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Liang W, Liu Y, Zhao Y, Chen Y, Yin Y, Zhai L, Li Z, Gong Z, Zhang J, Zhang M. Quantitative MRI Analysis of Brachial Plexus and Limb-Girdle Muscles in Upper Extremity Onset Amyotrophic Lateral Sclerosis. J Magn Reson Imaging 2024; 60:291-301. [PMID: 37767949 DOI: 10.1002/jmri.29027] [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: 07/20/2023] [Revised: 09/14/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Recent evidence highlights the potential of axonal degeneration as a biomarker for amyotrophic lateral sclerosis (ALS) detection. However, the diagnostic potential of peripheral nerve axon changes in ALS remains unclear. PURPOSE To evaluate the diagnostic performance of quantitative MRI of the brachial plexus and limb-girdle muscles (LGMs) in patients with upper extremity onset of ALS. STUDY TYPE Retrospective. POPULATION 47 patients with upper extremity onset of ALS and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE 3-T, three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions with short-tau inversion recovery sequences, T2-weighted turbo spin-echo Dixon sequence. ASSESSMENT The cross-sectional area (CSA) and nerve-muscle T2 signal intensity ratio (nT2) of the bilateral brachial plexus as well as the CSA and fat fraction (FF) of the bilateral LGMs were assessed by two radiologists. Disease severity and clinical stage of ALS patients were assessed by two neurologists. STATISTICAL TESTS Student's t-test, Wilcoxon rank-sum test, binary logistic regression, interclass correlation coefficient, receiver operating characteristic analysis, and correlation analysis were performed for MRI quantitative metrics and clinical variables. Significance level: P < 0.05. RESULTS In the affected limbs of patients with ALS, the CSA of the brachial plexus roots, trunks, and cords and the nT2 values of the brachial plexus trunks were significantly smaller than in the healthy controls. In the LGMs, the affected limbs of ALS showed significantly smaller CSA and higher FF than controls. The model containing parameters such as brachial plexus trunk CSA, subscapularis CSA, infraspinatus CSA, and subscapularis FF had excellent diagnostic efficacy for ALS. Additionally, increased subscapularis FF and supraspinatus FF were correlated with disease severity, and subscapularis CSA was negatively correlated with the clinical stage. DATA CONCLUSION Brachial plexus thinning, LGM atrophy, and fatty infiltration might serve as MRI-derived biomarkers for ALS with upper extremity onset. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Weiqiang Liang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Liu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yali Zhao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yangyang Yin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linhan Zhai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zehui Li
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhenxiang Gong
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Bolano-Diaz C, Verdú-Díaz J, Gonzalez-Chamorro A, Fitzsimmons S, Veeranki G, Straub V, Diaz-Manera J. Magnetic resonance imaging-based criteria to differentiate dysferlinopathy from other genetic muscle diseases. Neuromuscul Disord 2024; 34:54-60. [PMID: 38007344 DOI: 10.1016/j.nmd.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 11/27/2023]
Abstract
The identification of disease-characteristic patterns of muscle fatty replacement in magnetic resonance imaging (MRI) is helpful for diagnosing neuromuscular diseases. In the Clinical Outcome Study of Dysferlinopathy, eight diagnostic rules were described based on MRI findings. Our aim is to confirm that they are useful to differentiate dysferlinopathy (DYSF) from other genetic muscle diseases (GMD). The rules were applied to 182 MRIs of dysferlinopathy patients and 1000 MRIs of patients with 10 other GMD. We calculated sensitivity (S), specificity (Sp), positive and negative predictive values (PPV/NPV) and accuracy (Ac) for each rule. Five of the rules were more frequently met by the DYSF group. Patterns observed in patients with FKRP, ANO5 and CAPN3 myopathies were similar to the DYSF pattern, whereas patterns observed in patients with OPMD, laminopathy and dystrophinopathy were clearly different. We built a model using the five criteria more frequently met by DYSF patients that obtained a S 95.9%, Sp 46.1%, Ac 66.8%, PPV 56% and NPV 94% to distinguish dysferlinopathies from other diseases. Our findings support the use of MRI in the diagnosis of dysferlinopathy, but also identify the need to externally validate "disease-specific" MRI-based diagnostic criteria using MRIs of other GMD patients.
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Affiliation(s)
- Carla Bolano-Diaz
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - José Verdú-Díaz
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - Alejandro Gonzalez-Chamorro
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - Sam Fitzsimmons
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - Gopi Veeranki
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - Volker Straub
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK
| | - Jordi Diaz-Manera
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, NE13BZ, UK; Laboratori de Malalties Neuromusculars, Insitut de Recerca de l'Hospital de la Santa Creu i Sant Pau de Barcelona, Barcelona 08041, Spain; Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), Madrid 28029, Spain.
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Song Y, Xu K, Xu HY, Guo YK, Xu R, Fu H, Yuan WF, Zhou ZQ, Xu T, Chen XJ, Wang YL, Fu C, Zhou H, Cai XT, Li XS. Longitudinal changes in magnetic resonance imaging biomarkers of the gluteal muscle groups and functional ability in Duchenne muscular dystrophy: a 12-month cohort study. Pediatr Radiol 2023; 53:2672-2682. [PMID: 37889296 PMCID: PMC10697878 DOI: 10.1007/s00247-023-05791-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 10/08/2023] [Accepted: 10/09/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Quantitative magnetic resonance imaging (MRI) is considered an objective biomarker of Duchenne muscular dystrophy (DMD), but the longitudinal progression of MRI biomarkers in gluteal muscle groups and their predictive value for future motor function have not been described. OBJECTIVE To explore MRI biomarkers of the gluteal muscle groups as predictors of motor function decline in DMD by characterizing the progression over 12 months. MATERIALS AND METHODS A total of 112 participants with DMD were enrolled and underwent MRI examination of the gluteal muscles to determine fat fraction and longitudinal relaxation time (T1). Investigations were based on gluteal muscle groups including flexors, extensors, adductors, and abductors. The North Star Ambulatory Assessment and timed functional tests were performed. All participants returned for follow-up at an average of 12 months and were divided into two subgroups (functional stability/decline groups) based on changes in timed functional tests. Univariable and multivariable logistic regression methods were used to explore the risk factors associated with future motor function decline. RESULTS For the functional decline group, all T1 values decreased, while fat fraction values increased significantly over 12 months (P<0.05). For the functional stability group, only the fat fraction of the flexors and abductors increased significantly over 12 months (P<0.05). The baseline T1 value was positively correlated with North Star Ambulatory Assessment and negatively correlated with timed functional tests at the 12-month follow-up (P<0.001), while the baseline fat fraction value was negatively correlated with North Star Ambulatory Assessment and positively correlated with timed functional tests at the 12-month follow-up (P<0.001). Multivariate regression showed that increased fat fraction of the abductors was associated with future motor function decline (model 1: odds ratio [OR]=1.104, 95% confidence interval [CI]: 1.026~1.187, P=0.008; model 2: OR=1.085, 95% CI: 1.013~1.161, P=0.019), with an area under the curve of 0.874. CONCLUSION Fat fraction of the abductors is a powerful predictor of future motor functional decline in DMD patients at 12 months, underscoring the importance of focusing early on this parameter in patients with DMD.
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Affiliation(s)
- Yu Song
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Ke Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hua-Yan Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Ying-Kun Guo
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Rong Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hang Fu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Wei-Feng Yuan
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Zi-Qi Zhou
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Ting Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Xi-Jian Chen
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Yi-Lei Wang
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Chuan Fu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hui Zhou
- Department of Rehabilitation Medicine, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Xiao-Tang Cai
- Department of Rehabilitation Medicine, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Xue-Sheng Li
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
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Wei P, Zhong H, Xie Q, Li J, Luo S, Guan X, Liang Z, Yue D. Machine learning-based radiomics to differentiate immune-mediated necrotizing myopathy from limb-girdle muscular dystrophy R2 using MRI. Front Neurol 2023; 14:1251025. [PMID: 37936913 PMCID: PMC10627227 DOI: 10.3389/fneur.2023.1251025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/09/2023] [Indexed: 11/09/2023] Open
Abstract
Objectives This study aimed to assess the feasibility of a machine learning-based radiomics tools to discriminate between Limb-girdle muscular dystrophy R2 (LGMDR2) and immune-mediated necrotizing myopathy (IMNM) using lower-limb muscle magnetic resonance imaging (MRI) examination. Methods After institutional review board approval, 30 patients with genetically proven LGMDR2 (12 females; age, 34.0 ± 11.3) and 45 patients with IMNM (28 females; age, 49.2 ± 16.6) who underwent lower-limb MRI examination including T1-weighted and interactive decomposition water and fat with echos asymmetric and least-squares estimation (IDEAL) sequences between July 2014 and August 2022 were included. Radiomics features of muscles were obtained, and four machine learning algorithms were conducted to select the optimal radiomics classifier for differential diagnosis. This selected algorithm was performed to construct the T1-weighted (TM), water-only (WM), or the combined model (CM) for calf-only, thigh-only, or the calf and thigh MR images, respectively. And their diagnostic performance was studied using area under the curve (AUC) and compared to the semi-quantitative model constructed by the modified Mercuri scale of calf and thigh muscles scored by two radiologists specialized in musculoskeletal imaging. Results The logistic regression (LR) model was the optimal radiomics model. The performance of the WM and CM for thigh-only images (AUC 0.893, 0.913) was better than those for calf-only images (AUC 0.846, 0.880) except the TM. For "calf + thigh" images, the TM, WM, and CM models always performed best (AUC 0.953, 0.907, 0.953) with excellent accuracy (92.0, 84.0, 88.0%). The AUCs of the Mercuri model of the calf, thigh, and "calf + thigh" images were 0.847, 0.900, and 0.953 with accuracy (84.0, 84.0, 88.0%). Conclusion Machine learning-based radiomics models can differentiate LGMDR2 from IMNM, performing better than visual assessment. The model built by combining calf and thigh images presents excellent diagnostic efficiency.
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Affiliation(s)
- Ping Wei
- Department of Radiology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
| | - Huahua Zhong
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Qian Xie
- Department of Radiology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
| | - Jin Li
- Department of Radiology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
| | - Sushan Luo
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xueni Guan
- Department of Radiology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
| | - Zonghui Liang
- Department of Radiology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
| | - Dongyue Yue
- Department of Neurology, Jing’an District Center Hospital of Shanghai, Fudan University, Shanghai, China
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de Visser M, Carlier P, Vencovský J, Kubínová K, Preusse C. 255th ENMC workshop: Muscle imaging in idiopathic inflammatory myopathies. 15th January, 16th January and 22nd January 2021 - virtual meeting and hybrid meeting on 9th and 19th September 2022 in Hoofddorp, The Netherlands. Neuromuscul Disord 2023; 33:800-816. [PMID: 37770338 DOI: 10.1016/j.nmd.2023.08.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 08/20/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
The 255th ENMC workshop on Muscle Imaging in Idiopathic Inflammatory myopathies (IIM) aimed at defining recommendations concerning the applicability of muscle imaging in IIM. The workshop comprised of clinicians, researchers and people living with myositis. We aimed to achieve consensus on the following topics: a standardized protocol for the evaluation of muscle images in various types of IIMs; the exact parameters, anatomical localizations and magnetic resonance imaging (MRI) techniques; ultrasound as assessment tool in IIM; assessment methods; the pattern of muscle involvement in IIM subtypes; the application of MRI as biomarker in follow-up studies and clinical trials, and the place of MRI in the evaluation of swallowing difficulty and cardiac manifestations. The following recommendations were formulated: In patients with suspected IIM, muscle imaging is highly recommended to be part of the initial diagnostic workup and baseline assessment. MRI is the preferred imaging modality due to its sensitivity to both oedema and fat accumulation. Ultrasound may be used for suspected IBM. Repeat imaging should be considered if patients do not respond to treatment, if there is ongoing diagnostic uncertainty or there is clinical or laboratory evidence of disease relapse. Quantitative MRI is established as a sensitive biomarker in IBM and could be included as a primary or secondary outcome measure in early phase clinical trials, or as a secondary outcome measure in late phase clinical trials. Finally, a research agenda was drawn up.
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Affiliation(s)
- Marianne de Visser
- Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Centre, Location Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
| | | | - Jiří Vencovský
- Institute of Rheumatology, Department of Rheumatology, Charles University, Prague, Czech Republic
| | - Kateřina Kubínová
- Institute of Rheumatology, Department of Rheumatology, Charles University, Prague, Czech Republic
| | - Corinna Preusse
- Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Department of Neuropathology, Berlin, Germany
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Engelke K, Chaudry O, Gast L, Eldib MAB, Wang L, Laredo JD, Schett G, Nagel AM. Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translat 2023; 42:57-72. [PMID: 37654433 PMCID: PMC10465967 DOI: 10.1016/j.jot.2023.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 07/04/2023] [Accepted: 07/19/2023] [Indexed: 09/02/2023] Open
Abstract
Background Magnetic resonance imaging (MRI) is the dominant 3D imaging modality to quantify muscle properties in skeletal muscle disorders, in inherited and acquired muscle diseases, and in sarcopenia, in cachexia and frailty. Methods This review covers T1 weighted and Dixon sequences, introduces T2 mapping, diffusion tensor imaging (DTI) and non-proton MRI. Technical concepts, strengths, limitations and translational aspects of these techniques are discussed in detail. Examples of clinical applications are outlined. For comparison 31P-and 13C-MR Spectroscopy are also addressed. Results MRI technology provides a rich toolset to assess muscle deterioration. In addition to classical measures such as muscle atrophy using T1 weighted imaging and fat infiltration using Dixon sequences, parameters characterizing inflammation from T2 maps, tissue sodium using non-proton MRI techniques or concentration or fiber architecture using diffusion tensor imaging may be useful for an even earlier diagnosis of the impairment of muscle quality. Conclusion Quantitative MRI provides new options for muscle research and clinical applications. Current limitations that also impair its more widespread use in clinical trials are lack of standardization, ambiguity of image segmentation and analysis approaches, a multitude of outcome parameters without a clear strategy which ones to use and the lack of normal data.
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Affiliation(s)
- Klaus Engelke
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Institute of Medical Physics (IMP), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Henkestr. 91, 91052, Erlangen, Germany
- Clario Inc, Germany
| | - Oliver Chaudry
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Lena Gast
- Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany
| | | | - Ling Wang
- Department of Radiology, Beijing Jishuitan Hospital, Beijing, China
| | - Jean-Denis Laredo
- Service d’Imagerie Médicale, Institut Mutualiste Montsouris & B3OA, UMR CNRS 7052, Inserm U1271 Université de Paris-Cité, Paris, France
| | - Georg Schett
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Armin M. Nagel
- Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
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Song Y, Xu HY, Xu K, Guo YK, Xie LJ, Peng F, Xu R, Fu H, Yuan WF, Zhou ZQ, Cheng BC, Fu C, Zhou H, Cai XT, Li XS. Clinical utilisation of multimodal quantitative magnetic resonance imaging in investigating muscular damage in Duchenne muscular dystrophy: a study on the association between gluteal muscle groups and motor function. Pediatr Radiol 2023; 53:1648-1658. [PMID: 36892624 PMCID: PMC10359373 DOI: 10.1007/s00247-023-05632-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/03/2023] [Accepted: 02/13/2023] [Indexed: 03/10/2023]
Abstract
BACKGROUND Duchenne muscular dystrophy (DMD) is a neuromuscular disease characterised by progressive muscular weakness and atrophy. Currently, studies on DMD muscle function mostly focus on individual muscles; little is known regarding the effect of gluteal muscle group damage on motor function. OBJECTIVE To explore potential imaging biomarkers of hip and pelvic muscle groups for measuring muscular fat replacement and inflammatory oedema in DMD with multimodal quantitative magnetic resonance imaging (MRI). MATERIALS AND METHODS One hundred fifty-nine DMD boys and 32 healthy male controls were prospectively included. All subjects underwent MRI examination of the hip and pelvic muscles with T1 mapping, T2 mapping and Dixon sequences. Quantitatively measured parameters included longitudinal relaxation time (T1), transverse relaxation time (T2) and fat fraction. Investigations were all based on hip and pelvic muscle groups covering flexors, extensors, adductors and abductors. The North Star Ambulatory Assessment and stair climbing tests were used to measure motor function in DMD. RESULTS T1 of the extensors (r = 0.720, P < 0.01), flexors (r = 0.558, P < 0.01) and abductors (r = 0.697, P < 0.001) were positively correlated with the North Star Ambulatory Assessment score. In contrast, T2 of the adductors (r = -0.711, P < 0.01) and fat fraction of the extensors (r = -0.753, P < 0.01) were negatively correlated with the North Star Ambulatory Assessment score. Among them, T1 of the abductors (b = 0.013, t = 2.052, P = 0.042), T2 of the adductors (b = -0.234, t = -2.554, P = 0.012) and fat fraction of the extensors (b = -0.637, t = - 4.096, P < 0.001) significantly affected the North Star Ambulatory Assessment score. Moreover, T1 of the abductors was highly predictive for identifying motor dysfunction in DMD, with an area under the curve of 0.925. CONCLUSION Magnetic resonance biomarkers of hip and pelvic muscle groups (particularly T1 values of the abductor muscles) have the potential to be used as independent risk factors for motor dysfunction in DMD.
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Affiliation(s)
- Yu Song
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hua-Yan Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Ke Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Ying-Kun Guo
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Lin-Jun Xie
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Fei Peng
- Department of Radiology, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Rong Xu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hang Fu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Wei-Feng Yuan
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Zi-Qi Zhou
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Bo-Chao Cheng
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Chuan Fu
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Hui Zhou
- Department of Rehabilitation, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Xiao-Tang Cai
- Department of Rehabilitation, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Xue-Sheng Li
- Department of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
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Abstract
PURPOSE OF REVIEW To discuss recent developments in our understanding of epidemiology, diagnostics, biomarkers, pathology, pathogenesis, outcome measures, and therapeutics in inclusion body myositis (IBM). RECENT FINDINGS Recent epidemiology data confirms a relatively higher prevalence in the population aged above 50 years and the reduced life expectancy. Association with cancer and other systemic disorders is better defined. The role of magnetic resonance imaging (MRI) and ultrasound in diagnosis as well as in following disease progression has been elucidated. There are new blood and imaging biomarkers that show tremendous promise for diagnosis and as outcome measures in therapeutic trials. Improved understanding of the pathogenesis of the disease will lead to better therapeutic interventions, but also highlights the importance to have sensitive and responsive outcome measures that accurately quantitate change. SUMMARY There are exciting new developments in our understanding of IBM which should lead to improved management and therapeutic options.
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Affiliation(s)
- Mari Perez-Rosendahl
- Department of Pathology & Laboratory Medicine, School of Medicine, University of California, Irvine
| | - Tahseen Mozaffar
- Department of Pathology & Laboratory Medicine, School of Medicine, University of California, Irvine
- Department of Neurology, School of Medicine, University of California, Irvine
- Institute for Immunology, School of Medicine, University of California, Irvine
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9
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De Wel B, Huysmans L, Peeters R, Goosens V, Ghysels S, Byloos K, Putzeys G, D'Hondt A, De Bleecker JL, Dupont P, Maes F, Claeys KG. Prospective Natural History Study in 24 Adult Patients With LGMDR12 Over 2 Years of Follow-up: Quantitative MRI and Clinical Outcome Measures. Neurology 2022; 99:e638-e649. [PMID: 35577579 DOI: 10.1212/wnl.0000000000200708] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 03/24/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Limb-girdle muscular dystrophy autosomal recessive type 12 (LGMDR12) is a rare hereditary muscular dystrophy for which outcome measures are currently lacking. We evaluated quantitative MRI and clinical outcome measures to track disease progression to determine which tests could be useful in future clinical trials to evaluate potential therapies. METHODS We prospectively measured the following outcome measures in all participants at baseline and after 1 and 2 years: 6-minute walk distance (6MWD), 10-meter walk test (10MWT), the Medical Research Council (MRC) sum scores, Biodex isometric dynamometry, serum creatine kinase, and 6-point Dixon MRI of the thighs. RESULTS We included 24 genetically confirmed, adult patients with LGMDR12 and 24 age-matched and sex-matched healthy controls. Patients with intermediate-stage thigh muscle fat replacement at baseline (proton density fat fraction [PDFF] 20%-70%) already showed an increase in PDFF in 8 of the 14 evaluated thigh muscles after 1 year. The standardized response mean demonstrated a high responsiveness to change in PDFF for 6 individual muscles over 2 years in this group. However, in patients with early-stage (<20%) or end-stage (>70%) muscle fat replacement, PDFF did not increase significantly over 2 years of follow-up. Biodex isometric dynamometry showed a significant decrease in muscle strength in all patients in the right and left hamstrings (-6.2 Nm, p < 0.002 and -4.6 Nm, p < 0.009, respectively) and right quadriceps muscles (-9 Nm, p = 0.044) after 1 year of follow-up, whereas the 6MWD, 10MWT, and MRC sum scores were not able to detect a significant decrease in muscle function/strength even after 2 years. There was a moderately strong correlation between total thigh PDFF and clinical outcome measures at baseline. DISCUSSION Thigh muscle PDFF imaging is a sensitive outcome measure to track progressive muscle fat replacement in selected patients with LGMDR12 even after 1 year of follow-up and correlates with clinical outcome measures. Biodex isometric dynamometry can reliably capture the loss of muscle strength over the course of 1 year in patients with LGMDR12 and should be included as an outcome measure in future clinical trials as well.
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Affiliation(s)
- Bram De Wel
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Lotte Huysmans
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Ronald Peeters
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Veerle Goosens
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Stefan Ghysels
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Kris Byloos
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Guido Putzeys
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Ann D'Hondt
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Jan L De Bleecker
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Patrick Dupont
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Frederik Maes
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium
| | - Kristl G Claeys
- From the Departments of Neurology (B.D.W., A.D.H., K.G.C.) and Radiology (R.P., V.G., S.G., K.B., G.P.), and Medical Imaging Research Centre (L.H., F.M.), University Hospitals Leuven; Laboratories for Muscle Diseases and Neuropathies (B.D.W., K.G.C.) and Cognitive Neurology (P.D.), Department of Neurosciences, and Department ESAT-PSI (L.H., F.M.), KU Leuven; Leuven Brain Institute (LBI) (B.D.W., K.G.C., P.D.); and Department of Neurology (J.L.D.B.), University Hospital Gent, Belgium.
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10
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Albayda J, Demonceau G, Carlier PG. Muscle imaging in myositis: MRI, US, and PET. Best Pract Res Clin Rheumatol 2022; 36:101765. [PMID: 35760742 DOI: 10.1016/j.berh.2022.101765] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Imaging is an important tool in the evaluation of idiopathic inflammatory myopathies. It plays a role in diagnosis, assessment of disease activity and follow-up, and as a non-invasive biomarker. Among the different modalities, nuclear magnetic resonance imaging (MRI), ultrasound (US), and positron emission tomography (PET) may have the most clinical utility in myositis. MRI is currently the best modality to evaluate skeletal muscle and provides excellent characterization of muscle edema and fat replacement through the use of T1-weighted and T2-weighted fat suppressed/STIR sequences. Although MRI can be read qualitatively for the presence of abnormalities, a more quantitative approach using Dixon sequences and the generation of water T2 parametric maps would be preferable for follow-up. Newer protocols such as diffusion-weighted imaging, functional imaging measures, and spectroscopy may be of interest to provide further insights into myositis. Despite the advantages of MRI, image acquisition is relatively time-consuming, expensive, and not accessible to all patients. The use of US to evaluate skeletal muscle in myositis is gaining interest, especially in chronic disease, where fat replacement and fibrosis are detected readily by this modality. Although easily deployed at the bedside, it is heavily dependent on operator experience to recognize disease states. Further, systematic characterization of muscle edema by US is still needed. PET provides valuable information on muscle function at a cellular level. Fluorodeoxyglucose (FDG-PET) has been the most common application in myositis to detect pathologic uptake indicative of inflammation. The use of neurodegenerative markers is now also being utilized for inclusion body myositis. These different modalities may prove to be complementary methods for myositis evaluation.
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Affiliation(s)
- Jemima Albayda
- Division of Rheumatology, Johns Hopkins University, Baltimore, USA.
| | | | - Pierre G Carlier
- Université Paris-Saclay, CEA, DRF, Service Hospitalier Frederic Joliot, Orsay, France
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11
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Upper body involvement in GNE myopathy assessed by muscle imaging. Neuromuscul Disord 2022; 32:410-418. [DOI: 10.1016/j.nmd.2021.12.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 12/16/2021] [Accepted: 12/29/2021] [Indexed: 11/19/2022]
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12
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Alonso-Jiménez A, Nuñez-Peralta C, Montesinos P, Alonso-Pérez J, García C, Montiel E, Belmonte I, Pedrosa I, Segovia S, Llauger J, Díaz-Manera J. Different Approaches to Analyze Muscle Fat Replacement With Dixon MRI in Pompe Disease. Front Neurol 2021; 12:675781. [PMID: 34305788 PMCID: PMC8298190 DOI: 10.3389/fneur.2021.675781] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/08/2021] [Indexed: 12/13/2022] Open
Abstract
Quantitative MRI is an increasingly used method to monitor disease progression in muscular disorders due to its ability to measure changes in muscle fat content (reported as fat fraction) over a short period. Being able to objectively measure such changes is crucial for the development of new treatments in clinical trials. However, the analysis of the images involved continues to be a daunting task because of the time needed. Whether a more specific analysis selecting individual muscles or a global one analyzing the whole thigh or compartments could be a suitable alternative has only been marginally studied. In our study we compare three methods of analysis of 2-point-dixon images in a cohort of 34 patients with late onset Pompe disease followed over a period of one year. We measured fat fraction on MRIs obtained at baseline and at year 1, and we calculated the increment of fat fraction. We correlated the results obtained with the results of muscle function tests to investigate whether the three methods of analysis were equivalent or not. We observed significant differences between the three methods in the estimation of the fat fraction at both baseline and year 1, but no difference was found in the increment in fat fraction between baseline and year 1. When we correlated the fat fraction obtained with each method and the muscle function tests, we found a significant correlation with most tests in all three methods, although in most comparisons the highest correlation coefficient was found with the analysis of individual muscles. We conclude that the fastest strategy of analysis assessing compartments or the whole thigh could be reliable for certain cohorts of patients where the variable to study is the fat increment. In other sorts of studies, an individual muscle approach seems the most reliable technique.
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Affiliation(s)
- Alicia Alonso-Jiménez
- Neuromuscular Disorders Unit, Neurology Department, Departament de Medicina, Hospital de la Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Neuromuscular Reference Center, Neurology Department, University Hospital of Antwerp, Edegem, Belgium
| | - Claudia Nuñez-Peralta
- Radiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Jorge Alonso-Pérez
- Neuromuscular Disorders Unit, Neurology Department, Departament de Medicina, Hospital de la Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Biomedical Network Research Centre on Rare Diseases (CIBERER), Barcelona, Spain
| | - Carme García
- Rehabilitation and Physiotherapy Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Elena Montiel
- Rehabilitation and Physiotherapy Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Izaskun Belmonte
- Rehabilitation and Physiotherapy Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Irene Pedrosa
- Rehabilitation and Physiotherapy Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sonia Segovia
- Neuromuscular Disorders Unit, Neurology Department, Departament de Medicina, Hospital de la Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Biomedical Network Research Centre on Rare Diseases (CIBERER), Barcelona, Spain
| | - Jaume Llauger
- Radiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jordi Díaz-Manera
- Neuromuscular Disorders Unit, Neurology Department, Departament de Medicina, Hospital de la Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Biomedical Network Research Centre on Rare Diseases (CIBERER), Barcelona, Spain.,John Walton Muscular Dystrophy Research Centre, Newcastle University, International Centre for Life, Newcastle upon Tyne, United Kingdom
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13
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van de Velde NM, Hooijmans MT, Sardjoe Mishre ASD, Keene KR, Koeks Z, Veeger TTJ, Alleman I, van Zwet EW, Beenakker JWM, Verschuuren JJGM, Kan HE, Niks EH. Selection Approach to Identify the Optimal Biomarker Using Quantitative Muscle MRI and Functional Assessments in Becker Muscular Dystrophy. Neurology 2021; 97:e513-e522. [PMID: 34162720 PMCID: PMC8356376 DOI: 10.1212/wnl.0000000000012233] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 04/29/2021] [Indexed: 12/30/2022] Open
Abstract
Objective To identify the best quantitative fat–water MRI biomarker for disease progression of leg muscles in Becker muscular dystrophy (BMD) by applying a stepwise approach based on standardized response mean (SRM) over 24 months, correlations with baseline ambulatory tests, and reproducibility. Methods Dixon fat–water imaging was performed at baseline (n = 24) and 24 months (n = 20). Fat fractions (FF) were calculated for 3 center slices and the whole muscles for 19 muscles and 6 muscle groups. Contractile cross-sectional area (cCSA) was obtained from the center slice. Functional assessments included knee extension and flexion force and 3 ambulatory tests (North Star Ambulatory Assessment [NSAA], 10-meter run, 6-minute walking test). MRI measures were selected using SRM (≥0.8) and correlation with all ambulatory tests (ρ ≤ −0.8). Measures were evaluated based on intraclass correlation coefficient (ICC) and SD of the difference. Sample sizes were calculated assuming 50% reduction in disease progression over 24 months in a clinical trial with 1:1 randomization. Results Median whole muscle FF increased between 0.2% and 2.6% without consistent cCSA changes. High SRMs and strong functional correlations were found for 8 FF but no cCSA measures. All measures showed excellent ICC (≥0.999) and similar SD of the interrater difference. Whole thigh 3 center slices FF was the best biomarker (SRM 1.04, correlations ρ ≤ −0.81, ICC 1.00, SD 0.23%, sample size 59) based on low SD and acquisition and analysis time. Conclusion In BMD, median FF of all muscles increased over 24 months. Whole thigh 3 center slices FF reduced the sample size by approximately 40% compared to NSAA.
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Affiliation(s)
- Nienke M van de Velde
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Melissa T Hooijmans
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Aashley S D Sardjoe Mishre
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Kevin R Keene
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Zaïda Koeks
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Thom T J Veeger
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Iris Alleman
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Erik W van Zwet
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Jan-Willem M Beenakker
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Jan J G M Verschuuren
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Hermien E Kan
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands
| | - Erik H Niks
- From the Department of Neurology (N.M.v.d.V., K.R.K., Z.K., J.J.G.M.V., E.H.N.), C.J. Gorter Center for High-Field MRI, Department of Radiology (M.T.H., A.S.D.S.M., K.R.K., T.T.J.V., J.-W.M.B., H.E.K.), Department of Orthopaedics, Rehabilitation and Physical Therapy (I.A.), Department of Biomedical Data Sciences (E.W.v.Z.), and Department of Ophthalmology (J.-W.M.B.), Leiden University Medical Center, the Netherlands; and Duchenne Center Netherlands (N.M.v.d.V., J.J.G.M.V., H.E.K., E.H.N.), the Netherlands.
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14
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Malartre S, Bachasson D, Mercy G, Sarkis E, Anquetil C, Benveniste O, Allenbach Y. MRI and muscle imaging for idiopathic inflammatory myopathies. Brain Pathol 2021; 31:e12954. [PMID: 34043260 PMCID: PMC8412099 DOI: 10.1111/bpa.12954] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 03/11/2021] [Indexed: 12/22/2022] Open
Abstract
Although idiopathic inflammatory myopathies (IIM) are a heterogeneous group of diseases nearly all patients display muscle inflammation. Originally, muscle biopsy was considered as the gold standard for IIM diagnosis. The development of muscle imaging led to revisiting not only the IIM diagnosis strategy but also the patients' follow-up. Different techniques have been tested or are in development for IIM including positron emission tomography, ultrasound imaging, ultrasound shear wave elastography, though magnetic resonance imaging (MRI) remains the most widely used technique in routine. Whereas guidelines on muscle imaging in myositis are lacking here we reviewed the relevance of muscle imaging for both diagnosis and myositis patients' follow-up. We propose recommendations about when and how to perform MRI on myositis patients, and we describe new techniques that are under development.
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Affiliation(s)
- Samuel Malartre
- Department of Internal Medicine and Clinical Immunlogy, Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Centre de Recherche en Myologie, UMRS974, Association Institut de Myologie, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Paris, France
| | - Damien Bachasson
- Neuromuscular Physiology Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France
| | - Guillaume Mercy
- Department of Medical Imaging, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière-Charles-Foix, Sorbonne Université, Paris, France
| | - Elissone Sarkis
- Department of Internal Medicine and Clinical Immunlogy, Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Centre de Recherche en Myologie, UMRS974, Association Institut de Myologie, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Paris, France
| | - Céline Anquetil
- Department of Internal Medicine and Clinical Immunlogy, Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Centre de Recherche en Myologie, UMRS974, Association Institut de Myologie, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Paris, France
| | - Olivier Benveniste
- Department of Internal Medicine and Clinical Immunlogy, Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Centre de Recherche en Myologie, UMRS974, Association Institut de Myologie, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Paris, France
| | - Yves Allenbach
- Department of Internal Medicine and Clinical Immunlogy, Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Centre de Recherche en Myologie, UMRS974, Association Institut de Myologie, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Paris, France
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