Preferential changes of skeletal muscle echogenicity in myotonic dystrophy type 1

Takamatsu, Naoko; Sogawa, Kazuki; Nodera, Hiroyuki; Hashiguchi, Shuji; Osaki, Yusuke; Saito, Miho; Mori, Atsuko; Izumi, Yuishin; Kaji, Ryuji

doi:10.1111/ene.13212

Cited by 5 publications

(4 citation statements)

References 19 publications

(27 reference statements)

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“…Other muscles that are more severely affected in respective myopathies might provide more useful data. Of note, however, we have reported that gastrocnemius is one of the most severely affected muscles in IBM and DM1, (5,6) but obviously thigh and shoulder-girdle muscles should be more representative of abnormality in PM/DM.…”

Section: Study Limitationsmentioning

confidence: 77%

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Texture analysis of sonographic muscle images can distinguish myopathic conditions

et al. 2019

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Given the recent technological advent of muscle ultrasound (US), classification of various myopathic conditions could be possible, especially by mathematical analysis of muscular fine structure called texture analysis. We prospectively enrolled patients with three neuromuscular conditions and their lower leg US images were quantitatively analyzed by texture analysis and machine learning methodology in the following subjects : Inclusion body myositis (IBM) [N=11] ; myotonic dystrophy type 1 (DM1) [N=19] ; polymyositis/dermatomyositis (PM-DM) [N=21]. Although three-group analysis achieved up to 58.8% accuracy, two-group analysis of IBM plus PM-DM versus DM1 showed 78.4% accuracy. Despite the small number of subjects, texture analysis of muscle US followed by machine learning might be expected to be useful in identifying myopathic conditions. J. Med. Invest. 237Abbreviations DM = dermatomyositis, DM1 = myotonic dystrophy type 1, EI = echointensity, GLCM = gray level co-occurrence matrix, GLNU = graylevel non-uniformity, GLRLM = gray-level run length matrix, GLZLM = gray-level zone length matrix, IBM = inclusion body myositis, NGLDM = neighborhood gray-level different matrix, PM = polymyositis, ROI = region of interest, US = ultrasound

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Section: Study Limitationsmentioning

confidence: 77%

“…As previously reported, IBM and DM1 showed preferential high echodensity regions in the medial gastrocnemius. (5,6) The representative view of LifeX texture analytic system is shown in Figure 2. Based on the calculated texture features as shown in the superimposed spreadsheet, the following analyses were performed.…”

Section: Sonographymentioning

confidence: 99%

Texture analysis of sonographic muscle images can distinguish myopathic conditions

et al. 2019

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“…Hierdurch sind einzelne Muskeln sowie tiefer liegende Knochenstrukturen teilweise gar nicht mehr abgrenzbar. Ähnliche Veränderungen wurden auch bei Patienten mit myotoner Dystrophie Typ I und II berichtet [46,47]. Diese Echogenitätsveränderungen können bei Muskeldystrophien als Verlaufsparameter verwendet werden, da gezeigt wurde, dass sie mit dem klinischen Verlauf korrelieren [48].…”

Section: Muskeldystrophienunclassified

Moderner Ultraschall in der Diagnostik Neuromuskulärer Erkrankungen

Fisse

Pitarokoili

Schreiber

2022

Klinische Neurophysiologie

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ZusammenfassungDer neuromuskuläre Ultraschall hat sich in den letzten Jahren zu einem festen Bestandteil in der neurologischen Diagnostik entwickelt. Dazu tragen auch die fortwährende technische Weiterentwicklung der Methode und ihr unkomplizierter und nebenwirkungsfreier Einsatz direkt am Patienten bei. Im klinischen Alltag wird der Ultraschall in der Diagnostik und Differentialdiagnostik sowie in der Verlaufskontrolle traumatischer Nervenläsionen, sekundärer und dynamischer nervaler Kompressionssyndrome, hereditärer und akuter sowie chronisch autoimmuner Polyneuropathien, Motoneuron- und Muskelerkrankungen verwendet. Dabei spielt die Ultraschalldiagnostik auch zunehmend eine Rolle für Therapieentscheidungen, v.a. im Hinblick auf die operative Versorgung und den Einsatz oder die Fortführung immunmodulatorischer Medikamente. In den nächsten Jahren ist eine weitere interdisziplinäre Verbreitung und fortwährend zunehmende Standardisierung der Methode zu erwarten.

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“…Neuromuscular disorders encompassing primary myopathies, neuropathies and diseases of the neuromuscular junction are together a group of diseases that are often challenging to disentangle diagnostically . Many of these have a genetic basis and novel causative mutations continue to be identified and the clinical phenotype of existing mutations more clearly defined .…”

mentioning

confidence: 99%

Progress in neurology 2017–2018

Schapira

2018

Euro J of Neurology

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Preferential changes of skeletal muscle echogenicity in myotonic dystrophy type 1

Abstract: Preferential high echogenicity in the medial gastrocnemius and deep finger flexors is suggestive of DM1. Muscle echogenicity is not generally related to functional dysfunction in DM1.

Cited by 5 publications

References 19 publications

Texture analysis of sonographic muscle images can distinguish myopathic conditions

Texture analysis of sonographic muscle images can distinguish myopathic conditions

Moderner Ultraschall in der Diagnostik Neuromuskulärer Erkrankungen

Progress in neurology 2017–2018

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