A magnetic resonance image classification system for children with cerebral palsy
10.3760/cma.j.issn.0254-1424.2020.11.004
- VernacularTitle:磁共振成像分类系统在儿童脑性瘫痪中的应用
- Author:
Junying YUAN
1
;
Qingna XING
;
Lihong ZHANG
;
Jie LIU
;
Jiefeng HU
;
Shijie MA
;
Dong LI
;
Kejie CAO
;
Dengna ZHU
;
Jun WANG
Author Information
1. 郑州大学第三附属医院儿童康复科，郑州 450052
- From:
Chinese Journal of Physical Medicine and Rehabilitation
2020;42(11):978-983
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the relationship of risk factors and clinical features to assessments of children with cerebral palsy (CP ) using a magnetic resonance imaging classification system (MRICS).Methods:Medical records of CP patients under 18 years old were reviewed retrospectively. Data including high-risk factors, cranial MRI results and clinical characteristics were collected. The cranial MRI results were classified according to the MRICS.Results:Of 1357 patients studied, 1112 (82%) had received cranial MRI scans. Among them, 962 (86.5%) showed MRI-identified brain abnormalities, 489 in the periventricular white matter. Subjects with different weeks of gestation, birth weights, delivery times, neonatal hypoxic-ischemic encephalopathy, and neonatal cerebral hemorrhage had significantly different MRI classifications according to the system. Premature birth, low birth weight and multiple births correlated with the incidence of white matter brain injury. Only 4 of the subjects with neonatal cerebral hemorrhage were classified as having normal brain structures using the MRICS. However, gender, birth method, and pathological jaundice had no significant relationship with MRICS ratings. Significant differences in MRICS classifications were observed between patients with different CP subtypes, gross motor function scores, as well as with or without epilepsy, speech or language impairment. But degrees of mental retardation were not significantly related with MRICS classifications.Conclusion:MRICS classifications relate closely with risk factors and the clinical characteristics of CP patients. The system can play an important role in finding pathogenesis and predicting clinical outcomes. It is worthy of applying and promoting in the clinic.
