Correlation Analysis Of Morphologic Risk Factors For Spastic Cerebral Palsy In Preterm Children

OBJECTIVE :To analyze the CT imaging data of 87 preterm children with cerebral palsy and study the relationship of the spastic diplegia and correlative element of imaging for ascertaining the risk factors and CT features of spastic cerebral palsy in preterm children.MATIRIALS AND METHODS: CT imaging data of 87 cases (58 boys,29 girls)of preterm children were identified, Their age ranged from 4 to 72 months, means age: 23 months .The data of all cases were divided into 5 series according to the correlative element of imaging : X1 (cortical atrophy ) , X2 ( dilation of ventricles ) , X3 (abnomal gray matter, included abnomal increasement and heterotopia) , X4 ( white matter losing ) , and X5 ( angle of Periventricular white matter ). Statistical analysis was performed using SPSS FOR WINDOWS software. The statistical data were transmitted into the SPSS logistic model for single and multivariable LOGISTIC regression analysis compared with Y (1)(spastic cerebral palsy), the result was performed with hypothesis testing . Result : The statistics conclusion of the binary logistic regressionwere concluded: Abnormal grey matter (OR=8.874), angle of periventrical white matter (OR=4.274) and white matter losing (OR=1.792) were identified as risk factors of spastic cerebral palsy, The statistic conclusion also suggested that abnormal grey matter (OR=8.874) is the highest statistical significance among all elements of opposed factors. On the other hand, the X1(cortical atrophy) and X2 (the size of the ventricles) were not characteristic feature to Y(1)(spastic cerebral palsy), and the factor of age was also removed by logistic regression modle. Conclusion : The heterotopia and abnomal increasement of grey matter was the main correlative element to the spastic cerebral palsy in preterm children. The small lesion of heterotopic gray matter which are located abnormally in the periventricular white matter near the upper of ventricles would be one of the rather characteristic imaging feature to the diagnosis of the spastic cerebral palsy. It would be useful to clinical prediction and treatment at early stage.