Jun Zhang1, Zixing Huang1, Likun Cao2, Zhen Zhang1, Yi Wei1, Xin Zhang3, Bin Song1. 1. Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China. 2. Department of Radiology, Peking Union Medical College Hospital (Dongdan Campus), Beijing 100730, China. 3. Pharmaceutical Diagnostic team, GE Healthcare, Life Sciences, Beijing 100176, China.
Abstract
BACKGROUND: Combined hepatocellular and cholangiocarcinoma (CHC) and intrahepatic cholangiocarcinoma (ICC) are hard to identify in clinical practice preoperatively. This study looked to develop and confirm a radiomics-based model for preoperative differentiation CHC from ICC. METHODS: The model was developed in 86 patients with ICC and 46 CHC, confirmed in 37 ICC and 20 CHC, and data were collected from January 2014 to December 2018. The radiomics scores (Radscores) were built from radiomics features of contrast-enhanced computed tomography in 12 regions of interest (ROI). The Radscore and clinical-radiologic factors were integrated into the combined model using multivariable logistic regression. The best-combined model constructed the radiomics-based nomogram, and the performance was assessed concerning its calibration, discrimination, and clinical usefulness. RESULTS: The radiomics features extracted from tumor ROI in the arterial phase (AP) with preprocessing were selected to build Radscore and yielded an area under the curve (AUC) of 0.800 and 0.789 in training and validation cohorts, respectively. The radiomics-based model contained Radscore and 4 clinical-radiologic factors showed the best performance (training cohort, AUC =0.942; validation cohort, AUC =0.942) and good calibration (training cohort, AUC =0.935; validation cohort, AUC =0.931). CONCLUSIONS: The proposed radiomics-based model may be used conveniently to the preoperatively differentiate CHC from ICC. 2020 Annals of Translational Medicine. All rights reserved.
BACKGROUND: Combined hepatocellular and cholangiocarcinoma (CHC) and intrahepatic cholangiocarcinoma (ICC) are hard to identify in clinical practice preoperatively. This study looked to develop and confirm a radiomics-based model for preoperative differentiation CHC from ICC. METHODS: The model was developed in 86 patients with ICC and 46 CHC, confirmed in 37 ICC and 20 CHC, and data were collected from January 2014 to December 2018. The radiomics scores (Radscores) were built from radiomics features of contrast-enhanced computed tomography in 12 regions of interest (ROI). The Radscore and clinical-radiologic factors were integrated into the combined model using multivariable logistic regression. The best-combined model constructed the radiomics-based nomogram, and the performance was assessed concerning its calibration, discrimination, and clinical usefulness. RESULTS: The radiomics features extracted from tumor ROI in the arterial phase (AP) with preprocessing were selected to build Radscore and yielded an area under the curve (AUC) of 0.800 and 0.789 in training and validation cohorts, respectively. The radiomics-based model contained Radscore and 4 clinical-radiologic factors showed the best performance (training cohort, AUC =0.942; validation cohort, AUC =0.942) and good calibration (training cohort, AUC =0.935; validation cohort, AUC =0.931). CONCLUSIONS: The proposed radiomics-based model may be used conveniently to the preoperatively differentiate CHC from ICC. 2020 Annals of Translational Medicine. All rights reserved.
Authors: Kathryn J Fowler; Arman Sheybani; Rex A Parker; Sean Doherty; Elizabeth M Brunt; William C Chapman; Christine O Menias Journal: AJR Am J Roentgenol Date: 2013-08 Impact factor: 3.959
Authors: N Machairas; P Stamopoulos; I D Kostakis; Z Garoufalia; A Paspala; P Tsaparas; G C Sotiropoulos Journal: Transplant Proc Date: 2019-01-28 Impact factor: 1.066
Authors: Philipp Kickingereder; Michael Götz; John Muschelli; Antje Wick; Ulf Neuberger; Russell T Shinohara; Martin Sill; Martha Nowosielski; Heinz-Peter Schlemmer; Alexander Radbruch; Wolfgang Wick; Martin Bendszus; Klaus H Maier-Hein; David Bonekamp Journal: Clin Cancer Res Date: 2016-10-10 Impact factor: 12.531
Authors: Michael L Wells; Sudhakar K Venkatesh; Vishal S Chandan; Jeff L Fidler; Joel G Fletcher; Geoffrey B Johnson; David M Hough; Lewis R Roberts Journal: Abdom Imaging Date: 2015-10
Authors: Chenggong Yan; Peng Hao; Guangyao Wu; Jie Lin; Jun Xu; Tianjing Zhang; Xiangying Li; Haixia Li; Sibin Wang; Yikai Xu; Henry C Woodruff; Philippe Lambin Journal: Ann Transl Med Date: 2022-05