[1]李文华,许传斌,崔景景,等.基于治疗前MR-T2WI影像组学特征预测肝细胞癌射频消融术后早期复发的价值[J].医学信息,2022,35(18):39-43,52.[doi:10.3969/j.issn.1006-1959.2022.18.009]
 LI Wen-hua,XU Chuan-bin,CUI Jing-jing,et al.The Value of Predicting Early Recurrence of Hepatocellular Carcinoma After Radiofrequency Ablation Based on Pre-treatment MR-T2WI Radiomics Features[J].Journal of Medical Information,2022,35(18):39-43,52.[doi:10.3969/j.issn.1006-1959.2022.18.009]
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基于治疗前MR-T2WI影像组学特征预测肝细胞癌射频消融术后早期复发的价值()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年18期
页码:
39-43,52
栏目:
论著
出版日期:
2022-09-15

文章信息/Info

Title:
The Value of Predicting Early Recurrence of Hepatocellular Carcinoma After Radiofrequency Ablation Based on Pre-treatment MR-T2WI Radiomics Features
文章编号:
1006-1959(2022)18-0039-06
作者:
李文华许传斌崔景景
(1.佳木斯大学临床医学院,黑龙江 佳木斯 154002;2.解放军总医院第四医学中心放射诊断科,北京 100048;3.联影医疗科技<北京>有限公司,北京 100089)
Author(s):
LI Wen-huaXU Chuan-binCUI Jing-jinget al.
(1.The Clinical Medical College of Jiamusi University,Jiamusi 154002,Heilongjiang,China;2.Department of Radiology,the Fourth Medical Center of PLA General Hospital,Beijing 100048,China;3.United Imaging Intelligence Co.,Ltd.,Beijing 100089,China)
关键词:
肝细胞癌射频消融术早期复发影像组学磁共振成像
Keywords:
Hepatocellular carcinomaRadiofrequency ablationEarly recurrenceRadiomicsMagnetic resonance imaging
分类号:
R735.7;R445.2
DOI:
10.3969/j.issn.1006-1959.2022.18.009
文献标志码:
A
摘要:
目的 初步探讨基于治疗前T2加权成像(T2WI)的影像组学特征预测肝细胞癌(HCC)射频消融术(RFA)后早期复发的价值。方法 回顾性分析2015年1月-2021年3月于解放军总医院第四医学中心采取射频消融治疗的140例肝细胞癌患者的临床和影像资料,术后定期随访,了解是否发生早期复发。所有样本按8∶2的比例随机分成训练集和测试集,在训练集中先提取734个特征,采用方差阈值、K最佳和LASSO算法筛选特征,最后构建机器学习预测模型(逻辑回归、支持向量机、随机森林)并采用测试集进行内部验证。结果 共筛选出8个与肝细胞癌早期复发相关的特征,随机森林分类器在训练集预测肝细胞癌术后早期复发的AUC值、准确率、诊断敏感性、特异性分别为0.903、0.812、0.839、0.802;在测试集中的AUC值、准确率、诊断敏感性、特异度分别为0.806、0.750 、0.625、0.800。结论 治疗前T2WI的影像组学特征可用于肝细胞癌射频消融术后早期复发的自动化评估,这有助于临床医生制定合适治疗方案。
Abstract:
Objective To preliminarily explore the diagnostic value of radiomics features frompreoperative T2-weighted imaging (T2WI) in predicting the early recurrence of hepatocellular carcinoma after radiofrequency ablation.Methods Retrospectively analyze the clinical and imaging data of 140 hepatocellular carcinoma patients with radiofrequency ablation treatment at the Fourth Medical Center of PLA General Hospital from January 2015 to March 2021.Early recurrence was confirmed by postoperative regular follow-up. All samples are randomly divided into training set and validation set with a percentage of 8:2. In the training set, 734 features were extracted first, and the features were screened by variance threshold, K best and LASSO algorithm. Finally, the machine learning prediction model (logistic regression, support vector machine, random forest) was constructed and the test set was used for internal verification.Results A total of 8 features related to early recurrence of hepatocellular carcinoma were screened out. The AUC value, accuracy, diagnostic sensitivity and specificity of random forest classifier in predicting early recurrence of hepatocellular carcinoma after operation in training set were 0.903, 0.812, 0.839 and 0.802, respectively. The AUC value, accuracy, diagnostic sensitivity and specificity in the test set were 0.806, 0.750, 0.625 and 0.800, respectively.Conclusion The radiomics features of T2WI before treatment can be used for automatic evaluation of early recurrence after radiofrequency ablation of hepatocellular carcinoma, which is helpful for clinicians to formulate appropriate treatment plans.

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更新日期/Last Update: 1900-01-01