CT纹理分析在鉴别乏脂肪肾错构瘤与肾透明细胞癌中的价值

发布时间：2018-04-01 17:14

本文选题：肾错构瘤　切入点：肾透明细胞癌　出处：《临床放射学杂志》2017年07期

【摘要】：目的探讨CT纹理分析对鉴别乏脂肪肾错构瘤与肾透明细胞癌的价值。方法回顾性分析经手术病理证实的16例乏脂肪肾错构瘤与79例肾透明细胞癌的CT增强图像;通过纹理分析的方法测得其平均值、标准差、熵、不均匀度、峰值、偏度等定量参数,并进行统计学分析。结果两位观察者测得的CT纹理分析定量参数的一致性分析结果如下:平均值、标准差、熵、不均匀度、峰值及偏度的Cronbachα系数分别为:0.97、0.93、0.97、0.94、0.56、0.68。纹理分析定量参数中差、熵、不均匀度三个参数两组间比较结果具有显著差异:标准差(t=3.60,P0.01),熵(t=4.80,P0.01),不均匀度(t=3.86,P0.01);利用标准差鉴别两组肿瘤的曲线下面积、阈值、敏感性、特异性、准确性分别为:0.78、45.46、70.9%、81.2%、72.6%;利用熵鉴别两组肿瘤的曲线下面积、阈值、敏感性、特异性、准确性分别为:0.82、4.50、84.8%、68.8%、82.1%;利用不均匀度鉴别两组肿瘤的曲线下面积、阈值、敏感性、特异性、准确性分别为:0.80、0.09、70.9%、81.2%、72.6%。利用多参数联合鉴别肾乏脂肪错构瘤与肾透明细胞癌的效能:标准差+熵鉴别两组肿瘤的曲线下面积、敏感性、特异性、准确性分别为:0.83%、75.0%、81.0%、80.0%;标准差+不均匀度鉴别两组肿瘤的曲线下面积、敏感性、特异性、准确性分别为:0.81%、81.2%、70.1%、71.6%;熵+不均匀度鉴别两组肿瘤的曲线下面积、敏感性、特异性、准确性分别为:0.83、81.2%、70.1%、72.6%;标准差+熵+不均匀度鉴别两组肿瘤的曲线下面积、敏感性、特异性、准确性分别为:0.84、87.5%、69.6%、72.6%。结论 CT纹理分析的部分定量参数(标准差、熵、不均匀度)可用于鉴别乏脂肪错构瘤与肾细胞癌。
[Abstract]:Objective to evaluate the value of CT texture analysis in differentiating adipogenic renal hamartoma from renal clear cell carcinoma. Methods CT enhanced images of 16 cases of adipose renal hamartoma and 79 cases of renal clear cell carcinoma proved by surgery and pathology were retrospectively analyzed. The quantitative parameters such as average value, standard deviation, entropy, non-uniformity, peak value, deviation and so on are measured by means of texture analysis. Results the consistency of the quantitative parameters of CT texture analysis measured by two observers was as follows: mean value, standard deviation, entropy, non-uniformity, The Cronbach 伪 coefficients of peak value and skewness are 0. 97 / 0. 93 / 0. 97 / 0. 94 / 0. 566 / 0. 68 respectively. There are significant differences between the three groups in the quantitative parameters of texture analysis: standard deviation is 3. 60% P0.01g, entropy is 4. 80 P0. 01, heterogeneity is 3. 86% P0. 01, and the area under the curve of the two groups is identified by using standard deviation. The threshold value, sensitivity, specificity, accuracy were 72.6. the area under the curve, threshold, sensitivity, specificity and accuracy of the two groups were identified by entropy, respectively. The area under the curve, the threshold, the sensitivity, the specificity and the accuracy of the tumor in the two groups were respectively 82.1.The area under the curve, the threshold, the sensitivity, the specificity, and the accuracy of the two groups were respectively 82.1.The area under the curve, the threshold, the sensitivity, the specificity, and the accuracy of the two groups were identified by non-uniformity. The sensitivity, specificity and accuracy of the two groups were respectively 81.20.The effectiveness of multiple parameters in differentiating renal adipose hamartoma from renal clear cell carcinoma: the area under the curve, sensitivity and specificity of the two groups of tumors were identified by standard deviation entropy. The accuracy of the two groups of tumors was 75.0 and 81.0, respectively; the area under the curve, sensitivity, specificity, and accuracy of the standard deviation non-uniformity were 70.1 and 71.6, respectively; the area under the curve, sensitivity, specificity, and specificity of the two groups of tumors were identified by entropy non-uniformity, and the area under the curve, sensitivity, specificity, and specificity of the two groups of tumors were identified. The accuracy was 70.1% and 72.6% respectively; the standard deviation entropy unevenness was used to identify the area, sensitivity, specificity and accuracy of the two groups of tumors under the curve, respectively. The sensitivity, specificity and accuracy of the two groups were 69.66.Conclusion some quantitative parameters of CT texture analysis (standard deviation, entropy, entropy), Heterogeneity) can be used to differentiate adipose hamartoma from renal cell carcinoma.
【作者单位】：徐州医学院附属医院放射科;
【分类号】：R730.44;R737.11

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