Methods Inf Med 2019; 58(01): 042-049
DOI: 10.1055/s-0039-1688758
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Correlations between P53 Mutation Status and Texture Features of CT Images for Hepatocellular Carcinoma

Hongzhen Wu
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
2  Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
,
Xin Chen
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Jiawei Chen
3  Southern Medical University, Guangzhou, China
,
Yuqi Luo
4  Department of General Surgery, Nansha Hospital, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
5  The Second Affiliated Hospital, South China University of Technology, Guangzhou, China
,
Xinqing Jiang
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
2  Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
,
Xinhua Wei
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Wenjie Tang
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Yu Liu
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Yingying Liang
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Weifeng Liu
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
,
Yuan Guo
1  Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
› Institutsangaben
Funding This study was supported by Guangdong modern hospital management institute hospital management research (No. 2016009), the National Natural Science Foundation of China (No.81571665) and the Science and Technology Planning Project of Guangzhou (No. 201804010032).
Weitere Informationen

Publikationsverlauf

20. Juni 2018

21. März 2019

Publikationsdatum:
04. Juni 2019 (eFirst)

Abstract

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(+).