Publication:
Muscle imaging in laminopathies: Synthesis study identifies meaningful muscles for follow-up.

dc.contributor.authorGóMez-Andrés, David
dc.contributor.authorDíaz-Manera, Jordi
dc.contributor.authorAlejaldre, Aida
dc.contributor.authorPulido-Valdeolivas, Irene
dc.contributor.authorGonzáLez-Mera, Laura
dc.contributor.authorOlivé, Montse
dc.contributor.authorVilchez, Juan José
dc.contributor.authorDe Munain, Adolfo LóPez
dc.contributor.authorParadas, Carmen
dc.contributor.authorMuelas, Nuria
dc.contributor.authorSáNchez-MontáÑez, Ángel
dc.contributor.authorAlonso-Jimenez, Alicia
dc.contributor.authorDe la Banda, Marta Gómez García
dc.contributor.authorDabaj, Ivana
dc.contributor.authorBonne, Gisèle
dc.contributor.authorMunell, Francina
dc.contributor.authorCarlier, Robert Y
dc.contributor.authorQuijano-Roy, Susana
dc.date.accessioned2023-01-25T10:21:11Z
dc.date.available2023-01-25T10:21:11Z
dc.date.issued2018-11-18
dc.description.abstractParticular fibroadipose infiltration patterns have been recently described by muscle imaging in congenital and later onset forms of LMNA-related muscular dystrophies (LMNA-RD). Scores for fibroadipose infiltration of 23 lower limb muscles in 34 patients with LMNA-RD were collected from heat maps of 2 previous studies. Scoring systems were homogenized. Relationships between muscle infiltration and disease duration and age of onset were modeled with random forests. The pattern of infiltration differs according to disease duration but not to age of disease onset. The muscles whose progression best predicts disease duration were semitendinosus, biceps femoris long head, gluteus medius, and semimembranosus. In LMNA-RD, our synthetic analysis of lower limb muscle infiltration did not find major differences between forms with different ages of onset but allowed the identification of muscles with characteristic infiltration during disease progression. Monitoring of these specific muscles by quantitative MRI may provide useful imaging biomarkers in LMNA-RD. Muscle Nerve 58:812-817, 2018.
dc.identifier.doi10.1002/mus.26312
dc.identifier.essn1097-4598
dc.identifier.pmid30066418
dc.identifier.unpaywallURLhttps://hal.sorbonne-universite.fr/hal-02297512/file/G%C3%B3Mez%E2%80%90Andr%C3%A9s%20et%20al.%20-%202018%20-%20Muscle%20imaging%20in%20laminopathies%20Synthesis%20study%20i.pdf
dc.identifier.urihttp://hdl.handle.net/10668/12785
dc.issue.number6
dc.journal.titleMuscle & nerve
dc.journal.titleabbreviationMuscle Nerve
dc.language.isoen
dc.organizationHospital Universitario Virgen del Rocío
dc.page.number812-817
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.rights.accessRightsopen access
dc.subjectLMNA, machine learning, magnetic resonance
dc.subjectbiomarker
dc.subjectimaging
dc.subjectlaminopathy
dc.subject.meshAdolescent
dc.subject.meshAdult
dc.subject.meshAged
dc.subject.meshChild
dc.subject.meshCohort Studies
dc.subject.meshDisease Progression
dc.subject.meshExtremities
dc.subject.meshFemale
dc.subject.meshHumans
dc.subject.meshMagnetic Resonance Imaging
dc.subject.meshMale
dc.subject.meshMiddle Aged
dc.subject.meshMuscle, Skeletal
dc.subject.meshMuscular Atrophy, Spinal
dc.subject.meshStatistics, Nonparametric
dc.subject.meshTomography, X-Ray Computed
dc.subject.meshYoung Adult
dc.titleMuscle imaging in laminopathies: Synthesis study identifies meaningful muscles for follow-up.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number58
dspace.entity.typePublication

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