Study on the Radiomics Model to Predict Early Recurrence after Hepatocellular Carcinoma Ablation
10.3969/j.issn.1672-2159.2024.08.008
- VernacularTitle:普美显增强MRI预测肝细胞癌消融术后早期复发的影像组学模型研究
- Author:
Zhipeng CHENG
1
,
2
;
Xiaoling CHEN
;
Hui ZHANG
;
Yixin CHEN
;
Yuchang LIN
;
Qian YANG
;
Sina JIANG
;
Huang HUANG
Author Information
1. 510515 南方医科大学南方医院护理部
2. 510515 南方医科大学第一临床医学院
- Keywords:
Hepatocellular Carcinoma;
Radiomics;
Contrast-enhanced Ultrasound;
Magnetic Resonance Imaging;
Ablation;
Early Recurrence;
Prediction Model
- From:
Modern Interventional Diagnosis and Treatment in Gastroenterology
2024;29(8):923-931,942
- CountryChina
- Language:Chinese
-
Abstract:
Objective Liver cancer is the second leading cause of tumor-related death.The efficacy of local thermal ablation is comparable to surgical resection for the early hepatocellular carcinoma(HCC),and the ablation technique is minimally invasive,repeatable,and has a low complication rate.However,early recurrence((2 years)is the main cause of death after HCC ablation,but there is still a lack of accurate and reliable prediction models for early recurrence.Therefore,this survey intended to construct prediction models for early recurrence of HCC after ablation by using preoperative gadoxetic acid disodium-enhanced magnetic resonance(MR)images data combined with radiomics methods,evaluate and verify their predictive efficacy.To explore the application value of contrast-enhanced MRI imaging before ablation in the prognosis assessment of HCC patients,and to provide reliable data and theoretical basis for clinical treatment decisions.Methods A retrospective study was performed on 120 patients with HCC who underwent ablation and all the patients were underwent contrast-enhanced MRI examination within 1 month.A total of 1318 radiomic features were extracted from each patient by using preoperative T2-weighted sequence(T2WI)images of contrast-enhanced MRI.After feature selection,six machine learning algorithms would be used for construction of models and comparison.Finally,Logistic regression analysis was used to establish a clinical model,a radiomics model and a combined model which included the above risk factors and radiologic features.The nomogram was constructed based the combined model to evaluate the differentiation,accuracy and clinical benefit.Results Five radiomic features most closely related to early recurrence were identified and selected for model construction.The radiomic model had effective predictive performance,with AUC of 0.80 in the training sets.Two clinical risk factors associated with early recurrence,including tumor number and peritumoral hypodensity on the hepatobiliary phase,were selected to established a clinical-radiological-radiomics(CRRM)model,with AUC as high as 0.92 in the validation sets.The nomogram of CRRM model was constructed and the calibration curves indicated the goodness of fit.Decision curve analysis further confirmed the clinical usefulness of CRRM model.Conclusion The radiomics model of preoperatively contrast-enhanced MRI-T2WI image features was identified be effective to predict HCC early recurrence.In contrast,the CRRM model could be used as a more comprehensive and superior tool to predict individual probability of early recurrence.Patients at high risk of early recurrence could be identified and the appropriate and effective preoperative treatments could also be taken,to improve the prognosis and long-term survival rate of HCC patients the individualized treatment strategies should be formulated.
