Shuting Chen1, Yanjie Zhu2, Zaiyi Liu3, Changhong Liang4. 1. Southern Medical University, Guangzhou, 510080, China; Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China. 2. Shenzhen Institutes of Advanced Technology, Shenzhen, 518055, China. 3. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China. Electronic address: zyliu@163.com. 4. Southern Medical University, Guangzhou, 510080, China; Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China. Electronic address: cjr.lchh@vip.163.com.
Abstract
OBJECTIVE: To assess the prognostic value of texture analysis for single hepatocellular carcinomas (HCCs) after hepatectomy. MATERIALS AND METHODS: A total of 61 HCC patients were enrolled in this retrospective study. Textural characteristics of the computed tomography (CT) images were quantified. The differences between the hepatic arterial phase and the portal venous phase were obtained (the Dif.). The receiver operating characteristic (ROC) curves were used for data screening. Cox regression analyses were performed to determine independent factors adjusted with the derived clinical and radiological variables. Model identifications were based on Akaike information criteria. Kaplan-Meier and log-rank tests were performed for overall survival (OS) and disease-free survival (DFS). RESULTS: ROC and Cox regression analyses identified five parameters. Filter 1.0 achieved the best performance, in which the Dif.Scale 1.2 was a superior indicative independent marker for OS (p=0.05). Kaplan-Meier analyses further demonstrated that the Dif.Scale2.2 at filter 0 (p=0.001), Dif.Scale1.2 (p=0.006), Dif.Scale3.2 (p=0.005) at filter 1.0, Dif.Wavelet 8 at filter 1.5 (p<0.001), and corona (p=0.032) were associated with OS. Moreover, Dif.Scale 2.2 at filter 0 (p=0.039), Dif.Scale1.2 at filter 1.0 (p=0.001), and Dif.Wavelet 8 at filter 1.5 (p=0.007) were associated with DFS, while the Barcelona-Clínic Liver Cancer (BCLC) parameters showed no statistical correlation with OS (p=0.057). CONCLUSIONS: For patients with a single HCC treated by hepatectomy, the textural features for Gabor and Wavelet, especially the varying Dif., potentially provided prognostic information beyond traditional indicators such as those of the BCLC.
OBJECTIVE: To assess the prognostic value of texture analysis for single hepatocellular carcinomas (HCCs) after hepatectomy. MATERIALS AND METHODS: A total of 61 HCC patients were enrolled in this retrospective study. Textural characteristics of the computed tomography (CT) images were quantified. The differences between the hepatic arterial phase and the portal venous phase were obtained (the Dif.). The receiver operating characteristic (ROC) curves were used for data screening. Cox regression analyses were performed to determine independent factors adjusted with the derived clinical and radiological variables. Model identifications were based on Akaike information criteria. Kaplan-Meier and log-rank tests were performed for overall survival (OS) and disease-free survival (DFS). RESULTS: ROC and Cox regression analyses identified five parameters. Filter 1.0 achieved the best performance, in which the Dif.Scale 1.2 was a superior indicative independent marker for OS (p=0.05). Kaplan-Meier analyses further demonstrated that the Dif.Scale2.2 at filter 0 (p=0.001), Dif.Scale1.2 (p=0.006), Dif.Scale3.2 (p=0.005) at filter 1.0, Dif.Wavelet 8 at filter 1.5 (p<0.001), and corona (p=0.032) were associated with OS. Moreover, Dif.Scale 2.2 at filter 0 (p=0.039), Dif.Scale1.2 at filter 1.0 (p=0.001), and Dif.Wavelet 8 at filter 1.5 (p=0.007) were associated with DFS, while the Barcelona-Clínic Liver Cancer (BCLC) parameters showed no statistical correlation with OS (p=0.057). CONCLUSIONS: For patients with a single HCC treated by hepatectomy, the textural features for Gabor and Wavelet, especially the varying Dif., potentially provided prognostic information beyond traditional indicators such as those of the BCLC.
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