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目的评价脑血管病患者脑萎缩与胼胝体面积变化的关系。方法46例脑血管病患者在观察期的起止2个时间点分别进行了MR扫描。2次扫描的参数和定位保持一致。利用脑结构图像萎缩率标准化评价软件(structural image evaluation usingnorm alization of atrophy,SIENA)对前后2次的T1W图像进行自动化分析,计算该组患者的年脑体积变化率(percent brain volum echange,PBVC);同时,手工勾画前后2次正中矢状位图像上胼胝体面积和颅内面积,计算得出标准化胼胝体面积的变化率(percentcorpus callosum area change,PCCAC),利用Pearson相关分析这2项指标和年龄的相互关系。结果年龄、年脑体积变化率、年标准化胼胝体面积变化率这3个指标之间的相关具有统计学意义,其相关系数分别为:年龄与PBVC,-0.295(P=0.047);年龄与PC-CAC,-0.4(P=0.006);PBVC与PCCAC,0.538(P=0.000)。结论利用SIENA软件可以自动化测量脑体积变化率,该指标与胼胝体面积的变化较为一致。
Objective To evaluate the relationship between brain atrophy and corpus callosum area in patients with cerebrovascular disease. Methods 46 cases of cerebrovascular disease were observed at the beginning and end of the two time points were MR scan. The parameters and positioning of 2 scans are the same. The percent brain volum echange (PBVC) in this group of patients was calculated by automated analysis of T1W images using structural image evaluation using norm alization of atrophy (SIENA). At the same time, the percent corpus callosum area change (PCCAC) was calculated by manual mapping of corpus callosum area and intracranial area on the two mid-sagittal images. Pearson correlation analysis was used to analyze the relationship between the two indexes and age relationship. Results The correlation between the age, the rate of annual brain volume change and the rate of annual normalized corpus callosum was statistically significant. The correlation coefficients were as follows: age and PBVC, -0.295 (P = 0.047); age and PC- CAC, -0.4 (P = 0.006); PBVC and PCCAC, 0.538 (P = 0.000). Conclusion SIENA software can automatically measure the rate of brain volume change, the index and the corpus callosum area changes are more consistent.