Estimation of Gastrocnemius Muscle Volume Using Ultrasonography in Children with Spastic Cerebral Palsy.
10.3349/ymj.2014.55.4.1115
- Author:
Eun Sook PARK
1
;
Eungeol SIM
;
Dong Wook RHA
;
Soojin JUNG
Author Information
1. Department of Rehabilitation Medicine, Severance Hospital, Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, Korea. werch@yuhs.ac
- Publication Type:Original Article
- Keywords:
Gastrocnemius muscle;
volume;
ultrasound imaging;
magnetic resonance imaging;
cerebral palsy
- MeSH:
Cerebral Palsy/*pathology/ultrasonography;
Child;
Child, Preschool;
Female;
Humans;
Magnetic Resonance Imaging;
Male;
Muscle, Skeletal/*pathology/ultrasonography
- From:Yonsei Medical Journal
2014;55(4):1115-1122
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: This study aimed to investigate useful parameters for estimating gastrocnemius (GCM) muscle volume (MV) using ultrasonography (US) and anthropometry in children with spastic cerebral palsy (CP). MATERIALS AND METHODS: Eighteen legs from nine children with spastic CP aged 2 to 6 years were investigated in this study. Tibial length (TL) of each leg was measured and muscle thickness (MT) and anatomical cross-sectional area (aCSA) of GCM muscles were assessed using US. The volume of the GCM was measured by magnetic resonance imaging (MRI) scans. The relationship of TL, MT, and aCSA with MV measured by MRI was investigated. Simple and multiple regression analyses were performed to establish muscle volume prediction equations. RESULTS: Resting MT, aCSA, and TL were highly related to MV of both medial and lateral head of GCM determined by MRI. The MV prediction equation based on simple regression analysis resulted in r2 values ranging from 0.591 to 0.832 (p<0.05). The r2 values were higher using aCSA as independent variable than using MT. The MV prediction equation based on multiple regression analysis resulted in r2 values ranging from 0.779 to 0.903 (p<0.05). However, the relatively high standard error of the estimate values ranged from 18.0-33.6% on simple regression and 15.5-25.6% on multiple regression. The contribution of aCSA was higher than that of MT for predicting MV of GCM. CONCLUSION: Our study demonstrated the suitability of US assessment of aCSA and MT combined with TL for estimating MV of GCM in children with spastic CP and showed that aCSA is more useful parameter than MT.
