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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Leon de Jong (Radiology & nuclear medicine, Radboudumc)
Anton Nikolaev (Radiology & nuclear medicine, Radboudumc)
Anna Greco (Neurology, Radboudumc)
Jurgen Fütterer (Radiology & nuclear medicine, Radboudumc)
Chris de Korte (radiology & nuclear medicine, Radboudumc)

Abstract:
Purpose: This study focuses on providing new parameters within the diagnostic workup for patients having (a suspicion of) neuromuscular disease. Even though many of these patients show muscle weakness, the underlying mechanism of the disorder varies heavily. Over 600 different types of disorders are known in literature, indicating the need for adequate diagnostics. Myopathy patients form a group of neuromuscular disorders that suffers from mechanical changes in skeletal muscle tissue. In this study, we assess if automated 3D ultrasound can be used to quantify parameters related to these mechanical properties in a healthy population. Study population: 124 healthy volunteers with 11 different nationalities participated in this study; 65 males and 59 females, age 38 ± 16, BMI 21.4 ± 4.3, 12 lefthanded, 110 righthanded 2 ambidexter. Volunteers declared to have no prior medical conditions relevant to this measurement. Method: The overall parameters that were measured prior to the ultrasound examination are; weight, bone mass and water fraction. Segmental parameters (arms/legs/core) are; fat fraction and muscle mass. Medical Research Council (MRC)-scores were acquired by physical examination by a physician and maximum hand grip strength was measured for both hands. Automated 3D ultrasound scans of the tibialis anterior muscle were performed whilst maintaining isometric contractions at 0, 20% and 40% of maximum voluntary contraction (MVC) force. Acquisition planes were in transversal as well as sagittal direction. Results: Initial analysis of 10 subjects show an increasing pennation angle with respect to the initial angle from 1.1° (0-20% MVC) via 1.8° (20-40% MVC) to 3.0° (0-40% MVC), where positive values represent increasing angles. Future implications: This study provides a non-invasive method to assess quantitative parameters that are of interest in the diagnostic track of neuromuscular disorders, especially myopathies. We suggest that the acquired parameters (echogenicity, muscle volume and architecture, fascicle length and pennation angles) of this dataset can be used to investigate disease gradation, progression and treatment effect.