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Imaging Viscoelasticity in Control and Dystrophic Vastus Lateralis using Quantitative Viscoelastic Response (QVisR) Ultrasound
- Source :
- 2019 IEEE International Ultrasonics Symposium (IUS).
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Mechanical property changes associated with inflammation, necrosis, fibrosis, and fatty deposition in dystrophic muscle may be quantitatively evaluated by Quantitative Viscoelastic Response (QVisR) ultrasound. QVisR uses a machine learning (ML) framework that takes as input tissue displacement in response to two consecutive and co-located acoustic radiation force (ARF) excitations and yields as output estimates of shear elastic and shear viscous moduli. QVisR imaging was performed in the vastus lateralis (VL) muscles of 11 boys with Duchenne muscular dystrophy (DMD) aged 5 to 12 years and of 8 age-matched boys with no known neuromuscular disorders, who served as controls. QVisR measures of elastic moduli differed between DMD and control VL in boys aged less than six years and six-to-seven years. Similarly, QVisR measures of viscous moduli differed between DMD and control VL in boys aged six-to-seven years. These results demonstrate that QVisR measures of elastic and viscous moduli differentiate dystrophic from control muscle. The findings suggest that QVisR may be relevant to monitoring dystrophic muscle degeneration and response to intervention, particularly in early stages when interventions are most likely to be impactful.
- Subjects :
- Mechanical property
medicine.medical_specialty
business.industry
Duchenne muscular dystrophy
Ultrasound
Dystrophic muscle
medicine.disease
01 natural sciences
Viscoelasticity
030218 nuclear medicine & medical imaging
Ultrasonic imaging
03 medical and health sciences
0302 clinical medicine
Fibrosis
Internal medicine
0103 physical sciences
medicine
Cardiology
business
010301 acoustics
Control muscle
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 IEEE International Ultrasonics Symposium (IUS)
- Accession number :
- edsair.doi...........f44d5821cd5712837cd5ca2716dba57d