET tracer for synaptic vesicle protein 2A in the brain. J Nucl Med 2014; 55: 1336-41.
- 162Cai H, Mangner TJ, Muzik O, et al. Radiosynthesis of (11)C-levetiracetam: a potential marker for PET imaging of SV2A expression. ACS Med Chem Lett 2014; 5: 1152-5.
- 163Estrada S, Lubberink M, Thibblin A, et al. [(11)C]UCB-A, a novel PET tracer for synaptic vesicle protein 2A. Nucl Med Biol 2016; 43: 325-32.
- 164Li S, Cai Z, Wu X, et al. Synthesis and in vivo evaluation of a novel PET radiotracer for imaging of synaptic vesicle glycoprotein 2A (SV2A) in nonhuman primates. ACS Chem Neurosci 2019; 10: 1544-54.
- 165Cai Z, Li S, Finnema S, et al. Imaging synaptic density with novel 18F-labeled radioligands for synaptic vesicle protein-2A (SV2A): synthesis and evaluation in nonhuman primates. J Nucl Med 2017; 58: 547.
- 166Kaufman AC, Salazar SV, Haas LT, et al. Fyn inhibition rescues established memory and synapse loss in Alzheimer mice. Ann Neurol 2015; 77: 953-71.
- 167Oppenheimer DR. The cervical cord in multiple sclerosis. Neuropathol Appl Neurobiol 1978; 4: 151-62.
- 168Gilmore CP, Bö L, Owens T, et al. Spinal cord gray matter demyelination in multiple sclerosis-a novel pattern of residual plaque morphology. Brain Pathol Zurich Switz 2006; 16: 202-8.
- 169Vogt J, Paul F, Aktas O, et al. Lower motor neuron loss in multiple sclerosis and experimental autoimmune encephalomyelitis. Ann Neurol 2009; 66: 310-22.
- 170Schirmer L, Albert M, Buss A, et al. Substantial early, but non-progressive neuronal loss in multiple sclerosis (MS) spinal cord. Ann Neurol 2009; 66: 698-704.
- 171Bergers E, Bot JCJ, van der Valk P, et al. Diffuse signal abnormalities in the spinal cord in multiple sclerosis: direct postmortem in situ magnetic resonance imaging correlated with in vitro high-resolution magnetic resonance imaging and histopathology. Ann Neurol 2002; 51: 652-6.
- 172Bergers E, Bot JCJ, De Groot CJA, et al. Axonal damage in the spinal cord of MS patients occurs largely independent of T2 MRI lesions. Neurology 2002; 59: 1766-71.
- 173Ganter P, Prince C, Esiri MM. Spinal cord axonal loss in multiple sclerosis: a post-mortem study. Neuropathol Appl Neurobiol 1999; 25: 459-67.
- 174DeLuca GC, Ebers GC, Esiri MM. Axonal loss in multiple sclerosis: a pathological survey of the corticospinal and sensory tracts. Brain 2004; 127: 1009-18.
- 175De Leener B, Lévy S, Dupont SM, et al. SCT: spinal cord toolbox, an open-source software for processing spinal cord MRI data. Neuroimage 2017; 145: 24-43.
- 176Yiannakas MC, Mustafa AM, De Leener B, et al. Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: application to multiple sclerosis. Neuroimage Clin 2016; 10: 71-7.
- 177Eden D, Gros C, Badji A, et al. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain 2019; 142: 633-46.
- 178Gros C, De Leener B, Badji A, et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage 2019; 184: 901-15.
- 179Dula AN, Pawate S, Dortch RD, et al. Magnetic resonance imaging of the cervical spinal cord in multiple sclerosis at 7T. Mult Scler 2016; 22: 320-8.
- 180Casserly C, Seyman EE, Alcaide-Leon P, et al. Spinal cord atrophy in multiple sclerosis: a systematic review and meta-analysis. J Neuroimaging 2018; 28: 556-86.
- 181By S, Smith AK, Dethrage LM, et al. Quantifying the impact of underlying measurement error on cervical spinal cord diffusion tensor imaging at 3T. J Magn Reson Imaging JMRI 2016; 44: 1608-18.
- 182By S, Xu J, Box BA, et al. Application and evaluation of NODDI in the cervical spinal cord of multiple sclerosis patients. Neuroimage Clin 2017; 15: 333-42.
- 183Grussu F, Schneider T, Zhang H, et al. Neurite orientation dispersion and density imaging of the healthy cervical spinal cord in vivo. Neuroimage 2015; 111: 590-601.
- 184By S, Xu J, Box BA, et al. Multi-compartmental diffusion characterization of the human cervical spinal cord in vivo using the spherical mean technique. NMR Biomed 2018; 31: e3894-4015.
- 185Smith AK, By S, Lyttle BD, et al. Evaluating single-point quantitative magnetization transfer in the cervical spinal cord: application to multiple sclerosis. Neuroimage Clin 2017; 16: 58-65.
- 186Ljungberg E, Vavasour I, Tam R, et al. Rapid myelin water imaging in human cervical spinal cord. Magn Reson Med 2017; 78: 1482-7.
- 187Laule C, Vavasour IM, Zhao Y, et al. Two-year study of cervical cord volume and myelin water in primary progressive multiple sclerosis. Mult Scler 2010; 16: 670-7.
- 188van Zijl PCM, Yadav NN. Chemical exchange saturation transfer (CEST): what is in a name and what isn't? Magn Reson Med 2011; 65: 927-48.
- 189By S, Barry RL, Smith AK, et al. Amide proton transfer CEST of the cervical spinal cord in multiple sclerosis patients at 3T. Magn Reson Med 2018; 79: 806-14.
- 190Stroman PW, Wheeler-Kingshott C, Bacon M, et al. The current state-of-the-art of spinal cord imaging: methods. Neuroimage 2014; 84: 1070-81.
- 191Barry RL, Smith SA, Dula AN, et al. Resting state functional connectivity in the human spinal cord. eLife 2014; 3:e02812.
- 192Eippert F, Kong Y, Winkler AM, et al. Investigating resting-state functional connectivity in the cervical spinal cord at 3T. Neuroimage 2017; 147: 589-601.
- 193Eippert F, Tracey I. The spinal cord is never at rest. eLife 2014; 3:e03811.
- 194Provencher SW. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR Biomed 2001; 14: 260-4
- 195Perone CS, Calabrese E, Cohen-Adad J. Spinal cord gray matter segmentation using deep dilated convolutions. Sci Rep 2018; 8: 5966-79.