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Attarian S, Beloribi-Djefaflia S, Bernard R, Nguyen K, Cances C, Gavazza C, Echaniz-Laguna A, Espil C, Evangelista T, Feasson L, Audic F, Zagorda B, Milhe De Bovis V, Stojkovic T, Sole G, Salort-Campana E, Sacconi S. French National Protocol for diagnosis and care of facioscapulohumeral muscular dystrophy (FSHD). J Neurol 2024:10.1007/s00415-024-12538-3. [PMID: 38955828 DOI: 10.1007/s00415-024-12538-3] [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: 03/05/2024] [Revised: 06/21/2024] [Accepted: 06/23/2024] [Indexed: 07/04/2024]
Abstract
Facioscapulohumeral muscular dystrophy (FSHD) is one of the most common genetically inherited myopathies in adults. It is characterized by incomplete penetrance and variable expressivity. Typically, FSHD patients display asymmetric weakness of facial, scapular, and humeral muscles that may progress to other muscle groups, particularly the abdominal and lower limb muscles. Early-onset patients display more severe muscle weakness and atrophy, resulting in a higher frequency of associated skeletal abnormalities. In these patients, multisystem involvement, including respiratory, ocular, and auditory, is more frequent and severe and may include the central nervous system. Adult-onset FSHD patients may also display some degree of multisystem involvement which mainly remains subclinical. In 95% of cases, FSHD patients carry a pathogenic contraction of the D4Z4 repeat units (RUs) in the subtelomeric region of chromosome 4 (4q35), which leads to the expression of DUX4 retrogene, toxic for muscles (FSHD1). Five percent of patients display the same clinical phenotype in association with a mutation in the SMCHD1 gene located in chromosome 18, inducing epigenetic modifications of the 4q D4Z4 repeated region and expression of DUX4 retrogene. This review highlights the complexities and challenges of diagnosing and managing FSHD, underscoring the importance of standardized approaches for optimal patient outcomes. It emphasizes the critical role of multidisciplinary care in addressing the diverse manifestations of FSHD across different age groups, from skeletal abnormalities in early-onset cases to the often-subclinical multisystem involvement in adults. With no current cure, the focus on alleviating symptoms and slowing disease progression through coordinated care is paramount.
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Affiliation(s)
- Shahram Attarian
- Reference Center for Neuromuscular Disorders and ALS, Timone University Hospital, Aix-Marseille University, Marseille, France.
- FILNEMUS, European Reference Network for Rare Diseases (ERN-NMD), Marseille, France.
- Marseille Medical Genetics, Aix Marseille Université-Inserm UMR_1251, 13005, Marseille, France.
| | - Sadia Beloribi-Djefaflia
- Reference Center for Neuromuscular Disorders and ALS, Timone University Hospital, Aix-Marseille University, Marseille, France
| | - Rafaelle Bernard
- Marseille Medical Genetics, Aix Marseille Université-Inserm UMR_1251, 13005, Marseille, France
| | - Karine Nguyen
- Marseille Medical Genetics, Aix Marseille Université-Inserm UMR_1251, 13005, Marseille, France
| | - Claude Cances
- Reference Center for Neuromuscular Disorders, Toulouse Children's Hospital, Toulouse, France
- Pediatric Neurology Department, Toulouse Children's Hospital, Toulouse, France
| | - Carole Gavazza
- Reference Center for Neuromuscular Disorders and ALS, Timone University Hospital, Aix-Marseille University, Marseille, France
| | - Andoni Echaniz-Laguna
- Department of Neurology, APHP, CHU de Bicêtre, Le Kremlin Bicêtre, France
- French National Reference Center for Rare Neuropathies (NNERF), Le Kremlin Bicêtre, France
- Inserm U1195, University Paris Saclay, Le Kremlin Bicêtre, France
| | - Caroline Espil
- Reference Center for Neuromuscular Disorders AOC, Children's Hospital, CHU Bordeaux, Bordeaux, France
| | - Teresinha Evangelista
- Institute of Myology, Nord/Est/Ile-de-France Neuromuscular Reference Center, Pitié-Salpêtrière Hospital, APHP, Sorbonne University, Paris, France
| | - Léonard Feasson
- Department of Clinical and Exercise Physiology, University Hospital Center of Saint-Etienne, 42000, Saint-Etienne, France
- Inter-University Laboratory of Human Movement Biology, EA 7424, Jean Monnet University, 42000, Saint-Etienne, France
| | - Frédérique Audic
- Reference Center for Neuromuscular Diseases in Children PACARARE, Neuropediatrics Department, Timone University Children's Hospital, Marseille, France
| | - Berenice Zagorda
- Department of Clinical and Exercise Physiology, University Hospital Center of Saint-Etienne, 42000, Saint-Etienne, France
| | - Virginie Milhe De Bovis
- Reference Center for Neuromuscular Disorders and ALS, Timone University Hospital, Aix-Marseille University, Marseille, France
| | - Tanya Stojkovic
- Institute of Myology, Nord/Est/Ile-de-France Neuromuscular Reference Center, Pitié-Salpêtrière Hospital, APHP, Sorbonne University, Paris, France
| | - Guilhem Sole
- Centre de Référence des Maladies Neuromusculaires AOC, FILNEMUS, Hôpital Pellegrin, CHU de Bordeaux, Bordeaux, France
| | - Emmanuelle Salort-Campana
- Reference Center for Neuromuscular Disorders and ALS, Timone University Hospital, Aix-Marseille University, Marseille, France
| | - Sabrina Sacconi
- Peripheral Nervous System and Muscle Department, Université Côte d'Azur, CHU Nice, Pasteur 2, Nice Hospital, France.
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2
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Maggi L, Quijano-Roy S, Bönnemann C, Bonne G. 253rd ENMC international workshop: Striated muscle laminopathies - natural history and clinical trial readiness. 24-26 June 2022, Hoofddorp, the Netherlands. Neuromuscul Disord 2023; 33:498-510. [PMID: 37235886 DOI: 10.1016/j.nmd.2023.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 04/25/2023] [Indexed: 05/28/2023]
Affiliation(s)
- Lorenzo Maggi
- Neuroimmunology and Neuromuscular Diseases Unit, Fondazione IRCCS Instituto Neurologico Carlo Besta, Milano, Italy.
| | - Susana Quijano-Roy
- APHP-Université Paris-Saclay, Neuromuscular Disorders Reference Center of Nord-Est-Île de France, FILNEMUS, ERN-Euro-NMD, Creteil, France; Pediatric Neurology and ICU Department, DMU Santé Enfant Adolescent (SEA), Raymond Poincaré University Hospital, Garches, France
| | - Carsten Bönnemann
- Neuromuscular and Neurogenetic Disorders of Childhood Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Gisèle Bonne
- Sorbonne Université, INSERM, Institut de Myologie, Centre de Recherche en Myologie, Paris, France.
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Garibaldi M, Nicoletti T, Bucci E, Fionda L, Leonardi L, Morino S, Tufano L, Alfieri G, Lauletta A, Merlonghi G, Perna A, Rossi S, Ricci E, Tartaglione T, Petrucci A, Pennisi EM, Salvetti M, Cutter G, Díaz-Manera J, Silvestri G, Antonini G. Muscle MRI in Myotonic Dystrophy type 1 (DM1): refining muscle involvement and implications for clinical trials. Eur J Neurol 2021; 29:843-854. [PMID: 34753219 PMCID: PMC9299773 DOI: 10.1111/ene.15174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/19/2021] [Accepted: 11/01/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Only few studies reported muscle imaging data on small cohorts of patients with Myotonic dystrophy type 1 (DM1). We aimed to investigate the muscle involvement in a large cohort of patients, to refine the pattern of muscle involvement, to better understand the pathophysiological mechanisms of muscle weakness and to identify potential imaging biomarkers for disease activity and severity. METHODS 134 DM1 patients underwent a cross-sectional muscle MRI study. STIR and T1- sequences in lower and upper body were analysed. Fat replacement, muscle atrophy and STIR positivity were evaluated using three different scales. Correlations between MRI scores, clinical features and genetic background were investigated. RESULTS The most frequent pattern of muscle involvement in T1 consisted of fat replacement of the tongue, sternocleidomastoideus, paraspinalis, gluteus minimus, distal quadriceps and gastrocnemius medialis. Degree of fat replacement at MRI correlated with clinical severity and disease duration, but not with CTG expansion. Fat replacement was also detected in milder/asymptomatic patients. More than 80% of patients had STIR positive signal in muscles. Most DM1 patients also showed a variable degree of muscle atrophy regardless MRI signs of fat replacement. A subset of patients (20%) showed a "marbled" muscle appearance. CONCLUSIONS muscle MRI is a sensitive biomarker of disease severity also for the milder spectrum of disease. STIR hyperintensty seems to precede fat replacement in T1. Beyond fat replacement, STIR positivity, muscle atrophy and "marbled" appearance suggest further mechanisms of muscle wasting and weakness in DM1, representing additional outcome measures and therapeutical targets for forthcoming clinical trials.
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Affiliation(s)
- Matteo Garibaldi
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Tommaso Nicoletti
- UOC Neurologia, Fondazione Policlinico Universitario 'A. Gemelli' IRCCS, 00168, Rome, Italy.,Department of Neurosciences, Università Cattolica del Sacro Cuore, Facoltà di Medicina e Chirurgia, 00168, Rome, Italy
| | - Elisabetta Bucci
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Laura Fionda
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Luca Leonardi
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Stefania Morino
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Laura Tufano
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Girolamo Alfieri
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Antonio Lauletta
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Gioia Merlonghi
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
| | - Alessia Perna
- UOC Neurologia, Fondazione Policlinico Universitario 'A. Gemelli' IRCCS, 00168, Rome, Italy.,Department of Neurosciences, Università Cattolica del Sacro Cuore, Facoltà di Medicina e Chirurgia, 00168, Rome, Italy
| | - Salvatore Rossi
- UOC Neurologia, Fondazione Policlinico Universitario 'A. Gemelli' IRCCS, 00168, Rome, Italy.,Department of Neurosciences, Università Cattolica del Sacro Cuore, Facoltà di Medicina e Chirurgia, 00168, Rome, Italy
| | - Enzo Ricci
- UOC Neurologia, Fondazione Policlinico Universitario 'A. Gemelli' IRCCS, 00168, Rome, Italy.,Department of Neurosciences, Università Cattolica del Sacro Cuore, Facoltà di Medicina e Chirurgia, 00168, Rome, Italy
| | - Tommaso Tartaglione
- Department of Radiology, Istituto Dermopatico dell'Immacolata, IRCCS, 00167, Rome, Italy
| | - Antonio Petrucci
- Neurology Unit, San Camillo-Forlanini Hospital, 00152, Rome, Italy
| | | | - Marco Salvetti
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy.,IRCCS Istituto Neurologico Mediterraneo (INM) Neuromed, 86077, Pozzilli, Italy
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, 35233, Birmingham, AL, USA
| | - Jordi Díaz-Manera
- John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle Hospitals NHS Foundation Trust, NE1 3BZ, Newcastle upon Tyne, United Kingdom.,Neuromuscular Disorders Unit. Neurology Department, Universitat Autònoma de Barcelona. Hospital de la Santa Creu I Sant Pau, 08041, Barcelona, UK.,Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), 08041, Spain
| | - Gabriella Silvestri
- UOC Neurologia, Fondazione Policlinico Universitario 'A. Gemelli' IRCCS, 00168, Rome, Italy.,Department of Neurosciences, Università Cattolica del Sacro Cuore, Facoltà di Medicina e Chirurgia, 00168, Rome, Italy
| | - Giovanni Antonini
- Neuromuscular and Rare Disease Centre, Department of Neuroscience, Mental Health and Sensory Organs (NESMOS), SAPIENZA University of Rome, Sant'Andrea Hospital, 00189, Rome, Italy
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4
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Gómez-Andrés D, Oulhissane A, Quijano-Roy S. Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches. Neuromuscul Disord 2021; 31:1038-1050. [PMID: 34736625 DOI: 10.1016/j.nmd.2021.08.006] [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: 07/27/2021] [Revised: 07/30/2021] [Accepted: 08/01/2021] [Indexed: 11/29/2022]
Abstract
Muscle imaging has progressively gained popularity in the neuromuscular field. Together with detailed clinical examination and muscle biopsy, it has become one of the main tools for deep phenotyping and orientation of etiological diagnosis. Even in the current era of powerful new generation sequencing, muscle MRI has arisen as a tool for prioritization of certain genetic entities, supporting the pathogenicity of variants of unknown significance and facilitating diagnosis in cases with an initially inconclusive genetic study. Although the utility of muscle imaging is increasingly clear, it has not reached its full potential in clinical practice. Pattern recognition is known for a number of diseases and will certainly be enhanced by the use of machine learning approaches. For instance, MRI heatmap representations might be confronted with molecular results by obtaining a probabilistic diagnosis based in each disease "MRI fingerprints". Muscle ultrasound as a screening tool and quantified techniques such as Dixon MRI seem still underdeveloped. In this paper, we aim to appraise the advances in recent years in pediatric muscle imaging and try to define areas of uncertainty and potential advances that might become standardized to be widely used in the future.
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Affiliation(s)
- David Gómez-Andrés
- Pediatric Neurology, Vall d'Hebron Institut de Recerca (VHIR), Hospital Universitari Vall d'Hebron, ERN-RND - EURO-NMD, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; European Network for Reference Centers on Neuromuscular Disorders (Euro-NMD ERN)
| | - Amal Oulhissane
- Université Paris-Saclay, APHP, Neuromuscular Unit, Pediatric Neurology and ICU Department, Raymond Poincaré Hospital, 92390 Garches, France
| | - Susana Quijano-Roy
- Université Paris-Saclay, APHP, Neuromuscular Unit, Pediatric Neurology and ICU Department, Raymond Poincaré Hospital, 92390 Garches, France; UMR 1179, Laboratoire handicap neuromusculaire: physiopathologie biothérapie pharmacologie appliquées (END-ICAP), UFR Simone Veil, Montigny Le Bretonneux, France; French Network of Neuromuscular Reference Centers (FILNEMUS), France.
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5
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Savarese M, Välipakka S, Johari M, Hackman P, Udd B. Is Gene-Size an Issue for the Diagnosis of Skeletal Muscle Disorders? J Neuromuscul Dis 2021; 7:203-216. [PMID: 32176652 PMCID: PMC7369045 DOI: 10.3233/jnd-190459] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Human genes have a variable length. Those having a coding sequence of extraordinary length and a high number of exons were almost impossible to sequence using the traditional Sanger-based gene-by-gene approach. High-throughput sequencing has partly overcome the size-related technical issues, enabling a straightforward, rapid and relatively inexpensive analysis of large genes. Several large genes (e.g. TTN, NEB, RYR1, DMD) are recognized as disease-causing in patients with skeletal muscle diseases. However, because of their sheer size, the clinical interpretation of variants in these genes is probably the most challenging aspect of the high-throughput genetic investigation in the field of skeletal muscle diseases. The main aim of this review is to discuss the technical and interpretative issues related to the diagnostic investigation of large genes and to reflect upon the current state of the art and the future advancements in the field.
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Affiliation(s)
- Marco Savarese
- Folkhälsan Research Center, Helsinki, Finland.,Department of Medical Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - Salla Välipakka
- Folkhälsan Research Center, Helsinki, Finland.,Department of Medical Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - Mridul Johari
- Folkhälsan Research Center, Helsinki, Finland.,Department of Medical Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - Peter Hackman
- Folkhälsan Research Center, Helsinki, Finland.,Department of Medical Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - Bjarne Udd
- Folkhälsan Research Center, Helsinki, Finland.,Department of Medical Genetics, Medicum, University of Helsinki, Helsinki, Finland.,Neuromuscular Research Center, Tampere University and University Hospital, Tampere, Finland.,Department of Neurology, Vaasa Central Hospital, Vaasa, Finland
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6
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Cotta A, Paim JF, Carvalho E, Valicek J, da Cunha Junior AL, Navarro MM, Vargas AP, Lima MI, de Almeida CF, Takata RI, Vainzof M. LMNA-Related Muscular Dystrophy with Clinical Intrafamilial Variability. J Mol Neurosci 2019; 69:623-627. [PMID: 31410651 DOI: 10.1007/s12031-019-01390-0] [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: 02/15/2019] [Accepted: 07/18/2019] [Indexed: 10/26/2022]
Abstract
The LMNA gene is associated to a huge broad of phenotypes, including congenital Emery-Dreifuss muscular dystrophy and late-onset LMNA-related muscular dystrophy. In these forms, muscle weakness, contractures, and cardiac impairment are common. In an autosomal dominant pedigree including 5 affected patients, NGS molecular analysis performed in 6 relatives identifies the heterozygous c.1129C>T p.Arg377Cys variant in the exon 6 of the LMNA gene in three of them. Clinical, laboratorial, imaging investigation of these affected patients showed a significant clinical variability: the father presented subclinical imaging muscular dystrophy masqueraded as radiculopathy. One of his sons presented cardiac arrhythmia, muscular weakness, elbow contractures, and intranuclear pseudoinclusions on muscle biopsy. A second son presented only decreased tendon reflexes. Two other brothers presenting myalgia and cramps were not carriers of the same mutation in the LMNA gene. Early diagnosis, considering these variable phenotype and genotype, is important for genetic counseling, as well as cardiac, and rehabilitation management.
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Affiliation(s)
- Ana Cotta
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Julia F Paim
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Elmano Carvalho
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Jaquelin Valicek
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Antonio L da Cunha Junior
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Monica M Navarro
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Antonio P Vargas
- Pathology, Neurophysiology, Radiology, Pediatrics and Genetics, and Neurology Departments, SARAH Network of Rehabilitation Hospitals, Belo Horizonte, Brazil
| | - Maria I Lima
- Electron Microscopy and Molecular Biology Departments, SARAH Network of Rehabilitation Hospitals, Brasilia, Brazil
| | - Camila F de Almeida
- Human Genome and Stem Cells Research Center, Genetics and Evolutionary Biology Department, IBUSP, University of São Paulo, Rua do Matão, Travessa 13, no. 106, São Paulo, SP, 05508-090, Brazil
| | - Reinaldo I Takata
- Electron Microscopy and Molecular Biology Departments, SARAH Network of Rehabilitation Hospitals, Brasilia, Brazil
| | - Mariz Vainzof
- Human Genome and Stem Cells Research Center, Genetics and Evolutionary Biology Department, IBUSP, University of São Paulo, Rua do Matão, Travessa 13, no. 106, São Paulo, SP, 05508-090, Brazil.
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7
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Weber KA, Smith AC, Wasielewski M, Eghtesad K, Upadhyayula PA, Wintermark M, Hastie TJ, Parrish TB, Mackey S, Elliott JM. Deep Learning Convolutional Neural Networks for the Automatic Quantification of Muscle Fat Infiltration Following Whiplash Injury. Sci Rep 2019; 9:7973. [PMID: 31138878 PMCID: PMC6538618 DOI: 10.1038/s41598-019-44416-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 05/15/2019] [Indexed: 02/07/2023] Open
Abstract
Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated state-of-the-art performance in segmentation tasks. Here, we train and test a CNN for muscle segmentation and automatic MFI calculation using high-resolution fat-water images from 39 participants (26 female, average = 31.7 ± 9.3 years) 3 months post whiplash injury. First, we demonstrate high test reliability and accuracy of the CNN compared to manual segmentation. Then we explore the relationships between CNN muscle volume, CNN MFI, and clinical measures of pain and neck-related disability. Across all participants, we demonstrate that CNN muscle volume was negatively correlated to pain (R = -0.415, p = 0.006) and disability (R = -0.286, p = 0.045), while CNN MFI tended to be positively correlated to disability (R = 0.214, p = 0.105). Additionally, CNN MFI was higher in participants with persisting pain and disability (p = 0.049). Overall, CNN's may improve the efficiency and objectivity of muscle measures allowing for the quantitative monitoring of muscle properties in disorders of and beyond the cervical spine.
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Affiliation(s)
- Kenneth A Weber
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA, USA.
| | - Andrew C Smith
- School of Physical Therapy, Regis University, Denver, CO, USA
| | - Marie Wasielewski
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Kamran Eghtesad
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA, USA
| | - Pranav A Upadhyayula
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA, USA
| | - Max Wintermark
- Department of Radiology, Neuroradiology Section, Stanford University, Palo Alto, CA, USA
| | - Trevor J Hastie
- Statistics Department, Stanford University, Palo Alto, CA, USA
| | - Todd B Parrish
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Sean Mackey
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA, USA
| | - James M Elliott
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Honorary Senior Fellow, School of Health and Rehabilitation Sciences, The University of Queensland, Queensland, Australia
- Northern Sydney Local Health District, The Kolling Research Institute and The Faculty of Health Sciences, The University of Sydney, St. Leonards, NSW, Australia
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8
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Leung DG. Advancements in magnetic resonance imaging-based biomarkers for muscular dystrophy. Muscle Nerve 2019; 60:347-360. [PMID: 31026060 DOI: 10.1002/mus.26497] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/23/2019] [Indexed: 12/26/2022]
Abstract
Recent years have seen steady progress in the identification of genetic muscle diseases as well as efforts to develop treatment for these diseases. Consequently, sensitive and objective new methods are required to identify and monitor muscle pathology. Magnetic resonance imaging offers multiple potential biomarkers of disease severity in the muscular dystrophies. This Review uses a pathology-based approach to examine the ways in which MRI and spectroscopy have been used to study muscular dystrophies. Methods that have been used to quantitate intramuscular fat, edema, fiber orientation, metabolism, fibrosis, and vascular perfusion are examined, and this Review describes how MRI can help diagnose these conditions and improve upon existing muscle biomarkers by detecting small increments of disease-related change. Important challenges in the implementation of imaging biomarkers, such as standardization of protocols and validating imaging measurements with respect to clinical outcomes, are also described.
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Affiliation(s)
- Doris G Leung
- Center for Genetic Muscle Disorders, Hugo W. Moser Research Institute at Kennedy Krieger Institute, 716 North Broadway, Room 411, Baltimore, Maryland, 21205.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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