Texture as an imaging biomarker for disease severity in golden retriever muscular dystrophy.
Muscle Nerve
; 59(3): 380-386, 2019 03.
Article
em En
| MEDLINE
| ID: mdl-30461036
ABSTRACT
INTRODUCTION:
Golden retriever muscular dystrophy (GRMD), an X-linked recessive disorder, causes similar phenotypic features to Duchenne muscular dystrophy (DMD). There is currently a need for a quantitative and reproducible monitoring of disease progression for GRMD and DMD.METHODS:
To assess severity in the GRMD, we analyzed texture features extracted from multi-parametric MRI (T1w, T2w, T1m, T2m, and Dixon images) using 5 feature extraction methods and classified using support vector machines.RESULTS:
A single feature from qualitative images can provide 89% maximal accuracy. Furthermore, 2 features from T1w, T2m, or Dixon images provided highest accuracy. When considering a tradeoff between scan-time and computational complexity, T2m images provided good accuracy at a lower acquisition and processing time and effort.CONCLUSIONS:
The combination of MRI texture features improved the classification accuracy for assessment of disease progression in GRMD with evaluation of the heterogenous nature of skeletal muscles as reflection of the histopathological changes. Muscle Nerve 59380-386, 2019.Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Imageamento por Ressonância Magnética
/
Doenças do Cão
/
Distrofia Muscular Animal
Tipo de estudo:
Qualitative_research
Limite:
Animals
Idioma:
En
Revista:
Muscle Nerve
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos