Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features

被引:10
|
作者
Liu, Jun [1 ]
Pei, Yigang [2 ,3 ]
Zhang, Yu [1 ]
Wu, Yifan [1 ]
Liu, Fuquan [1 ]
Gu, Shanzhi [4 ,5 ]
机构
[1] Capital Med Univ, Beijing Shijitan Hosp, Dept Intervent Therapy, Affiliated Hosp, Beijing 100038, Peoples R China
[2] Cent South Univ, Xiangya Hosp, Dept Radiol, Changsha 410008, Hunan, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Changsha 410008, Hunan, Peoples R China
[4] Cent South Univ, Dept Intervent Therapy, Hunan Canc Hosp, Xiangya Sch Med, Changsha 410006, Hunan, Peoples R China
[5] Cent South Univ, Affiliated Canc Hosp, Xiangya Sch Med, Changsha 410006, Hunan, Peoples R China
基金
中国博士后科学基金;
关键词
Hepatocellular carcinoma; Transarterial chemoembolization; Microwave ablation; Texture analysis; Prognosis; TUMOR HETEROGENEITY; TRANSARTERIAL CHEMOEMBOLIZATION; CT TEXTURE; CANCER HETEROGENEITY; TREATMENT RESPONSE; ENHANCED MRI; SURVIVAL; OUTCOMES; THERAPY;
D O I
10.1007/s00261-020-02891-y
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective To investigate the prognostic value of baseline magnetic resonance imaging (MRI) texture analysis of hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolization (TACE) and microwave ablation (MWA). Methods MRI was performed on 102 patients with HCC before receiving TACE combined with MWA in this retrospective study. The best 10 texture features were screened as a feature group for each MRI sequence by MaZda software using mutual information coefficient (MI), nonlinear discriminant analysis (NDA) and other methods. The optimal feature group with the lowest misdiagnosis rate was achieved on one MRI sequence between two groups dichotomized by 3-year survival, which was used to optimize the significant texture features with the optimal cutoff values. The Cox proportional hazards model was generated for the significant texture features and clinical variables to determine the independent predictors of overall survival (OS). The predictive performance of the model was further evaluated by the area under the ROC curve (AUC). Kaplan-Meier and log-rank tests were performed for disease-free survival (DFS) and Local recurrence-free survival (LRFS). Results The optimal feature group with the lowest misdiagnosis rate of 8.82% was obtained on T2WI using MI combined with NDA feature analysis. For Cox proportional hazards regression models, the independent prognostic factors associated with OS were albumin (P = 0.047), BCLC stage (P = 0.001), Correlat((1,- 1)T2) (P = 0.01) and SumEntrp((3,0)T2) (P = 0.015), and the prediction efficiency of multivariate model is AUC = 0.876, 95%CI = 0.803-0.949. Kaplan-Meier analyses further demonstrated that BCLC (P < 0.001), Correlat((1,- 1)T2) (P = 0.023) and SumEntrp((3,0)T2) (P < 0.001) were associated with DFS, and BCLC (P = 0.007) related to LRFS. Conclusions MR imaging texture features may be used to predict the prognosis of HCC treated with TACE combined with MWA.
引用
收藏
页码:3748 / 3757
页数:10
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