Prediction analysis of short-term therapeutic efficacy after radiofrequency ablation for hepatocellular carcinoma based on preoperative arterial phase MRI radiomics
10.3969/j.issn.1002-1671.2024.08.014
- VernacularTitle:基于术前MRI动脉期的影像组学对肝细胞肝癌射频消融术后短期疗效的预测分析
- Author:
Lunxin WU
1
,
2
,
3
;
Yingchun LIU
;
Oucheng WANG
;
Qi YAO
;
Haiyi ZHANG
;
Jing WANG
;
Yong LIU
Author Information
1. 西南医科大学临床医学院,四川 泸州 646000
2. 西南医科大学附属中医医院MR室,四川 泸州 646000
3. 合江县人民医院放射科,四川 合江 646200
- Keywords:
magnetic resonance imaging;
radiomics;
hepatocellular carcinoma;
radiofrequency ablation
- From:
Journal of Practical Radiology
2024;40(8):1281-1285
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the feasibility of constructing a short-term therapeutic efficacy prediction model for hepatocellular carcinoma(HCC)after radiofrequency ablation(RFA)based on texture analysis of preoperative MRI arterial phase images.Methods A retrospective analysis was conducted on 169 HCC patients treated with RFA.Based on the short-term therapeutic efficacy,the patients were divided into a good prognosis group(112 cases)and a poor prognosis group(57 cases).Texture features of preoperative MRI arterial phase images were extracted using Mazda software,and dimension reduction was performed through Fisher coefficient,mutual information,classification error probability,and mean correlation coefficient.The patients were divided into a training group(n=119)and a testing group(n=50)in a 7∶3 ratio.Independent sample t-tests and the least absolute shrinkage and selection operator(LASSO)algorithm were employed for further feature selection.Subsequently,a radiomics model was established using LASSO regression and evaluated through the receiver operating characteristic(ROC)curve and area under the curve(AUC).Results The radiomics model comprised features such as S_2__2_SumOfSqs,Teta1,S_5_0_DifVarnc,S_2_0_DifEntrp,Horzl_LngREmph,and S_5_5_InvDfMom.The AUC of the model were 0.987[95％confidence interval(CI)0.965-1.000]and 0.918(95％CI 0.818-1.000)in the training and testing groups,respectively.The sensitivity was 98.7％(95％CI 92.4-100)and 93.9％(95％CI 84.8-100),and the specificity was 97.5％(95％CI 90.0-100)and 88.2％(95％CI 70.6-100),respectively.Conclusion The construction of a predictive model for short-term therapeutic efficacy of HCC after RFA based on texture analysis of preoperative MRI arterial phase images is feasible and demonstrates good predictive performance.
