MRI-based radiomics signatures for predicting the efficacy of targeted therapy with lenvatinib in hepatocellular carcinoma: a retrospective cohort study.

IF 2.8 3区 医学 Q3 ONCOLOGY
Kun Huang, Haiyan Ma, Haikuan Liu, Jia Yuan, Xiaolan He, Yuancheng Liu, Zhouli Zheng, Rongpin Wang
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引用次数: 0

Abstract

Purpose: Targeted therapy with lenvatinib is a preferred option for advanced hepatocellular carcinoma, however, predicting its efficacy remains challenging. This study aimed to build a nomogram integrating clinicoradiological indicators and radiomics features to predict the response to lenvatinib in patients with hepatocellular carcinoma.

Methods: This study included 211 patients with hepatocellular carcinoma from two centers, who were allocated into the training (107 patients), internal test (46 patients) and external test set(58 patients). Radiomics features were extracted using a Pyradiomics-based system. Biopsy specimens were used for immunohistochemical staining of epidermal growth factor receptor. Risk factors for predicting treatment response were screened out to construct models by logistic regression analysis. The performance of models was evaluated with receiver operating characteristic and decision curve analyses.

Results: A total of 9370 radiomics features were extracted from five sequences. Subsequently, seven radiomics features were identified for modeling. Intratumoral vessel and expression level of epidermal growth factor receptor were independent risk factors for predicting treatment response to lenvatinib and were used to build a clinical model. No difference was found in predicting performance between clinical model and radiomics model. The combined model, integrating intratumoral vessel, epidermal growth factor receptor and radiomics features, had better predicting performance with areas under the receiver operating characteristic curve of 0.908, 0.877, and 0.870 for the training, internal test and external test sets, respectively.

Conclusion: This study underscored the significant potential of radiomics features combined with clinicoradiological indicators in the prediction of treatment response to lenvatinib in patients with hepatocellular carcinoma.

Abstract Image

Abstract Image

基于mri的放射组学特征预测lenvatinib靶向治疗肝癌的疗效:一项回顾性队列研究。
目的:lenvatinib靶向治疗是晚期肝细胞癌的首选治疗方案,然而,预测其疗效仍然具有挑战性。本研究旨在建立一种综合临床放射学指标和放射组学特征的nomogram预测lenvatinib在肝癌患者中的疗效。方法:本研究纳入来自两个中心的211例肝癌患者,分为训练组(107例)、内部测试组(46例)和外部测试组(58例)。使用基于pyradiomics的系统提取放射组学特征。活检标本用于表皮生长因子受体免疫组化染色。筛选预测治疗反应的危险因素,通过logistic回归分析构建模型。通过受试者工作特征和决策曲线分析来评价模型的性能。结果:从5个序列中提取了9370个放射组学特征。随后,确定了七个放射组学特征进行建模。瘤内血管和表皮生长因子受体的表达水平是预测lenvatinib治疗反应的独立危险因素,并用于建立临床模型。临床模型和放射组学模型在预测预后方面无差异。结合肿瘤内血管、表皮生长因子受体和放射组学特征的联合模型预测效果较好,训练组、内测组和外测组的受试者工作特征曲线下面积分别为0.908、0.877和0.870。结论:本研究强调了放射组学特征结合临床放射学指标在预测肝细胞癌患者lenvatinib治疗反应方面的重要潜力。
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来源期刊
CiteScore
4.00
自引率
2.80%
发文量
577
审稿时长
2 months
期刊介绍: The "Journal of Cancer Research and Clinical Oncology" publishes significant and up-to-date articles within the fields of experimental and clinical oncology. The journal, which is chiefly devoted to Original papers, also includes Reviews as well as Editorials and Guest editorials on current, controversial topics. The section Letters to the editors provides a forum for a rapid exchange of comments and information concerning previously published papers and topics of current interest. Meeting reports provide current information on the latest results presented at important congresses. The following fields are covered: carcinogenesis - etiology, mechanisms; molecular biology; recent developments in tumor therapy; general diagnosis; laboratory diagnosis; diagnostic and experimental pathology; oncologic surgery; and epidemiology.
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