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Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.
Meng, Xiang-Pan; Wang, Yuan-Cheng; Ju, Shenghong; Lu, Chun-Qiang; Zhong, Bin-Yan; Ni, Cai-Fang; Zhang, Qi; Yu, Qian; Xu, Jian; Ji, JianSong; Zhang, Xiu-Ming; Tang, Tian-Yu; Yang, Guanyu; Zhao, Ziteng.
Afiliación
  • Meng XP; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Wang YC; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Ju S; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Lu CQ; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Zhong BY; Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
  • Ni CF; Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
  • Zhang Q; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Yu Q; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Xu J; Department of Interventional Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Ji J; Department of Radiology, Affiliated Lishui Hospital of Zhejiang University, The Central Hospital of Zhejiang Lishui, Lishui, China.
  • Zhang XM; Department of Radiology, Nanjing Medical University Affiliated Cancer Hospital, Cancer Institute of Jiangsu Province, Nanjing, China.
  • Tang TY; Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Yang G; LIST, Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing, China.
  • Zhao Z; LIST, Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing, China.
Front Oncol ; 10: 1196, 2020.
Article en En | MEDLINE | ID: mdl-32850345
ABSTRACT
Patients with HCC receiving TACE have various clinical outcomes. Several prognostic models have been proposed to predict clinical outcomes for patients with hepatocellular carcinomas (HCC) undergoing transarterial chemoembolization (TACE), but establishing an accurate prognostic model remains necessary. We aimed to develop a radiomics signature from pretreatment CT to establish a combined radiomics-clinic (CRC) model to predict survival for these patients. We compared this CRC model to the existing prognostic models in predicting patient survival. This retrospective study included multicenter data from 162 treatment-naïve patients with unresectable HCC undergoing TACE as an initial treatment from January 2007 and March 2017. We randomly allocated patients to a training cohort (n = 108) and a testing cohort (n = 54). Radiomics features were extracted from intra- and peritumoral regions on both the arterial phase and portal venous phase CT images. A radiomics signature (Rad-signature) for survival was constructed using the least absolute shrinkage and selection operator method in the training cohort. We used univariate and multivariate Cox regressions to identify associations between the Rad- signature and clinical factors of survival. From these, a CRC model was developed, validated, and further compared with previously published prognostic models including four-and-seven criteria, six-and-twelve score, hepatoma arterial-embolization prognostic scores, and albumin-bilirubin grade. The CRC model incorporated two variables The Rad-signature (composed of features extracted from intra- and peritumoral regions on the arterial phase and portal venous phase) and tumor number. The CRC model performed better than the other seven well-recognized prognostic models, with concordance indices of 0.73 [95% confidence interval (CI) 0.68-0.79] and 0.70 [95% CI 0.62-0.82] in the training and testing cohorts, respectively. Among the seven models tested, the six-and-12 score and four-and-seven criteria performed better than the other models, with C-indices of 0.64 [95% CI 0.58-0.70] and 0.65 [95% CI 0.55-0.75] in the testing cohort, respectively. The CT radiomics signature represents an independent biomarker of survival in patients with HCC undergoing TACE, and the CRC model displayed improved predictive performance.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2020 Tipo del documento: Article País de afiliación: China