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增强MRI直方图鉴别儿童后颅窝髓母细胞瘤和室管膜瘤的价值 被引量:11

Enhancement of MRI histogram in the identification of children with medulloblastoma and ependymoma
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摘要 目的:探讨增强MRI直方图分析鉴别儿童髓母细胞瘤和室管膜瘤的价值。材料和方法:回顾性分析我院经手术病理证实的36例儿童后颅窝肿瘤,其中髓母细胞瘤20例、室管膜瘤16例。收集该两种肿瘤的T1、T2加权和增强T1磁共振图像,用软件MaZda提取肿瘤的感兴趣区(ROI),针对肿瘤最大层面的ROI进行直方图分析,利用平均值、方差、偏斜度、峰度、第1、10、50、90、99百分位数特征,找出两种肿瘤之间的显著性差异。结果 :利用直方图提取出的9个纹理参数中,1百分数具有统计学意义(P<0.05),并绘制C1 ROC曲线,ROC曲线下的最大面积为0.82,取46.5的特异性和敏感性分别为82%、75%。结论:直方图分析可以提供更多量化信息特征,为儿童髓母细胞瘤和室管膜瘤的鉴别诊断提供了新的思路和方法。 Objective: To investigate the diagnostic value of the histogram analysis derived from enhancement MR imaging in differentiating medulloblastomas from ependymoma. Methods and Materials: Retrospective analysis of pathologically confirmed 36 cases of posterior fossa tumors, including 20 cases of medulloblastoma, 16 cases of ependymoma, were performed.T1, T2 and enhanced T1 weighted magnetic resonance images were collected, tumor region of interest were extracted by the software of MaZda(region of interest, ROI), histogram analysis for the maximum level of tumor region of interest was undergone, the average value, variance, skewness, kurtosis, the 1, 10, 50, 90, 99 percentile characteristics were selected to find out the significant differences between the two kinds of tumors. Result: 9 texture parameters from histogram were with statistical significance(1 percent), and in the C1 ROC curve, the maximum area under ROC curve is 0.82, 46.5 as cut-off value specificity and sensitivity were 82% and 75%. Conclusion: Histogram analysis can provide more quantitative information characteristics, which provides a new method for the differential diagnosis of children with medulloblastoma and ependymoma.
作者 汪卫建 程敬亮 张勇 郭亚飞 WANG Wei-jian;CHENG Jing-liang;ZHANG Yong;GUO Ya-fei(Department of MRI, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Chin)
出处 《中国临床医学影像杂志》 CAS 2018年第5期305-308,共4页 Journal of China Clinic Medical Imaging
基金 河南省医学科技攻关计划项目(201602030)
关键词 髓母细胞瘤 室管膜瘤 磁共振成像 诊断 鉴别 Medulloblastoma Ependymoma Magnetic resonance imaging Diagnosis differential
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