Lina Zhang1, Jingbiao Chen1, Hang Jiang1, Dailin Rong1, Ning Guo1, Hao Yang2, Jie Zhu1, Bing Hu1, Bingjun He1, Meng Yin3, Sudhakar K Venkatesh3, Richard L Ehman3, Jin Wang4. 1. Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, No. 600, Tianhe Road, Guangzhou, Guangdong 510630, PR China. 2. Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, No. 600, Tianhe Road, Guangzhou, Guangdong 510630, PR China; Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University (SYSU), No. 107, Yanjiangxi Road, Guangzhou, Guangdong 510120, People's Republic of China. 3. Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. 4. Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, No. 600, Tianhe Road, Guangzhou, Guangdong 510630, PR China. Electronic address: wangjin3@mail.sysu.edu.cn.
Abstract
PURPOSE: To investigate the diagnostic performance of preoperative MR elastography (MRE) in predicting early recurrence (ER) and late recurrence (LR) of HCC after hepatectomy. METHOD: In total, 180 patients (median age, 52 years; interquartile range, 41-50 years; 161 men) who underwent conventional MRI and MRE before hepatectomy between December 2014 and April 2020 were retrospectively recruited. A preoperative clinic-radiologic model and a combined postoperative clinic-pathologic and radiologic model were built using quantitatively MRE-derived stiffnesses, and image features to predict tumor ER and LR after hepatectomy. The Cox proportional hazards model and ROC analyses were used to identify the value of parameters to predict ER and LR. RESULTS: Seventy-three (40.5%) and 16 (8.9%) developed ER and LR after hepatectomy, respectively. For prediction of ER, the preoperative model integrated higher tumor stiffness (TS) (hazard ratio [HR],1.142; p < 0.001) with AFP ≥ 400 ng/mL (HR,1.761; p = 0.022), multifocal tumors (HR,3.229; p < 0.001) and lower ADC (HR,0.998; p = 0.017) variables; and the postoperative model incorporated higher TS, microvascular invasion, multifocal tumors, Child-Pugh class and ADC predictors. The two models provided comparable predictive performance (pre- 0.812 vs. post- 0.834, p = 0.283). Moreover, TS alone had a high sensitivity (90.4%) for predicting ER. Liver stiffness (LS) (HR, 1.757; p < 0.001) was the only independent predictor for LR in multivariate analysis in both the pre- and postoperative models with high specificity (90.0%), and its AUC with an optimal cut-off of 3.62 kPa was 0.860. CONCLUSIONS: Quantitative MRE-based stiffness is a useful biomarker for preoperative prediction of ER and LR of HCC.
PURPOSE: To investigate the diagnostic performance of preoperative MR elastography (MRE) in predicting early recurrence (ER) and late recurrence (LR) of HCC after hepatectomy. METHOD: In total, 180 patients (median age, 52 years; interquartile range, 41-50 years; 161 men) who underwent conventional MRI and MRE before hepatectomy between December 2014 and April 2020 were retrospectively recruited. A preoperative clinic-radiologic model and a combined postoperative clinic-pathologic and radiologic model were built using quantitatively MRE-derived stiffnesses, and image features to predict tumor ER and LR after hepatectomy. The Cox proportional hazards model and ROC analyses were used to identify the value of parameters to predict ER and LR. RESULTS: Seventy-three (40.5%) and 16 (8.9%) developed ER and LR after hepatectomy, respectively. For prediction of ER, the preoperative model integrated higher tumor stiffness (TS) (hazard ratio [HR],1.142; p < 0.001) with AFP ≥ 400 ng/mL (HR,1.761; p = 0.022), multifocal tumors (HR,3.229; p < 0.001) and lower ADC (HR,0.998; p = 0.017) variables; and the postoperative model incorporated higher TS, microvascular invasion, multifocal tumors, Child-Pugh class and ADC predictors. The two models provided comparable predictive performance (pre- 0.812 vs. post- 0.834, p = 0.283). Moreover, TS alone had a high sensitivity (90.4%) for predicting ER. Liver stiffness (LS) (HR, 1.757; p < 0.001) was the only independent predictor for LR in multivariate analysis in both the pre- and postoperative models with high specificity (90.0%), and its AUC with an optimal cut-off of 3.62 kPa was 0.860. CONCLUSIONS: Quantitative MRE-based stiffness is a useful biomarker for preoperative prediction of ER and LR of HCC.
Authors: Weimin Liu; Dailin Rong; Jie Zhu; Yuanqiang Xiao; Linqi Zhang; Ying Deng; Jun Chen; Meng Yin; Sudhakar K Venkatesh; Richard L Ehman; Jin Wang Journal: Abdom Radiol (NY) Date: 2021-06-03
Authors: Julie K Heimbach; Laura M Kulik; Richard S Finn; Claude B Sirlin; Michael M Abecassis; Lewis R Roberts; Andrew X Zhu; M Hassan Murad; Jorge A Marrero Journal: Hepatology Date: 2018-01 Impact factor: 17.425