Bo-Hao Zheng1, Long-Zi Liu1, Zhi-Zhi Zhang2, Jie-Yi Shi1, Liang-Qing Dong1, Ling-Yu Tian1, Zhen-Bin Ding1, Yuan Ji3, Sheng-Xiang Rao4, Jian Zhou1, Jia Fan1,5, Xiao-Ying Wang6, Qiang Gao7,8. 1. Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital and Key Laboratory of Carcinogenesis and Cancer Invasion, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. 2. Department of Hematology, Shanghai Jiao Tong University School of Medicine Affiliated Tongren Hospital, Shanghai, China. 3. Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. 4. Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. 5. Institute of Biomedical Sciences, Fudan University, Shanghai, 200032, China. 6. Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital and Key Laboratory of Carcinogenesis and Cancer Invasion, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. wang.xiaoying1@zs-hospital.sh.cn. 7. Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital and Key Laboratory of Carcinogenesis and Cancer Invasion, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. gaoqiang@fudan.edu.cn. 8. State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, People's Republic of China. gaoqiang@fudan.edu.cn.
Abstract
BACKGROUND: Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary hepatocellular carcinoma (HCC). METHODS: A total of 319 solitary HCC patients (training cohort: n = 212; validation cohort: n = 107) were enrolled. Radiomics features were extracted from the artery phase of preoperatively acquired computed tomography (CT) in all patients. A rad-score was generated by using the least absolute shrinkage and selection operator (lasso) logistic model. Kaplan-Meier and Cox's hazard regression analyses were used to evaluate the prognostic significance of the rad-score. Final nomograms predicting recurrence and survival of solitary HCC patients were established based on the rad-score and clinicopathological factors. C-index and calibration statistics were used to assess the performance of nomograms. RESULTS: Six potential radiomics features were selected out of 110 texture features to formulate the rad-score. Low rad-score positively correlated with aggressive tumor phenotypes, like larger tumor size and vascular invasion. Meanwhile, low rad-score was significantly associated with increased recurrence and reduced survival. In addition, multivariate analysis identified the rad-score as an independent prognostic factor (recurrence: Hazard ratio (HR): 2.472, 95% confident interval (CI): 1.339-4.564, p = 0.004;survival: HR: 1.558, 95%CI: 1.022-2.375, p = 0.039). Notably, the nomogram integrating rad-score had a better prognostic performance as compared with traditional staging systems. These results were further confirmed in the validation cohort. CONCLUSIONS: The preoperative CT image based rad-score was an independent prognostic factor for the postoperative outcome of solitary HCC patients. This score may be complementary to the current staging system and help to stratify individualized treatments for solitary HCC patients.
BACKGROUND: Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary hepatocellular carcinoma (HCC). METHODS: A total of 319 solitary HCCpatients (training cohort: n = 212; validation cohort: n = 107) were enrolled. Radiomics features were extracted from the artery phase of preoperatively acquired computed tomography (CT) in all patients. A rad-score was generated by using the least absolute shrinkage and selection operator (lasso) logistic model. Kaplan-Meier and Cox's hazard regression analyses were used to evaluate the prognostic significance of the rad-score. Final nomograms predicting recurrence and survival of solitary HCCpatients were established based on the rad-score and clinicopathological factors. C-index and calibration statistics were used to assess the performance of nomograms. RESULTS: Six potential radiomics features were selected out of 110 texture features to formulate the rad-score. Low rad-score positively correlated with aggressive tumor phenotypes, like larger tumor size and vascular invasion. Meanwhile, low rad-score was significantly associated with increased recurrence and reduced survival. In addition, multivariate analysis identified the rad-score as an independent prognostic factor (recurrence: Hazard ratio (HR): 2.472, 95% confident interval (CI): 1.339-4.564, p = 0.004;survival: HR: 1.558, 95%CI: 1.022-2.375, p = 0.039). Notably, the nomogram integrating rad-score had a better prognostic performance as compared with traditional staging systems. These results were further confirmed in the validation cohort. CONCLUSIONS: The preoperative CT image based rad-score was an independent prognostic factor for the postoperative outcome of solitary HCCpatients. This score may be complementary to the current staging system and help to stratify individualized treatments for solitary HCCpatients.
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