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Müller HP, Abrahao A, Beaulieu C, Benatar M, Dionne A, Genge A, Frayne R, Graham SJ, Gibson S, Korngut L, Luk C, Welsh RC, Zinman L, Kassubek J, Kalra S. Temporal and spatial progression of microstructural cerebral degeneration in ALS: A multicentre longitudinal diffusion tensor imaging study. Neuroimage Clin 2024; 43:103633. [PMID: 38889523 PMCID: PMC11231599 DOI: 10.1016/j.nicl.2024.103633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 06/20/2024]
Abstract
OBJECTIVE The corticospinal tract (CST) reveals progressive microstructural alterations in ALS measurable by DTI. The aim of this study was to evaluate fractional anisotropy (FA) along the CST as a longitudinal marker of disease progression in ALS. METHODS The study cohort consisted of 114 patients with ALS and 110 healthy controls from the second prospective, longitudinal, multicentre study of the Canadian ALS Neuroimaging Consortium (CALSNIC-2). DTI and clinical data from a harmonized protocol across 7 centres were collected. Thirty-nine ALS patients and 61 controls completed baseline and two follow-up visits and were included for longitudinal analyses. Whole brain-based spatial statistics and hypothesis-guided tract-of-interest analyses were performed for cross-sectional and longitudinal analyses. RESULTS FA was reduced at baseline and longitudinally in the CST, mid-corpus callosum (CC), frontal lobe, and other ALS-related tracts, with alterations most evident in the CST and mid-CC. CST and pontine FA correlated with functional impairment (ALSFRS-R), upper motor neuron function, and clinical disease progression rate. Reduction in FA was largely located in the upper CST; however, the longitudinal decline was greatest in the lower CST. Effect sizes were dependent on region, resulting in study group sizes between 17 and 31 per group over a 9-month interval. Cross-sectional effect sizes were maximal in the upper CST; whereas, longitudinal effect sizes were maximal in mid-callosal tracts. CONCLUSIONS Progressive microstructural alterations in ALS are most prominent in the CST and CC. DTI can provide a biomarker of cerebral degeneration in ALS, with longitudinal changes in white matter demonstrable over a reasonable observation period, with a feasible number of participants, and within a multicentre framework.
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Affiliation(s)
| | - Agessandro Abrahao
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Michael Benatar
- Neuromuscular Division, Department of Neurology, University of Miami, Miami, FL, United States
| | - Annie Dionne
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, Quebec, Canada
| | - Angela Genge
- Department of Neurology, McGill University, Montreal, Quebec, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Simon J Graham
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Summer Gibson
- Neuromuscular Medicine Division, University of Utah, Salt Lake City, Utah, United States
| | - Lawrence Korngut
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Collin Luk
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada; Divison of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Robert C Welsh
- Department of Psychiatry and Biobehavioral Science, UCLA, Los Angeles, CA, United States
| | - Lorne Zinman
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany; German Centre of Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Sanjay Kalra
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Divison of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada.
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2
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Labounek R, Bondy MT, Paulson AL, Bédard S, Abramovic M, Alonso-Ortiz E, Atcheson NT, Barlow LR, Barry RL, Barth M, Battiston M, Büchel C, Budde MD, Callot V, Combes A, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak AV, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Gandini Wheeler-Kingshott CAM, Germani G, Gilbert G, Giove F, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers JM, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Laganà MM, Laule C, Law CSW, Leutritz T, Liu Y, Llufriu S, Mackey S, Martin AR, Martinez-Heras E, Mattera L, O’Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley GW, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J, Cohen-Adad J, Lenglet C, Nestrašil I. Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591421. [PMID: 38746371 PMCID: PMC11092490 DOI: 10.1101/2024.04.29.591421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.
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Affiliation(s)
- René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Monica T. Bondy
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Amy L. Paulson
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - Nicole T Atcheson
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | - Laura R. Barlow
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, Massachusetts, USA
| | - Markus Barth
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Clement J. Zablocki Veteran’s Affairs Medical Center, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna Combes
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | | | - Marek Dostál
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam V. Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Jürgen Finsterbusch
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Claudia A. M. Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - GianCarlo Germani
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Department of Neurology, University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Haleh Karbasforoushan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
| | - Ali Khatibi
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Joo-won Kim
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Nawal Kinany
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Science, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Petr Kudlička
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
- First Department of Neurology, St. Anne’s University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Nyoman D. Kurniawan
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | | | | | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, Canada
| | | | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Allan R. Martin
- Department of Neurological Surgery, University of California, Davis, CA, USA
| | - Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Geneva, Genève, Switzerland
| | - Kristin P. O’Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Todd B. Parrish
- Department of Radiology, Northwestern University, Chicago, IL 60611, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
- Centre for Medical Image Computing, University College London, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Marc J. Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, Australia
| | - Rebecca S. Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Giovanni Savini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20072, Pieve Emanuele (MI), Italy
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089, Rozzano (MI), Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Alan C. Seifert
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alex K. Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN USA
| | - Zachary A. Smith
- Department of Neurosurgery, University of Oklahoma, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Yuichi Suzuki
- The University of Tokyo Hospital, Radiology Center, Tokyo, Japan
| | - George W Tackley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
| | - Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Department of Neurosurgery, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Marios C. Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Kenneth A. Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
| | - Richard G. Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
- Department of Neurosciences, Imaging, and Clinical Sciences, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
| | - Patrik O. Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Igor Nestrašil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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Branco LDMT, Rezende TJR, Reis F, França MC. Advanced Structural Magnetic Resonance Imaging of the Spinal Cord: Technical Aspects and Clinical Use. Semin Ultrasound CT MR 2023; 44:464-468. [PMID: 37581877 DOI: 10.1053/j.sult.2023.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
For a long time, technical obstacles have hampered the acquisition of high-resolution images and the development of reliable processing protocols for spinal cord (SC) MRI. Fortunately, this scenario has changed in the past 5-10 years, due to hardware and software improvements. Nowadays, with advanced protocols, SC MRI is considered a useful tool for several inherited and acquired neurologic diseases, not only for diagnosis approach but also for pathophysiological unraveling and as a biomarker for disease monitoring and clinical trials. In this review, we address advanced SC MRI sequences for macrostructural and microstructural evaluation, useful semiautomatic and automatic processing tools and clinical applications on several neurologic conditions such as hereditary cerebellar ataxia, hereditary spastic paraplegia, motor neuron diseases and multiple sclerosis.
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Affiliation(s)
- Lucas de M T Branco
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Thiago J R Rezende
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Fabiano Reis
- Department of Anesthesiology, Oncology and Radiology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Marcondes C França
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil.
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Rangaprakash D, Barry RL, Deshpande G. The confound of hemodynamic response function variability in human resting-state functional MRI studies. Front Neurosci 2023; 17:934138. [PMID: 37521709 PMCID: PMC10375034 DOI: 10.3389/fnins.2023.934138] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 04/07/2023] [Indexed: 08/01/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.
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Affiliation(s)
- D. Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychological Sciences, Auburn University, Auburn, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Birmingham, AL, United States
- Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
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Arnold FJ, Nguyen AD, Bedlack RS, Bennett CL, La Spada AR. Intercellular transmission of pathogenic proteins in ALS: Exploring the pathogenic wave. Neurobiol Dis 2023:106218. [PMID: 37394036 DOI: 10.1016/j.nbd.2023.106218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 06/16/2023] [Accepted: 06/28/2023] [Indexed: 07/04/2023] Open
Abstract
In patients with amyotrophic lateral sclerosis (ALS), disease symptoms and pathology typically spread in a predictable spatiotemporal pattern beginning at a focal site of onset and progressing along defined neuroanatomical tracts. Like other neurodegenerative diseases, ALS is characterized by the presence of protein aggregates in postmortem patient tissue. Cytoplasmic, ubiquitin-positive aggregates of TDP-43 are observed in approximately 97% of sporadic and familial ALS patients, while SOD1 inclusions are likely specific to cases of SOD1-ALS. Additionally, the most common subtype of familial ALS, caused by a hexanucleotide repeat expansion in the first intron of the C9orf72 gene (C9-ALS), is further characterized by the presence of aggregated dipeptide repeat proteins (DPRs). As we will describe, cell-to-cell propagation of these pathological proteins tightly correlates with the contiguous spread of disease. While TDP-43 and SOD1 are capable of seeding protein misfolding and aggregation in a prion-like manner, C9orf72 DPRs appear to induce (and transmit) a 'disease state' more generally. Multiple mechanisms of intercellular transport have been described for all of these proteins, including anterograde and retrograde axonal transport, extracellular vesicle secretion, and macropinocytosis. In addition to neuron-to-neuron transmission, transmission of pathological proteins occurs between neurons and glia. Given that the spread of ALS disease pathology corresponds with the spread of symptoms in patients, the various mechanisms by which ALS-associated protein aggregates propagate through the central nervous system should be closely examined.
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Affiliation(s)
- F J Arnold
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| | - A D Nguyen
- Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| | - R S Bedlack
- Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| | - C L Bennett
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA.
| | - A R La Spada
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA; Departments of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA; Department of Neurology, University of California, Irvine, Irvine, CA, USA; Department of Biological Chemistry, University of California, Irvine, Irvine, CA, USA; UCI Center for Neurotherapeutics, University of California, Irvine, Irvine, CA 92697, USA.
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6
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Nigri A, Dalla Bella E, Ferraro S, Medina Carrion JP, Demichelis G, Bersano E, Consonni M, Bischof A, Stanziano M, Palermo S, Lauria G, Bruzzone MG, Papinutto N. Cervical spinal cord atrophy in amyotrophic lateral sclerosis across disease stages. Ann Clin Transl Neurol 2023; 10:213-224. [PMID: 36599092 PMCID: PMC9930423 DOI: 10.1002/acn3.51712] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/11/2022] [Accepted: 11/21/2022] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE Spinal cord degeneration is a hallmark of amyotrophic lateral sclerosis. The assessment of gray matter and white matter cervical spinal cord atrophy across clinical stages defined using the King's staging system could advance the understanding of amyotrophic lateral sclerosis progression. METHODS We assessed the in vivo spatial pattern of gray and white matter atrophy along cervical spinal cord (C2 to C6 segments) using 2D phase-sensitive inversion recovery imaging in a cohort of 44 amyotrophic lateral sclerosis patients, evaluating its change across the King's stages and the correlation with disability scored by the amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) and disease duration. A mathematical model inferring the potential onset of cervical gray matter atrophy was developed. RESULTS In amyotrophic lateral sclerosis patients at King's stage 1, significant cervical spinal cord alterations were mainly identified in gray matter, whereas they involved both gray and white matter in patients at King's stage ≥ 2. Gray and white matter areas correlated with clinical disability at all cervical segments. C3-C4 level was the segment showing early gray matter atrophy starting about 7 to 20 months before symptom onset according to our model. INTERPRETATION Our findings suggest that cervical spinal cord atrophy spreads from gray to white matter across King's stages in amyotrophic lateral sclerosis, making spinal cord magnetic resonance imaging an in vivo assessment tool to measure the progression of the disease.
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Affiliation(s)
- Anna Nigri
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Eleonora Dalla Bella
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Stefania Ferraro
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,School of Life Science and Technology, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | - Greta Demichelis
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Enrica Bersano
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | - Monica Consonni
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Antje Bischof
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA,Department of Neurology with Institute for Translational NeurologyUniversity Hospital MünsterMünsterGermany
| | - Mario Stanziano
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
| | - Sara Palermo
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Giuseppe Lauria
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | | | - Nico Papinutto
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
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7
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Notturno F, Croce P, Ornello R, Sacco S, Zappasodi F. Yield of EEG features as markers of disease severity in amyotrophic lateral sclerosis: a pilot study. Amyotroph Lateral Scler Frontotemporal Degener 2022; 24:295-303. [PMID: 37078278 DOI: 10.1080/21678421.2022.2152696] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVE To clarify the role of electroencephalography (EEG) as a promising marker of severity in amyotrophic lateral sclerosis (ALS). We characterized the brain spatio-temporal patterns activity at rest by means of both spectral band powers and EEG microstates and correlated these features with clinical scores. METHODS Eyes closed EEG was acquired in 15 patients with ALS and spectral band power was calculated in frequency bands, defined on the basis of individual alpha frequency (IAF): delta-theta band (1-7 Hz); low alpha (IAF - 2 Hz - IAF); high alpha (IAF - IAF + 2 Hz); beta (13 - 25 Hz). EEG microstate metrics (duration, occurrence, and coverage) were also evaluated. Spectral band powers and microstate metrics were correlated with several clinical scores of disabilities and disease progression. As a control group, 15 healthy volunteers were enrolled. RESULTS The beta-band power in motor/frontal regions was higher in patients with higher disease burden, negatively correlated with clinical severity scores and positively correlated with disease progression. Overall microstate duration was longer and microstate occurrence was lower in patients than in controls. Longer duration was correlated with a worse clinical status. CONCLUSIONS Our results showed that beta-band power and microstate metrics may be good candidates of disease severity in ALS. Increased beta and longer microstate duration in clinically worse patients suggest a possible impairment of both motor and non-motor network activities to fast modify their status. This can be interpreted as an attempt in ALS patients to compensate the disability but resulting in an ineffective and probably maladaptive behavior.
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Affiliation(s)
| | - Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, University “Gabriele d’Annunzio” of Chieti-Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Raffaele Ornello
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy, and
| | - Simona Sacco
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy, and
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, University “Gabriele d’Annunzio” of Chieti-Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
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8
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Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness. Neuroimage Clin 2022; 36:103162. [PMID: 36067613 PMCID: PMC9460837 DOI: 10.1016/j.nicl.2022.103162] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 07/11/2022] [Accepted: 08/18/2022] [Indexed: 12/14/2022]
Abstract
There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.
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9
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Colvin LE, Foster ZW, Stein TD, Thakore-James M, Salajegheh MK, Carr K, Spencer KR, Rauf NA, Adams L, Averill JG, Walker SE, Robey I, Alvarez VE, Huber BR, McKee AC, Kowall NW, Brady CB. Utility of the ALSFRS-R for predicting ALS and comorbid disease neuropathology: The Veterans Affairs Biorepository Brain Bank. Muscle Nerve 2022; 66:167-174. [PMID: 35585776 PMCID: PMC9308705 DOI: 10.1002/mus.27635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 05/09/2022] [Accepted: 05/13/2022] [Indexed: 01/03/2023]
Abstract
INTRODUCTION/AIMS The amyotrophic lateral sclerosis (ALS) functional rating scale-revised (ALSFRS-R) is commonly used to track ALS disease progression; however, there are gaps in the literature regarding the extent to which the ALSFRS-R relates to underlying central nervous system (CNS) pathology. The current study explored the association between ALSFRS-R (total and subdomain) scores and postmortem neuropathology (both ALS-specific and comorbid disease). METHODS Within our sample of 93 military veterans with autopsy-confirmed ALS, we utilized hierarchical cluster analysis (HCA) to identify discrete profiles of motor dysfunction based on ALSFRS-R subdomain scores. We examined whether emergent clusters were associated with neuropathology. Separate analyses of variance and covariance with post-hoc comparisons were performed to examine relevant cluster differences. RESULTS Analyses revealed significant correlations between ALSFRS-R total and subdomain scores with some, but not all, neuropathological variables. The HCA illustrated three groups: Cluster 1-predominantly diffuse functional impairment; Cluster 2-spared respiratory/bulbar and impaired motor function; and Cluster 3-spared bulbar and impaired respiratory, and fine and gross motor function. Individuals in Cluster 1 (and to a lesser degree, Cluster 3) exhibited greater accumulation of ALS-specific neuropathology and less comorbid neuropathology than those in Cluster 2. DISCUSSION These results suggest that discrete patterns of motor dysfunction based on ALSFRS-R subdomain scores are related to postmortem neuropathology. Findings support use of ALSFRS-R subdomain scores to capture the heterogeneity of clinical presentation and disease progression in ALS, and may assist researchers in identifying endophenotypes for separate assessment in clinical trials.
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Affiliation(s)
| | | | - Thor D. Stein
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA
| | - Manisha Thakore-James
- VA Boston Healthcare System, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - M. Kian Salajegheh
- VA Boston Healthcare System, Boston, MA
- Harvard Medical School, Boston, MA
- Brigham and Women’s Hospital
| | | | | | | | | | | | | | - Ian Robey
- Southern Arizona VA Healthcare System, Tucson, Arizona
| | - Victor E. Alvarez
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
| | - Bertrand R. Huber
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
| | - Ann C. McKee
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA
| | - Neil W. Kowall
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
| | - Christopher B. Brady
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Harvard Medical School, Boston, MA
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10
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Ishaque A, Ta D, Khan M, Zinman L, Korngut L, Genge A, Dionne A, Briemberg H, Luk C, Yang YH, Beaulieu C, Emery D, Eurich DT, Frayne R, Graham S, Wilman A, Dupré N, Kalra S. Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis. Hum Brain Mapp 2021; 43:1519-1534. [PMID: 34908212 PMCID: PMC8886653 DOI: 10.1002/hbm.25738] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 11/22/2021] [Accepted: 11/25/2021] [Indexed: 01/17/2023] Open
Abstract
Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T0 ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T0 and Tmax (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at Tmax than at T0 . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.
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Affiliation(s)
- Abdullah Ishaque
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Daniel Ta
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Muhammad Khan
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Lorne Zinman
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
| | - Lawrence Korngut
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Angela Genge
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, Montreal, Canada
| | - Annie Dionne
- Département des Sciences Neurologiques, Hôpital de l'Enfant-Jésus, CHU de Québec, Quebec City, Canada
| | - Hannah Briemberg
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Collin Luk
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Yee-Hong Yang
- Department of Computing Science, University of Alberta, Edmonton
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Derek Emery
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada
| | - Dean T Eurich
- School of Public Health, University of Alberta, Edmonton, Canada
| | - Richard Frayne
- Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Canada
| | - Simon Graham
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Alan Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Nicolas Dupré
- Neuroscience Axis, CHU de Québec, Université Laval, Quebec City, Canada.,Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, Canada
| | - Sanjay Kalra
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.,Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
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11
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Kocar TD, Müller HP, Ludolph AC, Kassubek J. Feature selection from magnetic resonance imaging data in ALS: a systematic review. Ther Adv Chronic Dis 2021; 12:20406223211051002. [PMID: 34729157 PMCID: PMC8521429 DOI: 10.1177/20406223211051002] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/15/2021] [Indexed: 12/23/2022] Open
Abstract
Background: With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection. Methods: We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported. Results: Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS. Conclusions: These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.
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Affiliation(s)
- Thomas D Kocar
- Department of Neurology, University of Ulm, Ulm, Germany
| | | | - Albert C Ludolph
- Department of Neurology, University of Ulm, Ulm, Germany Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Oberer Eselsberg 45, 89081 Ulm, Germany
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12
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Cohen-Adad J, Alonso-Ortiz E, Abramovic M, Arneitz C, Atcheson N, Barlow L, Barry RL, Barth M, Battiston M, Büchel C, Budde M, Callot V, Combes AJE, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak A, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Wheeler-Kingshott CAMG, Germani G, Gilbert G, Giove F, Gros C, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers J, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Labounek R, Laganà MM, Laule C, Law CS, Lenglet C, Leutritz T, Liu Y, Llufriu S, Mackey S, Martinez-Heras E, Mattera L, Nestrasil I, O'Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley G, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J. Generic acquisition protocol for quantitative MRI of the spinal cord. Nat Protoc 2021; 16:4611-4632. [PMID: 34400839 PMCID: PMC8811488 DOI: 10.1038/s41596-021-00588-0] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 06/10/2021] [Indexed: 02/08/2023]
Abstract
Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.
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Affiliation(s)
- Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada.
- Mila-Quebec AI Institute, Montreal, Quebec, Canada.
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Carina Arneitz
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Nicole Atcheson
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Laura Barlow
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Markus Barth
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Christian Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin De Leener
- Department of Computer and Software Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- CHU Sainte-Justine Research Centre, Montreal, Quebec, Canada
| | - Maxime Descoteaux
- Centre de Recherche CHUS, CIMS, Sherbrooke, Quebec, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | | | - Marek Dostál
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Falk Eippert
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Karla R Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Kevin S Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Giancarlo Germani
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Francesco Grussu
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | - Haleh Karbasforoushan
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA
| | - Miloš Keřkovský
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Ali Khatibi
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Joo-Won Kim
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nawal Kinany
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Petr Kudlička
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Nyoman D Kurniawan
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Slawomir Kusmia
- CUBRIC, Cardiff University, Wales, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
| | - René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Departments of Neurology and Biomedical Engineering, University Hospital Olomouc, Olomouc, Czech Republic
| | | | - Cornelia Laule
- Departments of Radiology, Pathology & Laboratory Medicine, Physics & Astronomy; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - Christine S Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Sara Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eloy Martinez-Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Genève, Geneva, Switzerland
| | - Igor Nestrasil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Todd B Parrish
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- E-health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Àlex Rovira
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Marc J Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Rebecca S Samson
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Giovanni Savini
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alan C Seifert
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alex K Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zachary A Smith
- University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Yuichi Suzuki
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | | | - Alexandra Tinnermann
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University and University Hospital Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Kenneth A Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Richard G Wise
- CUBRIC, Cardiff University, Wales, UK
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Patrik O Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Abstract
OBJECTIVE Advanced neuroimaging techniques may offer the potential to monitor disease progression in amyotrophic lateral sclerosis (ALS), a neurodegenerative, multisystem disease that still lacks therapeutic outcome measures. We aim to investigate longitudinal functional and structural magnetic resonance imaging (MRI) changes in a cohort of patients with ALS monitored for one year after diagnosis. METHODS Resting state functional MRI, diffusion tensor imaging (DTI), and voxel-based morphometry analyses were performed in 22 patients with ALS examined by six-monthly MRI scans over one year. RESULTS During the follow-up period, patients with ALS showed reduced functional connectivity only in some extramotor areas, such as the middle temporal gyrus in the left frontoparietal network after six months and in the left middle frontal gyrus in the default mode network after one year without showing longitudinal changes of cognitive functions. Moreover, after six months, we reported in the ALS group a decreased fractional anisotropy (P = .003, Bonferroni corrected) in the right uncinate fasciculus. Conversely, we did not reveal significant longitudinal changes of functional connectivity in the sensorimotor network, as well as of gray matter (GM) atrophy or of DTI metrics in motor areas, although clinical measures of motor disability showed significant decline throughout the three time points. CONCLUSION Our findings highlighted that progressive impairment of extramotor frontotemporal networks may precede the appearance of executive and language dysfunctions and GM changes in ALS. Functional connectivity changes in cognitive resting state networks might represent candidate radiological markers of disease progression.
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Steinbach R, Prell T, Gaur N, Roediger A, Gaser C, Mayer TE, Witte OW, Grosskreutz J. Patterns of grey and white matter changes differ between bulbar and limb onset amyotrophic lateral sclerosis. Neuroimage Clin 2021; 30:102674. [PMID: 33901988 PMCID: PMC8099783 DOI: 10.1016/j.nicl.2021.102674] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 04/09/2021] [Accepted: 04/10/2021] [Indexed: 12/18/2022]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease that is characterized by a high heterogeneity in patients' disease course. Patients with bulbar onset of symptoms (b-ALS) have a poorer prognosis than patients with limb onset (l-ALS). However, neuroimaging correlates of the assumed biological difference between b-ALS and l-ALS may have been obfuscated by patients' diversity in the disease course. We conducted Voxel-Based-Morphometry (VBM) and Tract-Based-Spatial-Statistics (TBSS) in a group of 76 ALS patients without clinically relevant cognitive deficits. The subgroups of 26 b-ALS and 52 l-ALS patients did not differ in terms of disease Phase or disease aggressiveness according to the D50 progression model. VBM analyses showed widespread ALS-related changes in grey and white matter, that were more pronounced for b-ALS. TBSS analyses revealed that b-ALS was predominantly characterized by frontal fractional anisotropy decreases. This demonstrates a higher degree of neurodegenerative burden for the group of b-ALS patients in comparison to l-ALS. Correspondingly, higher bulbar symptom burden was associated with right-temporal and inferior-frontal grey matter density decreases as well as fractional anisotropy decreases in inter-hemispheric and long association tracts. Contrasts between patients in Phase I and Phase II further revealed that b-ALS was characterized by an early cortical pathology and showed a spread only outside primary motor regions to frontal and temporal areas. In contrast, l-ALS showed ongoing structural integrity loss within primary motor-regions until Phase II. We therefore provide a strong rationale to treat both onset types of disease separately in ALS studies.
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Affiliation(s)
- Robert Steinbach
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany.
| | - Tino Prell
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany; Center for Healthy Ageing, Jena University Hospital, Jena
| | - Nayana Gaur
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany
| | | | - Christian Gaser
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany; Center for Healthy Ageing, Jena University Hospital, Jena; Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Thomas E Mayer
- Department of Neuroradiology, Jena University Hospital, Jena, Germany
| | - Otto W Witte
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany; Center for Healthy Ageing, Jena University Hospital, Jena
| | - Julian Grosskreutz
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany; Center for Healthy Ageing, Jena University Hospital, Jena
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15
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Sassani M, Alix JJ, McDermott CJ, Baster K, Hoggard N, Wild JM, Mortiboys HJ, Shaw PJ, Wilkinson ID, Jenkins TM. Magnetic resonance spectroscopy reveals mitochondrial dysfunction in amyotrophic lateral sclerosis. Brain 2021; 143:3603-3618. [PMID: 33439988 DOI: 10.1093/brain/awaa340] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 07/16/2020] [Accepted: 08/08/2020] [Indexed: 12/16/2022] Open
Abstract
Mitochondrial dysfunction is postulated to be central to amyotrophic lateral sclerosis (ALS) pathophysiology. Evidence comes primarily from disease models and conclusive data to support bioenergetic dysfunction in vivo in patients is currently lacking. This study is the first to assess mitochondrial dysfunction in brain and muscle in individuals living with ALS using 31P-magnetic resonance spectroscopy (MRS), the modality of choice to assess energy metabolism in vivo. We recruited 20 patients and 10 healthy age and gender-matched control subjects in this cross-sectional clinico-radiological study. 31P-MRS was acquired from cerebral motor regions and from tibialis anterior during rest and exercise. Bioenergetic parameter estimates were derived including: ATP, phosphocreatine, inorganic phosphate, adenosine diphosphate, Gibbs free energy of ATP hydrolysis (ΔGATP), phosphomonoesters, phosphodiesters, pH, free magnesium concentration, and muscle dynamic recovery constants. Linear regression was used to test for associations between brain data and clinical parameters (revised amyotrophic functional rating scale, slow vital capacity, and upper motor neuron score) and between muscle data and clinico-neurophysiological measures (motor unit number and size indices, force of contraction, and speed of walking). Evidence for primary dysfunction of mitochondrial oxidative phosphorylation was detected in the brainstem where ΔGATP and phosphocreatine were reduced. Alterations were also detected in skeletal muscle in patients where resting inorganic phosphate, pH, and phosphomonoesters were increased, whereas resting ΔGATP, magnesium, and dynamic phosphocreatine to inorganic phosphate recovery were decreased. Phosphocreatine in brainstem correlated with respiratory dysfunction and disability; in muscle, energy metabolites correlated with motor unit number index, muscle power, and speed of walking. This study provides in vivo evidence for bioenergetic dysfunction in ALS in brain and skeletal muscle, which appears clinically and electrophysiologically relevant. 31P-MRS represents a promising technique to assess the pathophysiology of mitochondrial function in vivo in ALS and a potential tool for future clinical trials targeting bioenergetic dysfunction.
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Affiliation(s)
- Matilde Sassani
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - James J Alix
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Christopher J McDermott
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Kathleen Baster
- Statistical Service Unit, University of Sheffield, Sheffield, UK
| | - Nigel Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Jim M Wild
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Heather J Mortiboys
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Iain D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Thomas M Jenkins
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
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Steinbach R, Gaur N, Roediger A, Mayer TE, Witte OW, Prell T, Grosskreutz J. Disease aggressiveness signatures of amyotrophic lateral sclerosis in white matter tracts revealed by the D50 disease progression model. Hum Brain Mapp 2021; 42:737-752. [PMID: 33103324 PMCID: PMC7814763 DOI: 10.1002/hbm.25258] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 12/11/2022] Open
Abstract
Numerous neuroimaging studies in amyotrophic lateral sclerosis (ALS) have reported links between structural changes and clinical data; however phenotypic and disease course heterogeneity have occluded robust associations. The present study used the novel D50 model, which distinguishes between disease accumulation and aggressiveness, to probe correlations with measures of diffusion tensor imaging (DTI). DTI scans of 145 ALS patients and 69 controls were analyzed using tract-based-spatial-statistics of fractional anisotropy (FA), mean- (MD), radial (RD), and axial diffusivity (AD) maps. Intergroup contrasts were calculated between patients and controls, and between ALS subgroups: based on (a) the individual disease covered (Phase I vs. II) or b) patients' disease aggressiveness (D50 value). Regression analyses were used to probe correlations with model-derived parameters. Case-control comparisons revealed widespread ALS-related white matter pathology with decreased FA and increased MD/RD. These affected pathways showed also correlations with the accumulated disease for increased MD/RD, driven by the subgroup of Phase I patients. No significant differences were noted between patients in Phase I and II for any of the contrasts. Patients with high disease aggressiveness (D50 < 30 months) displayed increased AD/MD in bifrontal and biparietal pathways, which was corroborated by significant voxel-wise regressions with D50. Application of the D50 model revealed associations between DTI measures and ALS pathology in Phase I, representing individual disease accumulation early in disease. Patients' overall disease aggressiveness correlated robustly with the extent of DTI changes. We recommend the D50 model for studies developing/validating neuroimaging or other biomarkers for ALS.
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Affiliation(s)
- Robert Steinbach
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
| | - Nayana Gaur
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
| | | | - Thomas E. Mayer
- Department of NeuroradiologyJena University HospitalJenaGermany
| | - Otto W. Witte
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
- Center for Healthy AgeingJena University HospitalJenaGermany
| | - Tino Prell
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
- Center for Healthy AgeingJena University HospitalJenaGermany
| | - Julian Grosskreutz
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
- Center for Healthy AgeingJena University HospitalJenaGermany
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17
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Trojsi F, Di Nardo F, Siciliano M, Caiazzo G, Passaniti C, D'Alvano G, Ricciardi D, Russo A, Bisecco A, Lavorgna L, Bonavita S, Cirillo M, Esposito F, Tedeschi G. Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study. Amyotroph Lateral Scler Frontotemporal Degener 2020; 22:117-126. [PMID: 32885698 DOI: 10.1080/21678421.2020.1813306] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE Advanced neuroimaging techniques may offer the potential to monitor disease spreading in amyotrophic lateral sclerosis (ALS). We aim to investigate brain functional and structural magnetic resonance imaging (MRI) changes in a cohort of ALS patients, examined at diagnosis and clinically monitored over 18 months, in order to early discriminate fast progressors (FPs) from slow progressors (SPs). Methods: Resting state functional MRI (RS-fMRI), diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) analyses were performed at baseline in 54 patients with ALS and 22 HCs. ALS patients were classified a posteriori into FPs (n = 25) and SPs (n = 29) based on changes in Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score from baseline to the 18-month assessment (ΔALSFRS-R), applying a k-means clustering algorithm. Results: At diagnosis, when compared to HCs, ALS patients showed reduced functional connectivity in both motor and extra-motor networks. When compared to SPs, at baseline, FPs showed decreased function connectivity in paracentral lobule (sensorimotor network), precuneus (in the default mode network), middle frontal gyri (frontoparietal networks) and increased functional connectivity in insular cortices (salience network). Structural analyses did not reveal significant differences in gray and white matter damage by comparing FPs to SPs. Receiver operating characteristic (ROC) curve analysis showed that functional connectivity increase in the left insula at baseline best discriminated FPs and SPs (area under the curve 78%). Conclusions: Impairment of extra-motor networks may appear early in ALS patients with faster disease progression, suggesting that a more widespread functional connectivity damage may be an indicator of poorer prognosis.
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Affiliation(s)
- Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Federica Di Nardo
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Mattia Siciliano
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy.,Department of Psychology, Università degli Studi della Campania "Luigi Vanvitelli", Caserta, Italy, and
| | - Giuseppina Caiazzo
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Carla Passaniti
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy.,Department of Psychology, Università degli Studi della Campania "Luigi Vanvitelli", Caserta, Italy, and
| | - Giulia D'Alvano
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Dario Ricciardi
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Antonio Russo
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Luigi Lavorgna
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Mario Cirillo
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Fabrizio Esposito
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Italy
| | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences; MRI Research Center SUN-FISM, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
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18
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Consonni M, Dalla Bella E, Contarino VE, Bersano E, Lauria G. Cortical thinning trajectories across disease stages and cognitive impairment in amyotrophic lateral sclerosis. Cortex 2020; 131:284-294. [PMID: 32811660 DOI: 10.1016/j.cortex.2020.07.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 05/12/2020] [Accepted: 07/16/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND Cortical neuron degenerative process underlying upper motor neuron involvement in amyotrophic lateral sclerosis (ALS) spreads to extra-motor regions as disease progresses. This is associated with cognitive and behavioural worsening in more severe disease stages. However, the clinical variability of ALS patients might reflect different cortical involvement in extra-motor areas. OBJECTIVES To investigate cortical thinning across disease stages in ALS patients accounting for their cognitive/behavioural impairment. METHODS Thirty-six ALS patients (17 with cognitive/behavioural impairment, ALSimp) and 26 healthy controls underwent structural 3T magnetic resonance imaging. Cortical thickness was measured with a region-wise approach. The King's Clinical Staging System was used to determine disease stages. The Jonckheere-Terpstra test tested for trends in cortical thinning and cognitive involvement across disease stages. RESULTS Significant trends toward cortical atrophy across disease stages were found in bilateral frontal and cingular cortex, left temporal gyrus and right occipital gyrus of ALS patients, consistently with cognitive impairment in phonemic fluency, language, verbal episodic memory and social cognition. Sub-group analyses revealed that ALSimp had specific thinning in the right fronto-temporal insular cortex related to more pronounced cognitive involvement. CONCLUSION Looking at ALS patients irrespective of their cognitive phenotype, motor and extra-motor cortical involvement is consistent with neuropathological studies of disease dissemination. Segregating patients according to their cognitive status, a distinctive trajectory of cortical thinning emerged for ALSimp patients, suggesting a specific course distinct to that of the classic ALS phenotype.
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Affiliation(s)
- Monica Consonni
- 3rd Neurology Unit and Motor Neuron Diseases Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Via Celoria 11, 20133, Milan, Italy
| | - Eleonora Dalla Bella
- 3rd Neurology Unit and Motor Neuron Diseases Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Via Celoria 11, 20133, Milan, Italy
| | - Valeria Elisa Contarino
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 28, 20122, Milano, Italy
| | - Enrica Bersano
- 3rd Neurology Unit and Motor Neuron Diseases Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Via Celoria 11, 20133, Milan, Italy
| | - Giuseppe Lauria
- 3rd Neurology Unit and Motor Neuron Diseases Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Via Celoria 11, 20133, Milan, Italy; Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Via G.B. Grassi 74, 20157, Milan, Italy.
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19
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Kalra S, Müller HP, Ishaque A, Zinman L, Korngut L, Genge A, Beaulieu C, Frayne R, Graham SJ, Kassubek J. A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS. Neurology 2020; 95:e943-e952. [PMID: 32646955 DOI: 10.1212/wnl.0000000000010235] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 02/17/2020] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS). METHODS Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center. RESULTS Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe. CONCLUSIONS Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS. CLINICALTRIALSGOV IDENTIFIER NCT02405182.
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Affiliation(s)
- Sanjay Kalra
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada.
| | - Hans-Peter Müller
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Abdullah Ishaque
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Lorne Zinman
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Lawrence Korngut
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Angela Genge
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Christian Beaulieu
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Richard Frayne
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Simon J Graham
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Jan Kassubek
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
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van de Stadt SIW, van Ballegoij WJC, Labounek R, Huffnagel IC, Kemp S, Nestrasil I, Engelen M. Spinal cord atrophy as a measure of severity of myelopathy in adrenoleukodystrophy. J Inherit Metab Dis 2020; 43:852-860. [PMID: 32077106 PMCID: PMC7383492 DOI: 10.1002/jimd.12226] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 02/13/2020] [Accepted: 02/17/2020] [Indexed: 12/13/2022]
Abstract
All men and most women with X-linked adrenoleukodystrophy (ALD) develop myelopathy in adulthood. As clinical trials with new potential disease-modifying therapies are emerging, sensitive outcome measures for quantifying myelopathy are needed. This prospective cohort study evaluated spinal cord size (cross-sectional area - CSA) and shape (eccentricity) as potential new quantitative outcome measures for myelopathy in ALD. Seventy-four baseline magnetic resonance imaging (MRI) scans, acquired in 42 male ALD patients and 32 age-matched healthy controls, and 26 follow-up scans of ALD patients were included in the study. We used routine T1 -weighted MRI sequences to measure mean CSA, eccentricity, right-left and anteroposterior diameters in the cervical spinal cord. We compared MRI measurements between groups and correlated CSA with clinical outcome measures of disease severity. Longitudinally, we compared MRI measurements between baseline and 1-year follow-up. CSA was significantly smaller in patients compared to controls on all measured spinal cord levels (P < .001). The difference was completely explained by the effect of the symptomatic subgroup. Furthermore, the spinal cord showed flattening (higher eccentricity and smaller anteroposterior diameters) in patients. CSA correlated strongly with all clinical measures of severity of myelopathy. There was no detectable change in CSA after 1-year follow-up. The cervical spinal cord in symptomatic ALD patients is smaller and flattened compared to controls, possibly due to atrophy of the dorsal columns. CSA is a reliable marker of disease severity and can be a valuable outcome measure in long-term follow-up studies in ALD. SYNOPSIS: A prospective cohort study in 42 adrenoleukodystrophy (ALD) patients and 32 controls demonstrated that the spinal cord cross-sectional area of patients is smaller compared to healthy controls and correlates with severity of myelopathy in patients, hence it could be valuable as a much needed surrogate outcome measure.
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Affiliation(s)
- Stephanie I. W. van de Stadt
- Department of Pediatric NeurologyEmma Children's Hospital, Amsterdam University Medical CentersAmsterdamThe Netherlands
| | - Wouter J. C. van Ballegoij
- Department of Pediatric NeurologyEmma Children's Hospital, Amsterdam University Medical CentersAmsterdamThe Netherlands
| | - René Labounek
- Division of Clinical Behavioral Neuroscience, Department of PediatricsUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Irene C. Huffnagel
- Department of Pediatric NeurologyEmma Children's Hospital, Amsterdam University Medical CentersAmsterdamThe Netherlands
| | - Stephan Kemp
- Laboratory Genetic Metabolic DiseasesAmsterdam University Medical CentersAmsterdamThe Netherlands
| | - Igor Nestrasil
- Division of Clinical Behavioral Neuroscience, Department of PediatricsUniversity of MinnesotaMinneapolisMinnesotaUSA
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Marc Engelen
- Department of Pediatric NeurologyEmma Children's Hospital, Amsterdam University Medical CentersAmsterdamThe Netherlands
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21
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Structural MRI outcomes and predictors of disease progression in amyotrophic lateral sclerosis. NEUROIMAGE-CLINICAL 2020; 27:102315. [PMID: 32593977 PMCID: PMC7327879 DOI: 10.1016/j.nicl.2020.102315] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 06/10/2020] [Accepted: 06/11/2020] [Indexed: 11/20/2022]
Abstract
Serial diffusion tensor (DT) MRI showed progression of white matter pathology in ALS. Early involvement of motor fibers and later spread to extra-motor regions was found. DT MRI measures of damage to the motor networks showed consistent worsening. These correlated with clinical progression and long-term functional prognosis. No significant cortical thinning was detected either at baseline or over time.
Background and aims Considering the great heterogeneity of amyotrophic lateral sclerosis (ALS), the identification of accurate prognostic predictors is fundamental for both the clinical practice and the design of treatment trials. This study aimed to explore the progression of clinical and structural brain changes in patients with ALS, and to assess magnetic resonance imaging (MRI) measures of brain damage as predictors of subsequent functional decline. Methods 50 ALS patients underwent clinical evaluations and 3 T MRI scans at regular intervals for a maximum of 2 years (total MRI scans = 164). MRI measures of cortical thickness, as well as diffusion tensor (DT) metrics of microstructural damage along white matter (WM) tracts were obtained. Voxel-wise regression models and longitudinal mixed-effects models were used to test the relationship between clinical decline and baseline and longitudinal MRI features. Results The rate of decline of the ALS Functional Rating Scale revised (ALSFRS-r) was significantly associated with the rate of fractional anisotropy (FA) decrease in the body of the corpus callosum (CC). Corticospinal tract (CST) and CC-body alterations had a faster progression in patients with higher baseline ALSFRS-r scores and greater CC-body disruption at baseline. Lower FA of the cerebral peduncle was associated with faster subsequent clinical progression. Conclusions In this longitudinal study, we identified a significant association between measures of WM damage of the motor tracts and functional decline in ALS patients. Our data suggest that a multiparametric approach including DT MRI measures of brain damage would provide an optimal method for an accurate stratification of ALS patients into prognostic classes.
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22
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Montanaro D, Vavla M, Frijia F, Aghakhanyan G, Baratto A, Coi A, Stefan C, Girardi G, Paparella G, De Cori S, Totaro P, Lombardo F, Piccoli G, Martinuzzi A. Multimodal MRI Longitudinal Assessment of White and Gray Matter in Different SPG Types of Hereditary Spastic Paraparesis. Front Neurosci 2020; 14:325. [PMID: 32581663 PMCID: PMC7287014 DOI: 10.3389/fnins.2020.00325] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/19/2020] [Indexed: 01/18/2023] Open
Abstract
Hereditary spastic paraplegias (HSP) are a group of genetically and clinically heterogeneous neurologic disorders. Hereby we describe a relatively large group of patients (pts) affected by HSP studied at baseline (31 pts) and at follow-up (mean period 28.9 ± 8.4 months; 23 pts) with multimodal advanced MRI: high-resolution T1 images for voxel-based morphometry (VBM) analysis, magnetic resonance spectroscopy (MRS), and diffusion tensor imaging (DTI). An age-matched healthy control (HC) group underwent the same neuroimaging protocol in a time schedule matched with the HSP patients. At baseline, VBM showed gray matter (GM) reduction in HSP in the right pre-frontal cortex and bilaterally in the thalami. MRS at baseline depicted in HSP patients compared to the HC group reduction of NAA/Cr ratio in the right pre-frontal region, increase of Cho/Cr ratio in the right pre-central regions, and increase of mI/Cr ratio on the left pre-central area. At cross-sectional follow-up analysis and longitudinal evaluation, no VBM and MRS statistically significant results were obtained. Tract-based spatial statistics (TBSS) analysis showed widespread DTI brain white matter (WM) alterations in patients compared to HC at baseline, which are characterized by reduction of fractional anisotropy (FA) and increase of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity, as confirmed on cross-analysis of the follow-up dataset. A longitudinal analysis with TBSS in HSP patients did not show significant variations, while upon applying region-based analysis we found increased FA and decreased MD and AD in specific brain WM fiber complex during follow-up. The changes were not correlated with the clinical presentation (pure vs complicated HSP), motor function, and motility indexes or history of specific treatments (botulinum toxin). In conclusion, the cross-sectional analysis of the multiparametric MRI data in our HSP patients confirmed the non-prominent involvement of the cortex in the primary motor regions but rather of other more associative areas. On the contrary, DTI demonstrated a widespread involvement of the brain WM, including the primary motor regions, which was confirmed at follow-up. The longitudinal analysis revealed an apparent inversion of tendency when considering the expected evolution of a neurodegenerative process: we detected an increase of FA and a decrease of MD and AD. These time-related modifications may suggest a repair attempt by the residual central WM fibers, which requires confirmation with a larger group of patients and with a longer time interval.
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Affiliation(s)
- Domenico Montanaro
- U.O.C. Risonanza Magnetica Specialistica e Neuroradiologia, Fondazione CNR/Regione Toscana G. Monasterio, Pisa, Italy
| | - M Vavla
- Severe Developmental Disabilities Unit, Scientific Institute, IRCCS Eugenio Medea, Conegliano, Italy
| | - F Frijia
- U.O.C Bioengineering and Clinical Technology, Fondazione CNR/Regione Toscana G. Monasterio, Pisa, Italy
| | - G Aghakhanyan
- Department of Translational Research on New Technologies in Medicine and Surgery, Regional Center of Nuclear Medicine, University of Pisa, Pisa, Italy
| | - A Baratto
- Department of Radiology S. Maria dei Battuti Hospital - Conegliano, ULSS2-Marca Trevigiana, Conegliano, Italy
| | - A Coi
- Institute of Clinical Physiology, National Research Council, Pisa, Italy
| | - C Stefan
- Acquired Neuropsychological Disease Rehabilitation Unit, Scientific Institute, IRCCS Eugenio Medea, Pieve di Soligo, Italy
| | - G Girardi
- Acquired Neuropsychological Disease Rehabilitation Unit, Scientific Institute, IRCCS Eugenio Medea, Pieve di Soligo, Italy
| | - G Paparella
- Acquired Neuropsychological Disease Rehabilitation Unit, Scientific Institute, IRCCS Eugenio Medea, Pieve di Soligo, Italy
| | - S De Cori
- U.O.C. Risonanza Magnetica Specialistica e Neuroradiologia, Fondazione CNR/Regione Toscana G. Monasterio, Pisa, Italy
| | - P Totaro
- U.O.C. Risonanza Magnetica Specialistica e Neuroradiologia, Fondazione CNR/Regione Toscana G. Monasterio, Pisa, Italy
| | - F Lombardo
- U.O.C. Risonanza Magnetica Specialistica e Neuroradiologia, Fondazione CNR/Regione Toscana G. Monasterio, Pisa, Italy
| | - G Piccoli
- Department of Radiology S. Maria dei Battuti Hospital - Conegliano, ULSS2-Marca Trevigiana, Conegliano, Italy
| | - Andrea Martinuzzi
- Severe Developmental Disabilities Unit, Scientific Institute, IRCCS Eugenio Medea, Conegliano, Italy
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Vasta R, D'Ovidio F, Canosa A, Manera U, Torrieri MC, Grassano M, De Marchi F, Mazzini L, Moglia C, Calvo A, Chiò A. Plateaus in amyotrophic lateral sclerosis progression: results from a population‐based cohort. Eur J Neurol 2020; 27:1397-1404. [DOI: 10.1111/ene.14287] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 04/20/2020] [Accepted: 04/21/2020] [Indexed: 11/26/2022]
Affiliation(s)
- R. Vasta
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - F. D'Ovidio
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - A. Canosa
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - U. Manera
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - M. C. Torrieri
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - M. Grassano
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
| | - F. De Marchi
- Department of Neurology ALS Center Azienda Ospedaliero Universitaria Maggiore della Carità NovaraItaly
| | - L. Mazzini
- Department of Neurology ALS Center Azienda Ospedaliero Universitaria Maggiore della Carità NovaraItaly
| | - C. Moglia
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
- Neurology 1 Azienda Ospedaliero Universitaria Città della Salute e della Scienza Turin Italy
| | - A. Calvo
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
- Neurology 1 Azienda Ospedaliero Universitaria Città della Salute e della Scienza Turin Italy
| | - A. Chiò
- ‘Rita Levi Montalcini’ Department of Neuroscience ALS Center University of Turin TurinItaly
- Neurology 1 Azienda Ospedaliero Universitaria Città della Salute e della Scienza Turin Italy
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Meier JM, van der Burgh HK, Nitert AD, Bede P, de Lange SC, Hardiman O, van den Berg LH, van den Heuvel MP. Connectome-Based Propagation Model in Amyotrophic Lateral Sclerosis. Ann Neurol 2020; 87:725-738. [PMID: 32072667 PMCID: PMC7186838 DOI: 10.1002/ana.25706] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 02/14/2020] [Accepted: 02/15/2020] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Clinical trials in amyotrophic lateral sclerosis (ALS) continue to rely on survival or functional scales as endpoints, despite the emergence of quantitative biomarkers. Neuroimaging-based biomarkers in ALS have been shown to detect ALS-associated pathology in vivo, although anatomical patterns of disease spread are poorly characterized. The objective of this study is to simulate disease propagation using network analyses of cerebral magnetic resonance imaging (MRI) data to predict disease progression. METHODS Using brain networks of ALS patients (n = 208) and matched controls across longitudinal time points, network-based statistics unraveled progressive network degeneration originating from the motor cortex and expanding in a spatiotemporal manner. We applied a computational model to the MRI scan of patients to simulate this progressive network degeneration. Simulated aggregation levels at the group and individual level were validated with empirical impairment observed at later time points of white matter and clinical decline using both internal and external datasets. RESULTS We observe that computer-simulated aggregation levels mimic true disease patterns in ALS patients. Simulated patterns of involvement across cortical areas show significant overlap with the patterns of empirically impaired brain regions on later scans, at both group and individual levels. These findings are validated using an external longitudinal dataset of 30 patients. INTERPRETATION Our results are in accordance with established pathological staging systems and may have implications for patient stratification in future clinical trials. Our results demonstrate the utility of computational models in ALS to predict disease progression and underscore their potential as a prognostic biomarker. ANN NEUROL 2020;87:725-738.
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Affiliation(s)
- Jil M. Meier
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Hannelore K. van der Burgh
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Abram D. Nitert
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Peter Bede
- Computational Neuroimaging GroupTrinity Biomedical Sciences Institute, Trinity College DublinDublinIreland
- Department of NeurologyPitié‐Salpêtrière University HospitalParisFrance
- Biomedical Imaging Laboratory, Sorbonne University, National Center for Scientific ResearchNational Institute of Health and Medical ResearchParisFrance
| | - Siemon C. de Lange
- Dutch Connectome Lab, Center for Neurogenomics and Cognitive Research, Amsterdam NeuroscienceFree University AmsterdamAmsterdamthe Netherlands
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences InstituteTrinity College DublinDublinIreland
- Department of NeurologyBeaumont HospitalDublinIreland
| | - Leonard H. van den Berg
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Martijn P. van den Heuvel
- Dutch Connectome Lab, Center for Neurogenomics and Cognitive Research, Amsterdam NeuroscienceFree University AmsterdamAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam University Medical CenterAmsterdamthe Netherlands
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The upper cervical spinal cord in ALS assessed by cross-sectional and longitudinal 3T MRI. Sci Rep 2020; 10:1783. [PMID: 32020025 PMCID: PMC7000761 DOI: 10.1038/s41598-020-58687-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 01/20/2020] [Indexed: 02/08/2023] Open
Abstract
The upper cervical spinal cord is measured in a large longitudinal amyotrophic lateral sclerosis (ALS) cohort to evaluate its role as a biomarker. Specifically, the cervical spinal cord´s cross-sectional area (CSA) in plane of the segments C1–C3 was measured semi-automatically with T1-weighted 3T MRI sequences in 158 ALS patients and 86 controls. Six-month longitudinal follow-up MRI scans were analyzed in 103 patients. Compared to controls, in ALS there was a significant mean spinal cord atrophy (63.8 mm² vs. 60.8 mm², p = 0.001) which showed a trend towards worsening over time (mean spinal cord CSA decrease from 61.4 mm² to 60.6 mm² after 6 months, p = 0.06). Findings were most pronounced in the caudal segments of the upper cervical spinal cord and in limb-onset ALS. Baseline CSA was related to the revised ALS functional rating scale, disease duration, precentral gyrus thickness and total brain gray matter volume. In conclusion, spinal cord atrophy as assessed in brain MRIs in ALS patients mirrors the extent of overall neurodegeneration and parallels disease severity.
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van der Burgh HK, Westeneng HJ, Meier JM, van Es MA, Veldink JH, Hendrikse J, van den Heuvel MP, van den Berg LH. Cross-sectional and longitudinal assessment of the upper cervical spinal cord in motor neuron disease. NEUROIMAGE-CLINICAL 2019; 24:101984. [PMID: 31499409 PMCID: PMC6734179 DOI: 10.1016/j.nicl.2019.101984] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 08/12/2019] [Accepted: 08/13/2019] [Indexed: 11/28/2022]
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease characterized by both upper and lower motor neuron degeneration. While neuroimaging studies of the brain can detect upper motor neuron degeneration, these brain MRI scans also include the upper part of the cervical spinal cord, which offers the possibility to expand the focus also towards lower motor neuron degeneration. Here, we set out to investigate cross-sectional and longitudinal disease effects in the upper cervical spinal cord in patients with ALS, progressive muscular atrophy (PMA: primarily lower motor neuron involvement) and primary lateral sclerosis (PLS: primarily upper motor neuron involvement), and their relation to disease severity and grey and white matter brain measurements. Methods We enrolled 108 ALS patients without C9orf72 repeat expansion (ALS C9–), 26 ALS patients with C9orf72 repeat expansion (ALS C9+), 28 PLS patients, 56 PMA patients and 114 controls. During up to five visits, longitudinal T1-weighted brain MRI data were acquired and used to segment the upper cervical spinal cord (UCSC, up to C3) and individual cervical segments (C1 to C4) to calculate cross-sectional areas (CSA). Using linear (mixed-effects) models, the CSA differences were assessed between groups and correlated with disease severity. Furthermore, a relationship between CSA and brain measurements was examined in terms of cortical thickness of the precentral gyrus and white matter integrity of the corticospinal tract. Results Compared to controls, CSAs at baseline showed significantly thinner UCSC in all groups in the MND spectrum. Over time, ALS C9– patients demonstrated significant thinning of the UCSC and, more specifically, of segment C3 compared to controls. Progressive thinning over time was also observed in C1 of PMA patients, while ALS C9+ and PLS patients did not show any longitudinal changes. Longitudinal spinal cord measurements showed a significant relationship with disease severity and we found a significant correlation between spinal cord and motor cortex thickness or corticospinal tract integrity for PLS and PMA, but not for ALS patients. Discussion Our findings demonstrate atrophy of the upper cervical spinal cord in the motor neuron disease spectrum, which was progressive over time for all but PLS patients. Cervical spinal cord imaging in ALS seems to capture different disease effects than brain neuroimaging. Atrophy of the cervical spinal cord is therefore a promising additional biomarker for both diagnosis and disease progression and could help in the monitoring of treatment effects in future clinical trials. Atrophy of upper cervical spinal cord is shown in the motor neuron disease spectrum. Progressive cervical spinal cord thinning occurs over time for all but PLS patients. Cervical spinal cord imaging is a potential biomarker for disease progression in ALS.
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Affiliation(s)
- Hannelore K van der Burgh
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Henk-Jan Westeneng
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jil M Meier
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Michael A van Es
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jan H Veldink
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jeroen Hendrikse
- Department of Radiology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, The Netherlands.
| | - Leonard H van den Berg
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
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Querin G, Bede P, El Mendili MM, Li M, Pélégrini-Issac M, Rinaldi D, Catala M, Saracino D, Salachas F, Camuzat A, Marchand-Pauvert V, Cohen-Adad J, Colliot O, Le Ber I, Pradat PF. Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study. Ann Neurol 2019; 86:158-167. [PMID: 31177556 DOI: 10.1002/ana.25520] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 06/03/2019] [Accepted: 06/06/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVE C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers. METHODS Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9+ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9+ and C9- subgroups, and C9+ subjects were further stratified by age. RESULTS At baseline, significant WM atrophy was detected at each cervical vertebral level in C9+ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9+ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline. INTERPRETATION Cervical SC imaging detects WM atrophy exclusively in C9+ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.
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Affiliation(s)
- Giorgia Querin
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Peter Bede
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Mohamed Mounir El Mendili
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Menghan Li
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Mélanie Pélégrini-Issac
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Daisy Rinaldi
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France
| | - Martin Catala
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Sorbonne University, National Center for Scientific Research Mixed Unit of Research 7622, National Institute of Health and Medical Research Accademic Research Unit 1156, Biology Institute Paris-Seine, Paris, France
| | - Dario Saracino
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - François Salachas
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Agnes Camuzat
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - Véronique Marchand-Pauvert
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Julien Cohen-Adad
- NeuroPoly Laboratory, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,Functional Neuroimaging Unit, Research Center of the University Institute of Geriatrics of Montreal, University of Montreal, Montreal, Quebec, Canada
| | - Olivier Colliot
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Aramis Project Team, Inria Research Center of Paris, Paris, France.,Center for Image Acquisition and Processing, Brain and Spinal Cord Institute, Paris, France
| | - Isabelle Le Ber
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France.,Institute of Memory and Alzheimer's Disease, Center of Excellence of Neurodegenerative Disease, Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Pierre-François Pradat
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, Clinical-Translational Research and Innovation Center, Altnagelvin Hospital, Londonderry, United Kingdom
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29
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El Mendili MM, Querin G, Bede P, Pradat PF. Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts-Novel Techniques. Front Neurol 2019; 10:350. [PMID: 31031688 PMCID: PMC6474186 DOI: 10.3389/fneur.2019.00350] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 03/21/2019] [Indexed: 01/13/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles.
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Affiliation(s)
- Mohamed Mounir El Mendili
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.,Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France
| | - Giorgia Querin
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
| | - Peter Bede
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France.,Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Pierre-François Pradat
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
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30
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Verber NS, Shepheard SR, Sassani M, McDonough HE, Moore SA, Alix JJP, Wilkinson ID, Jenkins TM, Shaw PJ. Biomarkers in Motor Neuron Disease: A State of the Art Review. Front Neurol 2019; 10:291. [PMID: 31001186 PMCID: PMC6456669 DOI: 10.3389/fneur.2019.00291] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 03/06/2019] [Indexed: 12/17/2022] Open
Abstract
Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.
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Affiliation(s)
- Nick S Verber
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Stephanie R Shepheard
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Matilde Sassani
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Harry E McDonough
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Sophie A Moore
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - James J P Alix
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Iain D Wilkinson
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Tom M Jenkins
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
| | - Pamela J Shaw
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom
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31
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Chipika RH, Finegan E, Li Hi Shing S, Hardiman O, Bede P. Tracking a Fast-Moving Disease: Longitudinal Markers, Monitoring, and Clinical Trial Endpoints in ALS. Front Neurol 2019; 10:229. [PMID: 30941088 PMCID: PMC6433752 DOI: 10.3389/fneur.2019.00229] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2018] [Accepted: 02/22/2019] [Indexed: 12/13/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) encompasses a heterogeneous group of phenotypes with different progression rates, varying degree of extra-motor involvement and divergent progression patterns. The natural history of ALS is increasingly evaluated by large, multi-time point longitudinal studies, many of which now incorporate presymptomatic and post-mortem assessments. These studies not only have the potential to characterize patterns of anatomical propagation, molecular mechanisms of disease spread, but also to identify pragmatic monitoring markers. Sensitive markers of progressive neurodegenerative change are indispensable for clinical trials and individualized patient care. Biofluid markers, neuroimaging indices, electrophysiological markers, rating scales, questionnaires, and other disease-specific instruments have divergent sensitivity profiles. The discussion of candidate monitoring markers in ALS has a dual academic and clinical relevance, and is particularly timely given the increasing number of pharmacological trials. The objective of this paper is to provide a comprehensive and critical review of longitudinal studies in ALS, focusing on the sensitivity profile of established and emerging monitoring markers.
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Affiliation(s)
| | - Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
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32
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Alruwaili AR, Pannek K, Henderson RD, Gray M, Kurniawan ND, McCombe PA. Tract integrity in amyotrophic lateral sclerosis: 6-month evaluation using MR diffusion tensor imaging. BMC Med Imaging 2019; 19:19. [PMID: 30795741 PMCID: PMC6387547 DOI: 10.1186/s12880-019-0319-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 02/13/2019] [Indexed: 11/17/2022] Open
Abstract
Background This study was performed to assess changes in diffusion tensor imaging (DTI) over time in patients with amyotrophic lateral sclerosis (ALS). Methods We performed DTI in 23 ALS patients who had two magnetic resonance imaging (MRI) scans at 6 month intervals and to correlate results with clinical features. The revised ALS functional rating scale (ALSFRS–R) was administered at each clinical visit. Data analysis included voxel–based white matter tract–based spatial statistics (TBSS) and atlas–based region–of–interest (ROI) analysis of fractional anisotropy (FA) and mean diffusivity (MD). Results With TBSS, there were no significant changes between the two scans. The average change in FA and MD in the ROIs over 6 months was small and not significant after allowing for multiple comparisons. After allowing for multiple comparisons, there was no significant correlation of FA or MD with ALSFRS–R. Conclusion This study shows that there is little evidence of progressive changes in DTI over time in ALS. This could be because white matter is already substantially damaged by the time of onset of symptoms of ALS.
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Affiliation(s)
- Ashwag R Alruwaili
- Faculty of Medicine, The University of Queensland, Australia and King Saud University, Brisbane, Australia
| | - Kerstin Pannek
- The Australian e-Health Research Centre, CSIRO, Brisbane, Australia
| | - Robert D Henderson
- Department of Neurology, Faculty of Medicine, Royal Brisbane and Women's Hospital and The University of Queensland, Brisbane, Australia
| | - Marcus Gray
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Nyoman D Kurniawan
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Pamela A McCombe
- Faculty of Medicine, UQ Centre for Clinical Research, Royal Brisbane and Women's Hospital, The University of Queensland, Herston, QLD, 4029, Australia.
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The changing landscape of motor neuron disease imaging: the transition from descriptive studies to precision clinical tools. Curr Opin Neurol 2019; 31:431-438. [PMID: 29750730 DOI: 10.1097/wco.0000000000000569] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE OF REVIEW Neuroimaging in motor neuron disease (MND) has traditionally been seen as an academic tool with limited direct relevance to individualized patient care. This has changed radically in recent years as computational imaging has emerged as a viable clinical tool with true biomarker potential. This transition is not only fuelled by technological advances but also by important conceptual developments. RECENT FINDINGS The natural history of MND is now evaluated by presymptomatic, postmortem and multi-timepoint longitudinal imaging studies. The anatomical spectrum of MND imaging has also been expanded from an overwhelmingly cerebral focus to innovative spinal and muscle applications. In contrast to the group-comparisons of previous studies, machine-learning and deep-learning approaches are increasingly utilized to model real-life diagnostic dilemmas and aid prognostic classification. The focus from evaluating focal structural changes has shifted to the appraisal of network integrity by connectivity-based approaches. The armamentarium of MND imaging has also been complemented by novel PET-ligands, spinal toolboxes and the availability of magnetoencephalography and high-field magnetic resonance (MR) imaging platforms. SUMMARY In addition to the technological and conceptual advances, collaborative multicentre research efforts have also gained considerable momentum. This opinion-piece reviews emerging trends in MND imaging and their implications to clinical care and drug development.
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da Graça FF, de Rezende TJR, Vasconcellos LFR, Pedroso JL, Barsottini OGP, França MC. Neuroimaging in Hereditary Spastic Paraplegias: Current Use and Future Perspectives. Front Neurol 2019; 9:1117. [PMID: 30713518 PMCID: PMC6346681 DOI: 10.3389/fneur.2018.01117] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 12/05/2018] [Indexed: 12/13/2022] Open
Abstract
Hereditary spastic paraplegias (HSP) are a large group of genetic diseases characterized by progressive degeneration of the long tracts of the spinal cord, namely the corticospinal tracts and dorsal columns. Genotypic and phenotypic heterogeneity is a hallmark of this group of diseases, which makes proper diagnosis and management often challenging. In this scenario, magnetic resonance imaging (MRI) emerges as a valuable tool to assist in the exclusion of mimicking disorders and in the detailed phenotypic characterization. Some neuroradiological signs have been reported in specific subtypes of HSP and are therefore helpful to guide genetic testing/interpretation. In addition, advanced MRI techniques enable detection of subtle structural abnormalities not visible on routine scans in the spinal cord and brain of subjects with HSP. In particular, quantitative spinal cord morphometry and diffusion tensor imaging look promising tools to uncover the pathophysiology and to track progression of these diseases. In the current review article, we discuss the current use and future perspectives of MRI in the context of HSP.
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Affiliation(s)
- Felipe Franco da Graça
- Department of Neurology and Neuroimaging Laboratory, University of Campinas (UNICAMP), Campinas, Brazil
| | | | | | - José Luiz Pedroso
- Department of Neurology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | | | - Marcondes C França
- Department of Neurology and Neuroimaging Laboratory, University of Campinas (UNICAMP), Campinas, Brazil
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Shen DC, Xu YY, Hou B, Tai HF, Zhang K, Liu SW, Wang ZL, Feng F, Liu MS, Cui LY. Monitoring Value of Multimodal Magnetic Resonance Imaging in Disease Progression of Amyotrophic Lateral Sclerosis: A Prospective Observational Study. Chin Med J (Engl) 2018; 131:2904-2909. [PMID: 30539901 PMCID: PMC6302648 DOI: 10.4103/0366-6999.247214] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Background: Ongoing efforts have been made to identify new neuroimaging markers to track amyotrophic lateral sclerosis (ALS) progression. This study aimed to explore the monitoring value of multimodal magnetic resonance imaging (MRI) in the disease progression of ALS. Methods: From September 2015 to March 2017, ten patients diagnosed with ALS in Peking Union Medical College Hospital completed head MRI scans at baseline and during follow-up. Multimodal MRI analyses, including gray matter (GM) volume measured by voxel-based morphometry; cerebral blood flow (CBF) evaluated by arterial spin labeling; functional connectivity, including low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), measured by resting-state functional MRI; and integrity of white-matter (WM) fiber tracts evaluated by diffusion tensor imaging, were performed in these patients. Comparisons of imaging metrics were made between baseline and follow-up using paired t-test. Results: In the longitudinal comparisons, the brain structure (GM volume of the right precentral gyri, left postcentral gyri, and right thalami) and perfusion (CBF of the bilateral temporal poles, left precentral gyri, postcentral gyri, and right middle temporal gyri) in both motor and extramotor areas at follow-up were impaired to different extents when compared with those at baseline (all P < 0.05, false discovery rate adjusted). Functional connectivity was increased in the motor areas (fALFF of the right precentral gyri and superior frontal gyri, and ReHo of right precentral gyri) and decreased in the extramotor areas (fALFF of the bilateral middle frontal gyri and ReHo of the right precuneus and cingulate gyri) (all P < 0.001, unadjusted). No significant changes were detected in terms of brain WM measures. Conclusion: Multimodal MRI could be used to monitor short-term brain changes in ALS patients.
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Affiliation(s)
- Dong-Chao Shen
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Yin-Yan Xu
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Bo Hou
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Hong-Fei Tai
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Kang Zhang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Shuang-Wu Liu
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Zhi-Li Wang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Ming-Sheng Liu
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Li-Ying Cui
- Department of Neurology, Peking Union Medical College Hospital; Neuroscience Center, Chinese Academy of Medical Sciences, Beijing 100730, China
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36
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Querin G, El Mendili MM, Lenglet T, Behin A, Stojkovic T, Salachas F, Devos D, Le Forestier N, Del Mar Amador M, Debs R, Lacomblez L, Meininger V, Bruneteau G, Cohen-Adad J, Lehéricy S, Laforêt P, Blancho S, Benali H, Catala M, Li M, Marchand-Pauvert V, Hogrel JY, Bede P, Pradat PF. The spinal and cerebral profile of adult spinal-muscular atrophy: A multimodal imaging study. NEUROIMAGE-CLINICAL 2018; 21:101618. [PMID: 30522974 PMCID: PMC6413472 DOI: 10.1016/j.nicl.2018.101618] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Revised: 11/17/2018] [Accepted: 11/26/2018] [Indexed: 12/13/2022]
Abstract
Spinal muscular atrophy (SMA) type III and IV are autosomal recessive, slowly progressive lower motor neuron syndromes. Nevertheless, wider cerebral involvement has been consistently reported in mouse models. The objective of this study is the characterisation of spinal and cerebral pathology in adult forms of SMA using multimodal quantitative imaging. Methods Twenty-five type III and IV adult SMA patients and 25 age-matched healthy controls were enrolled in a spinal cord and brain imaging study. Structural measures of grey and white matter involvement and diffusion parameters of white matter integrity were evaluated at each cervical spinal level. Whole-brain and region-of-interest analyses were also conducted in the brain to explore cortical thickness, grey matter density and tract-based white matter alterations. Results In the spinal cord, considerable grey matter atrophy was detected between C2-C6 vertebral levels. In the brain, increased grey matter density was detected in motor and extra-motor regions of SMA patients. No white matter pathology was identified neither at brain and spinal level. Conclusions Adult forms of SMA are associated with selective grey matter degeneration in the spinal cord with preserved white matter integrity. The observed increased grey matter density in the motor cortex may represent adaptive reorganisation. (SMA) type 3 and 4 is a lower motor neuron syndrome. Nevertheless, wider involvement of the nervous system might be possible. 25 adults type 3 and 4 SMA patients were studied using brain and cervical spinal cord neuroimaging techniques. Grey matter atrophy was observed in the spinal cord. No white matter degeneration was present at brain and spinal level. Increased grey matter density was detected in cerebral motor regions and explained as compensatory mechanism.
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Affiliation(s)
- Giorgia Querin
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - Mohamed-Mounir El Mendili
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; Icahn School of Medicine at Mount Sinai, Department of Neurology, New York, USA
| | - Timothée Lenglet
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; APHP, Hôpital Pitié-Salpêtriere, Service d'Explorations Fonctionnelles, Paris, France
| | - Anthony Behin
- APHP, Centre de Référence Maladies Neuromusculaires Paris-Est, Institut de Myologie, Hôpital Pitié-Salpêtrière, Paris, France
| | - Tanya Stojkovic
- APHP, Centre de Référence Maladies Neuromusculaires Paris-Est, Institut de Myologie, Hôpital Pitié-Salpêtrière, Paris, France
| | - François Salachas
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - David Devos
- Department of Neurology, ALS Centre, Lille University, INSERM UMRS_1171, University Hospital Centre, LICEND COEN Centre, Lille, France; Department of Medical Pharmacology, Lille University, INSERM UMRS_1171, University Hospital Centre, LICEND COEN Centre, Lille, France
| | - Nadine Le Forestier
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Département de recherche en éthique, EA 1610: Etudes des sciences et techniques, Université Paris Sud/Paris Saclay, Paris, France
| | - Maria Del Mar Amador
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Rabab Debs
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Lucette Lacomblez
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Vincent Meininger
- Hôpital des Peupliers, Ramsay Générale de Santé, F-75013 Paris, France
| | - Gaëlle Bruneteau
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
| | - Stéphane Lehéricy
- APHP, Hôpital Pitié-Salpêtriere, Service de Neuroradiologie, Paris, France; Sorbonne Université, UMR-S975, Inserm U975, CNRS UMR7225, Centre de recherche de l'Institut du Cerveau et de la Moelle épinière - CRICM, Centre de Neuroimagerie de Recherche - CENIR, Paris, France
| | - Pascal Laforêt
- Neurology Department, Nord/Est/Ile de France neuromuscular center, Raymond-Poincaré Hospital, Garches, France; INSERM U1179, END-ICAP, Versailles Saint-Quentin-en-Yvelines University, Montigny-le-Bretonneux
| | - Sophie Blancho
- Institut pour la Recherche sur la Moelle Epinière et l'Encéphale (IRME), Paris, France
| | - Habib Benali
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; Concordia University, PERFORM Centre, Electrical & Computer Engineering Division, Canada
| | - Martin Catala
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Sorbonne Université, CNRS UMR7622, INSERM ERL 1156, IBPS, Paris, France
| | - Menghan Li
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | | | - Jean-Yves Hogrel
- Institute of Myology, Neuromuscular Investigation Center, Paris, France
| | - Peter Bede
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Ireland
| | - Pierre-François Pradat
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute Ulster University, C-TRIC, Altnagelvin Hospital, Derry, Londonderry, United Kingdom.
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Schreiber S, Spotorno N, Schreiber F, Acosta-Cabronero J, Kaufmann J, Machts J, Debska-Vielhaber G, Garz C, Bittner D, Hensiek N, Dengler R, Petri S, Nestor PJ, Vielhaber S. Significance of CSF NfL and tau in ALS. J Neurol 2018; 265:2633-2645. [DOI: 10.1007/s00415-018-9043-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 06/25/2018] [Accepted: 08/30/2018] [Indexed: 01/01/2023]
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Gatto RG, Amin MY, Deyoung D, Hey M, Mareci TH, Magin RL. Ultra-High Field Diffusion MRI Reveals Early Axonal Pathology in Spinal Cord of ALS mice. Transl Neurodegener 2018; 7:20. [PMID: 30128146 PMCID: PMC6097419 DOI: 10.1186/s40035-018-0122-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 07/02/2018] [Indexed: 12/11/2022] Open
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a disease characterized by a progressive degeneration of motor neurons leading to paralysis. Our previous MRI diffusion tensor imaging studies detected early white matter changes in the spinal cords of mice carrying the G93A-SOD1 mutation. Here, we extend those studies using ultra-high field MRI (17.6 T) and fluorescent microscopy to investigate the appearance of early structural and connectivity changes in the spinal cords of ALS mice. Methods The spinal cords from presymptomatic and symptomatic mice (80 to 120 days of age) were scanned (ex-vivo) using diffusion-weighted MRI. The fractional anisotropy (FA), axial (AD) and radial (RD) diffusivities were calculated for axial slices from the thoracic, cervical and lumbar regions of the spinal cords. The diffusion parameters were compared with fluorescence microscopy and membrane cellular markers from the same tissue regions. Results At early stages of the disease (day 80) in the lumbar region, we found, a 19% decrease in FA, a 9% decrease in AD and a 35% increase in RD. Similar changes were observed in cervical and thoracic spinal cord regions. Differences between control and ALS mice groups at the symptomatic stages (day 120) were larger. Quantitative fluorescence microscopy at 80 days, demonstrated a 22% reduction in axonal area and a 22% increase in axonal density. Tractography and quantitative connectome analyses measured by edge weights showed a 52% decrease in the lumbar regions of the spinal cords of this ALS mice group. A significant increase in ADC (23.3%) in the ALS mice group was related to an increase in aquaporin markers. Conclusions These findings suggest that the combination of ultra-high field diffusion MRI with fluorescent ALS mice reporters is a useful approach to detect and characterize presymptomatic white matter micro-ultrastructural changes and axonal connectivity anomalies in ALS.
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Affiliation(s)
- Rodolfo G Gatto
- 1Department of Anatomy and Cell Biology, University of Illinois at Chicago, 808 S. Wood St. Rm 578 M/C 512, Chicago, IL 60612 USA
| | - Manish Y Amin
- 2Department of Physics, University of Florida, Gainesville, FL USA
| | - Daniel Deyoung
- 2Department of Physics, University of Florida, Gainesville, FL USA
| | - Matthew Hey
- 3Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL USA
| | - Thomas H Mareci
- 4Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL USA
| | - Richard L Magin
- 5Department of Bioengineering, University of Illinois at Chicago, Chicago, IL USA
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Gatto RG, Li W, Gao J, Magin RL. In vivo diffusion MRI detects early spinal cord axonal pathology in a mouse model of amyotrophic lateral sclerosis. NMR IN BIOMEDICINE 2018; 31:e3954. [PMID: 30117615 DOI: 10.1002/nbm.3954] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 05/08/2018] [Accepted: 05/09/2018] [Indexed: 06/08/2023]
Abstract
Diffusion magnetic resonance imaging (MRI) exhibits contrast that identifies macro- and microstructural changes in neurodegenerative diseases. Previous studies have shown that MR diffusion tensor imaging (DTI) can observe changes in spinal cord white matter in animals and humans affected with symptomatic amyotrophic lateral sclerosis (ALS). The goal of this preclinical work was to investigate the sensitivity of DTI for the detection of signs of tissue damage before symptoms appear. High-field MRI data were acquired using a 9.4-T animal scanner to examine the spinal cord of an ALS mouse model at pre- and post-symptomatic stages (days 80 and 120, respectively). The MRI results were validated using yellow fluorescent protein (YFP) via optical microscopy of spinal cord tissue slices collected from the YFP,G93A-SOD1 mouse strain. DTI maps of diffusion-weighted imaging (DWI) signal intensity, mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD) and radial diffusivity (RD) were computed for axial slices of the lumbar region of the spinal cord. Significant changes were observed in FA (6.7% decrease, p < 0.01), AD (19.5% decrease, p < 0.01) and RD (16.1% increase, p < 0.001) at postnatal day 80 (P80). These differences were correlated with changes in axonal fluorescence intensity and membrane cellular markers. This study demonstrates the value of DTI as a potential tool to detect the underlying pathological progression associated with ALS, and may accelerate the discovery of therapeutic strategies for patients with this disease.
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Affiliation(s)
- Rodolfo G Gatto
- University of Illinois at Chicago, Anatomy and Cell Biology, Chicago, IL, USA
| | - Weiguo Li
- University of Illinois at Chicago, Bioengineering, Chicago, IL, USA
| | - Jin Gao
- University of Illinois at Chicago, Bioengineering, Chicago, IL, USA
| | - Richard L Magin
- University of Illinois at Chicago, Bioengineering, Chicago, IL, USA
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Wirth AM, Khomenko A, Baldaranov D, Kobor I, Hsam O, Grimm T, Johannesen S, Bruun TH, Schulte-Mattler W, Greenlee MW, Bogdahn U. Combinatory Biomarker Use of Cortical Thickness, MUNIX, and ALSFRS-R at Baseline and in Longitudinal Courses of Individual Patients With Amyotrophic Lateral Sclerosis. Front Neurol 2018; 9:614. [PMID: 30104996 PMCID: PMC6077217 DOI: 10.3389/fneur.2018.00614] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 07/09/2018] [Indexed: 11/13/2022] Open
Abstract
Objective: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative process affecting upper and lower motor neurons as well as non-motor systems. In this study, precentral and postcentral cortical thinning detected by structural magnetic resonance imaging (MRI) were combined with clinical (ALS-specific functional rating scale revised, ALSFRS-R) and neurophysiological (motor unit number index, MUNIX) biomarkers in both cross-sectional and longitudinal analyses. Methods: The unicenter sample included 20 limb-onset classical ALS patients compared to 30 age-related healthy controls. ALS patients were treated with standard Riluzole and additional long-term G-CSF (Filgrastim) on a named patient basis after written informed consent. Combinatory biomarker use included cortical thickness of atlas-based dorsal and ventral subdivisions of the precentral and postcentral cortex, ALSFRS-R, and MUNIX for the musculus abductor digiti minimi (ADM) bilaterally. Individual cross-sectional analysis investigated individual cortical thinning in ALS patients compared to age-related healthy controls in the context of state of disease at initial MRI scan. Beyond correlation analysis of biomarkers at cross-sectional group level (n = 20), longitudinal monitoring in a subset of slow progressive ALS patients (n = 4) explored within-subject temporal dynamics of repeatedly assessed biomarkers in time courses over at least 18 months. Results: Cross-sectional analysis demonstrated individually variable states of cortical thinning, which was most pronounced in the ventral section of the precentral cortex. Correlations of ALSFRS-R with cortical thickness and MUNIX were detected. Individual longitudinal biomarker monitoring in four slow progressive ALS patients revealed evident differences in individual disease courses and temporal dynamics of the biomarkers. Conclusion: A combinatory use of structural MRI, neurophysiological and clinical biomarkers allows for an appropriate and detailed assessment of clinical state and course of disease of ALS.
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Affiliation(s)
- Anna M Wirth
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany.,Department of Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Andrei Khomenko
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Dobri Baldaranov
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Ines Kobor
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Ohnmar Hsam
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Thomas Grimm
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Siw Johannesen
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | - Tim-Henrik Bruun
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
| | | | - Mark W Greenlee
- Department of Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Ulrich Bogdahn
- Department of Neurology, University Hospital of Regensburg, Regensburg, Germany
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Gatto RG, Mustafi SM, Amin MY, Mareci TH, Wu YC, Magin RL. Neurite orientation dispersion and density imaging can detect presymptomatic axonal degeneration in the spinal cord of ALS mice. FUNCTIONAL NEUROLOGY 2018; 33:155-163. [PMID: 30457969 PMCID: PMC7212765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Neurite orientation dispersion and density imaging (NODDI), a MRI multi-shell diffusion technique, has offered new insights for the study of microstructural changes in neurodegenerative diseases. Mainly, the present study aimed to determine the connection between NODDI-derived parameters and changes in white matter (WM) abnormalities at early stages of amyotrophic lateral sclerosis (ALS). Spinal cords from ALS mice (G93A-SOD1 mice) were scanned in a Bruker Avance III HD 17.6T magnet. Fluorescent axonal-tagged mice (YFP, G93A-SOD1 mice) were used for quantitative histological analysis. NODDI showed a decrease in intra-cellular volume fraction (-24%) and increases in orientation dispersion index (+35%) and isotropic volume fraction (+33%). In addition, histoathological results demonstrated a reductions in axonal area (-11%) and myelin content (-29%). A histological decrease in WM intra-axonal space (-71%) and an increase in the extra-axonal compartment (+22%) were also detected. Our studies demonstrate that NODDI may be a suitable technique for detecting presymptomatic spinal cord WM microstructural degeneration in ALS.
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Affiliation(s)
- Rodolfo G. Gatto
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, USA
| | - Sourajit M. Mustafi
- Department of Radiology and Imaging Sciences, Indiana University, School of Medicine Indianapolis, IN, USA
| | - Manish Y. Amin
- Department of Physics, University of Florida, Gainesville, FL, USA
| | - Thomas H. Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University, School of Medicine Indianapolis, IN, USA
| | - Richard L. Magin
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
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Antonescu F, Adam M, Popa C, Tuţă S. A review of cervical spine MRI in ALS patients. J Med Life 2018; 11:123-127. [PMID: 30140318 PMCID: PMC6101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
Abstract
Rationale. In recent years, significant advances have been made on the subject of MRI examination techniques, which have opened new avenues of research regarding the spinal involvement in amyotrophic lateral sclerosis (ALS). Objective. Our objective was to compile and analyze the available literature data, concerning the MRI of the cervical spine in ALS, detailing the metrics and their significance in diagnosis and follow-up. Methods and results. We have conducted an extensive search on the subject using literature data published over the last fifteen years, correlating it with our own experience. In ALS, there is a permanent interest in developing new biomarkers that might be sensitive to spatial and temporal patterns of neurodegeneration, which will permit early diagnosis and hopefully lead to new therapeutic approaches. Both diffusion tensor imaging (DTI) and spinal cord morphometry (especially spinal atrophy) reflect different aspects of the disease and correlate with clinical deterioration. Newer approaches like inhomogeneous magnetization transfer (ihMTR) and multiparametric analysis seem to have better sensitivity, are more appropriate for follow-up, and lend themselves to prognostic conclusions. Discussion. We conclude that MRI is a constantly expanding field, a unique non-invasive tool with immense potential in evaluating the in vivo evolution of the neurodegenerative ALS process, both structurally and functionally, with high hopes for the future. Abbreviations: ALS - amyotrophic lateral sclerosis, UMN - upper motor neuron, LMN - lower motor neuron, EMG - electromyography, CST - cortico-spinal tract, FLAIR - fluid-attenuated inversion recovery, MND - motor neuron disease, DTI - Diffusion tensor imaging, FA - fractional anisotropy, MD - mean diffusivity, ihMTR - inhomogeneous magnetization transfer, fMRI - functional MRI.
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Affiliation(s)
- F Antonescu
- National Institute of Neurology and Neurovascular Diseases, Bucharest,“Carol Davila” University of Medicine and Pharmacy, Bucharest
| | - M Adam
- MEDINST Diagnostic Center, Bucharest
| | - C Popa
- National Institute of Neurology and Neurovascular Diseases, Bucharest,“Carol Davila” University of Medicine and Pharmacy, Bucharest
| | - S Tuţă
- National Institute of Neurology and Neurovascular Diseases, Bucharest,“Carol Davila” University of Medicine and Pharmacy, Bucharest
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Menke RAL, Proudfoot M, Talbot K, Turner MR. The two-year progression of structural and functional cerebral MRI in amyotrophic lateral sclerosis. NEUROIMAGE-CLINICAL 2017; 17:953-961. [PMID: 29321969 PMCID: PMC5752097 DOI: 10.1016/j.nicl.2017.12.025] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 12/14/2017] [Accepted: 12/16/2017] [Indexed: 01/04/2023]
Abstract
MRI has emerged as one of several urgently needed candidate disease progression biomarkers for the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), not least due to its unique ability to non-invasively assess structural and functional cerebral pathology. We sought to identify the extent of detectable change in cerebral MRI metrics over a more prolonged period. Analysis of multi-modal MRI data was performed in a cohort of sixteen patients (13 ALS and 3 with primary lateral sclerosis) in whom it was possible to acquire six-monthly images over two years. Structural brain changes were assessed using voxel-based morphometry of grey matter and shape analysis of sub-cortical grey matter structures, tract-based spatial statistics of diffusion tensor imaging (DTI) metrics optimized for longitudinal analysis in the white matter, as well as whole brain voxel-wise statistics of DTI metrics. Changes in resting state functional MRI (rs-fMRI) were investigated via independent component and dual regression analyses of functional connectivity (FC), controlled for confounding effects of grey matter decline. Both linear changes with time and brain changes correlated with revised ALS functional rating score (ALSFRS-R) decline were studied. Widespread and progressive reductions in grey matter were observed in the precentral gyri and posterior cingulate cortex, as well as progressive local atrophy of the thalamus, caudate, and pallidum bilaterally, and right putamen, hippocampus and amygdala. The most prominent DTI tract-based changes were in the superior longitudinal fasciculi and corpus callosum. More widespread areas of DTI changes included the thalami and caudate nuclei, hippocampi and parahippocampal gyri, insular cortices, anterior and posterior cingulate gyri, frontal operculum and cerebellum. FC decreases were noted between the sensorimotor resting state network and the frontal pole, between a network comprising both thalami and an area in the visual cortex, in relation to both time from baseline and ALSFRS-R decline. FC increases between the left primary motor cortex and left fronto-parietal network were seen for both statistical approaches. A longer period of follow-up, though necessarily involving more slowly-progressive cases, demonstrated widespread changes in both grey and white matter structural MRI measures. The mixed picture of regional decreases and increases in FC is compatible with compensatory change, in what should be viewed as a brain-based disease characterised by larger-scale disintegration of motor and frontal projection cerebral networks. Analysis of serial MRI data (6-monthly over 2 years) was performed in ALS patients. Widespread progressive structural and functional brain changes were observed. Changes during this unprecedented study period involved basal ganglia regions. The results revealed novel longitudinal functional connectivity insights.
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Affiliation(s)
- R A L Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M Proudfoot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - K Talbot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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Rasoanandrianina H, Grapperon AM, Taso M, Girard OM, Duhamel G, Guye M, Ranjeva JP, Attarian S, Verschueren A, Callot V. Region-specific impairment of the cervical spinal cord (SC) in amyotrophic lateral sclerosis: A preliminary study using SC templates and quantitative MRI (diffusion tensor imaging/inhomogeneous magnetization transfer). NMR IN BIOMEDICINE 2017; 30:e3801. [PMID: 28926131 DOI: 10.1002/nbm.3801] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 07/24/2017] [Accepted: 08/07/2017] [Indexed: 06/07/2023]
Abstract
In this preliminary study, our objective was to investigate the potential of high-resolution anatomical imaging, diffusion tensor imaging (DTI) and conventional/inhomogeneous magnetization transfer imaging [magnetization transfer (MT)/inhomogeneous magnetization transfer (ihMT)] at 3 T, analyzed with template-extracted regions of interest, to measure the atrophy and structural changes of white (WM) and gray (GM) matter spinal cord (SC) occurring in patients with amyotrophic lateral sclerosis (ALS). Ten patients with ALS and 20 age-matched healthy controls were recruited. SC GM and WM areas were automatically segmented using dedicated templates. Atrophy indices were evaluated from T2 *-weighted images at each vertebral level from cervical C1 to C6. DTI and ihMT metrics were quantified within the corticospinal tract (CST), posterior sensory tract (PST) and anterior GM (aGM) horns at the C2 and C5 levels. Clinical disabilities of patients with ALS were evaluated using the Revised ALS Functional Rating Scale, upper motor neuron (UMN) and Medical Research Council scorings, and correlated with MR metrics. Compared with healthy controls, GM and WM atrophy was observed in patients with ALS, especially at lower cervical levels, where a strong correlation was also observed between GM atrophy and the UMN score (R = -0.75, p = 0.05 at C6). Interestingly, a significant decrease in ihMT ratio was found in all regions of interest (p < 0.0008), fractional anisotropy (FA) and MT ratios decreased significantly in CST, especially at C5 (p < 0.005), and λ// (axial diffusivity) decreased significantly in CST (p = 0.0004) and PST (p = 0.003) at C2. Strong correlations between MRI metrics and clinical scores were also found (0.47 < |R| < 0.87, p < 0.05). Altogether, these preliminary results suggest that high-resolution anatomical imaging and ihMT imaging, in addition to DTI, are valuable for the characterization of SC tissue impairment in ALS. In this study, in addition to an important SC WM demyelination, we also observed, for the first time in ALS, impairments of cervical aGM.
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Affiliation(s)
- Henitsoa Rasoanandrianina
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille-Montreal, France-Canada
- Aix-Marseille Université, IFSTTAR, LBA UMR T 24, Marseille, France
| | - Aude-Marie Grapperon
- Centre de Référence des Maladies neuro-musculaires et de la SLA, Hopital de La Timone, Marseille, France
| | - Manuel Taso
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille-Montreal, France-Canada
- Aix-Marseille Université, IFSTTAR, LBA UMR T 24, Marseille, France
| | - Olivier M Girard
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
| | - Guillaume Duhamel
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
| | - Shahram Attarian
- Centre de Référence des Maladies neuro-musculaires et de la SLA, Hopital de La Timone, Marseille, France
- Aix Marseille Université, INSERM, GMGF, Marseille, France
| | - Annie Verschueren
- Centre de Référence des Maladies neuro-musculaires et de la SLA, Hopital de La Timone, Marseille, France
| | - Virginie Callot
- Aix-Marseille Université, CNRS, APHM, CRMBM, Hôpital de la Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille-Montreal, France-Canada
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Wood H. Spinal cord morphometry — a promising technique to track disease course in ALS. Nat Rev Neurol 2017; 13:129. [DOI: 10.1038/nrneurol.2017.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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