OBJECTIVES To investigate the performance of texture analysis in characterizing P53 mutations of hepatocellular carcinomas (HCCs) based on computed tomography (CT). METHODS A total of 63 HCC patients underwent CT scans and were tested for P53 mutations. Patients were divided into two groups of P53(-) and P53(+) according to the P53 scores. First- and second-order texture features were computed from the CT images and compared between groups using independent Student's t-test. A Spearman's correlation coefficient was used for correlations to assess the relationship between the different P53 sores and CT data. The performance of texture features in differentiating the P53 mutations of HCC was assessed using receiver operating characteristic analysis. RESULTS The mean values of angular second moment (ASM; mean = 0.001) and contrast (mean = 194.727) for P53(-) were higher than those of P53(+). Meanwhile the mean values of correlation (mean = 0.735), sum variance (mean = 1,111.052), inverse difference moment (IDM; mean = 0.090), and entropy (mean = 3.016) for P53(-) were lower than those of P53(+). Significant correlations were found between P53 scores and ASM (r = - 0.439), contrast (r = - 0.263), correlation (r = 0.551), sum of squares (r = 0.282), sum variance (r = 0.417), IDM (r = 0.308), and entropy (r = 0.569). Five texture parameters (ASM, contrast, correlation, IDM, and entropy) were predictive of P53 mutation status, with areas under the curve ranging from 0.621 to 0.792. CONCLUSIONS There was a direct relationship between P53 mutations and gray-level co-occurrence matrix, but not with histograms for HCC patients. Correlation and entropy seemed to be the most promising in differentiating P53 (-) from P53(+).

中文翻译：

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肝细胞癌P53突变状态与CT图像纹理特征的相关性。

目的探讨基于计算机断层扫描（CT）的质地分析在表征肝细胞癌（HCC）P53突变中的性能。方法总共63例HCC患者接受了CT扫描，并检测了P53突变。根据P53评分将患者分为P53（-）和P53（+）两组。从CT图像计算出一阶和二阶纹理特征，并使用独立的Student's t检验在各组之间进行比较。使用Spearman相关系数进行相关，以评估不同P53疮与CT数据之间的关系。使用接收器工作特征分析评估了纹理特征在区分HCC P53突变中的性能。结果弯矩第二矩（ASM;平均值= 0.001）和对比度（平均值= 194）的平均值。727）的P53（-）高于P53（+）。同时，P53（-）的相关平均值（平均值= 0.735），总方差（平均值= 1,111.052），逆差矩（IDM;平均值= 0.090）和熵（平均值= 3.016）低于P53（-） +）。P53评分与ASM（r =-0.439），对比（r =-0.263），相关性（r = 0.551），平方和（r = 0.282），总和方差（r = 0.417），IDM（ r = 0.308）和熵（r = 0.569）。五个纹理参数（ASM，对比度，相关性，IDM和熵）可预测P53突变状态，曲线下面积范围为0.621至0.792。结论P53突变与灰度共生矩阵之间存在直接关系，但与HCC患者的直方图无关。