多期mri衍生的Delta放射组学与临床特征相结合,用于预测肝细胞癌热消融后的生存

IF 3.3 3区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Junpeng Luo , Hao Xin , Yandan Wang , Xiang He
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引用次数: 0

摘要

理论基础和目的评价多期增强磁共振成像(MRI)获得的δ放射学评分(DRS)结合临床特征预测肝细胞癌(HCC)患者热消融后总生存期(OS)和无复发生存期(RFS)的预测价值。材料和方法本回顾性研究纳入了来自两个中心的415例HCC患者,他们接受了多期磁共振增强成像和经皮热消融。机构1的患者(n = 315)被随机分配到培训队列(n = 220)和内部测试队列(n = 95),而机构2的100名患者组成外部验证队列。通过对比增强图像与非收缩图像,提取δ放射特征,然后进行方差滤波、相关分析、随机森林排序和Cox回归,得出DRS。DRS结合临床特征,包括肿瘤负荷评分(TBS)、巴塞罗那临床肝癌(BCLC)和中国肝癌分期(CNLC),建立随机生存森林(RSF)模型。采用一致性指数(C-index)、曲线下面积(AUC)、标定曲线和决策曲线分析(DCA)对模型的性能进行评价。结果将DRS与临床特征相结合的RSF模型对OS和RFS均具有良好的预测效果。对于36个月和60个月的OS预测,队列中的auc范围为0.71至0.83,相应的C指数在0.69至0.83之间。对于6、12、24个月的短期RFS预测,AUC范围为0.71 ~ 0.91,c指数范围为0.68 ~ 0.71。校准和DCA分析在内部和外部验证中证实了模型的稳健性和临床实用性。结论基于多期MRI的delta放射组学可有效捕获肿瘤动力学和异质性。当与临床特征相结合时,所得到的模型可以准确预测复发和长期生存,为HCC的风险分层和个体化消融后管理提供实用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiphase MRI-Derived Delta radiomics integrated with clinical features for survival prediction in hepatocellular carcinoma after thermal ablation

Rationale and objectives

To evaluate the predictive value of a delta radiomic score (DRS)derived from multiphase contrast-enhanced Magnetic Resonance Imaging (MRI), in combination with clinical characteristics, forecasting overall survival (OS) and recurrence-free survival (RFS) in patients with hepatocellular carcinoma (HCC) after thermal ablation.

Materials and Methods

This retrospective study enrolled 415 patients with HCC from two centers who underwent multiphase contrast-enhanced magnetic resonance imaging and percutaneous thermal ablation. Patients in Institution 1 (n = 315) were randomly assigned to the training cohorts (n = 220) and internal tests (n = 95), while 100 patients in Institution 2 formed the external validation cohort. Delta radiomic features were extracted by comparing contrast-enhanced phases with noncontract images, followed by variance filtering, correlation analysis, random forest ranking, and Cox regression to derive the DRS. The DRS was combined with clinical characteristics, including tumor burden score (TBS), Barcelona Clinic Liver Cancer (BCLC), and China Liver Cancer Staging (CNLC), to build Random Survival Forest (RSF) models. The performance of the model was evaluated using the concordance index (C-index), the area under the curve (AUC), the calibration curves and the analysis of decision curves (DCA).

Results

The RSF models that integrate DRS with clinical characteristics demonstrated favorable predictive performance for both OS and RFS. For OS predictions at 36 and 60 months, AUCs ranged from 0.71 to 0.83 in cohorts, with corresponding C indices between 0.69 and 0.83. For the prediction of short-term RFS at 6, 12, and 24 months, the AUC ranged from 0.71 to 0.91, with C-indices between 0.68 and 0.71. Calibration and DCA analysis confirmed the robustness and clinical utility of the models in internal and external validations.

Conclusions

Delta radiomics derived from multiphase MRI effectively captured tumor dynamics and heterogeneity. When integrated with clinical characteristics, the resulting models allowed an accurate prediction of both recurrence and long-term survival, providing a practical tool for risk stratification and individualized post-ablation management in HCC.
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来源期刊
CiteScore
6.70
自引率
3.00%
发文量
398
审稿时长
42 days
期刊介绍: European Journal of Radiology is an international journal which aims to communicate to its readers, state-of-the-art information on imaging developments in the form of high quality original research articles and timely reviews on current developments in the field. Its audience includes clinicians at all levels of training including radiology trainees, newly qualified imaging specialists and the experienced radiologist. Its aim is to inform efficient, appropriate and evidence-based imaging practice to the benefit of patients worldwide.
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