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基于MRI的放射组学对原发性中枢神经系统弥漫性大B细胞淋巴瘤患者的预后评估

Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics.

作者信息

Liu Jianpeng, Tu Jiaqi, Hu Bin, Li Chao, Piao Sirong, Lu Yucheng, Li Anning, Ding Tianling, Xiong Ji, Zhu Fengping, Li Yuxin

机构信息

Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.

Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK.

出版信息

J Magn Reson Imaging. 2025 Mar;61(3):1142-1152. doi: 10.1002/jmri.29533. Epub 2024 Jul 6.

Abstract

BACKGROUND

Primary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment.

PURPOSE

To develop and validate an MRI-based radiomics model and combine it with clinical factors to assess progression-free survival (PFS) and overall survival (OS) of patients with PCNSL.

STUDY TYPE

Retrospective and prospective.

POPULATION

Three hundred seventy-nine patients (179 female, 53 ± 7 years) from 2014 to 2022.

FIELD STRENGTH/SEQUENCE: T2/fluid-attenuated inversion recovery, contrast-enhanced T1WI and diffusion-weighted echo-planar imaging sequences on 3.0 T.

ASSESSMENT

Radiomics features were extracted from enhanced tumor regions on preoperative multi-sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance.

STATISTICAL TESTS

Chi-squared, Mann-Whitney, Kaplan-Meier, log-rank, LASSO, Cox, decision curve analysis, time-dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P-value <0.05 was considered significant.

RESULTS

Follow-up duration was 28.79 ± 22.59 months (median: 25). High-risk patients, determined by the median radiomics score, showed significantly lower survival rates than low-risk patients. Compared with NCCN-IPI, conventional imaging and clinical models, the combined model achieved the highest C-index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1-year, 3-year, and 5-year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1-year and 3-year survival in external validation.

DATA CONCLUSION

Incorporating a multi-sequence MR-based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

摘要

背景

原发性中枢神经系统淋巴瘤(PCNSL)预后较差。放射组学在预后评估中可能具有潜在价值。

目的

开发并验证基于MRI的放射组学模型,并将其与临床因素相结合,以评估PCNSL患者的无进展生存期(PFS)和总生存期(OS)。

研究类型

回顾性和前瞻性研究。

研究对象

2014年至2022年的379例患者(179例女性,年龄53±7岁)。

场强/序列:3.0T上的T2/液体衰减反转恢复序列、对比增强T1WI和扩散加权回波平面成像序列。

评估

从术前多序列MRI上的增强肿瘤区域提取放射组学特征。使用最小绝对收缩和选择算子(LASSO)Cox回归模型在训练队列(N = 169)中选择放射组学特征。构建临床、放射组学和联合模型的Cox比例风险模型,通过内部队列(N = 72)和外部队列(N = 32)验证模型性能。

统计检验

卡方检验、曼-惠特尼检验、Kaplan-Meier检验、对数秩检验、LASSO检验、Cox检验、决策曲线分析、时间依赖性受试者工作特征曲线、曲线下面积(AUC)和似然比检验。P值<0.05被认为具有统计学意义。

结果

随访时间为28.79±22.59个月(中位数:25个月)。根据放射组学评分中位数确定的高危患者生存率显著低于低危患者。与NCCN-IPI、传统影像和临床模型相比,联合模型在验证中PFS(内部C指数为0.660,外部为0.802)和OS(内部C指数为0.733,外部为0.781)的C指数最高。放射组学的净效益大于单纯临床模型。联合模型在内部验证中预测1年、3年和5年PFS的AUC分别为0.680、0.752和0.830,预测OS的AUC分别为0.770、0.789和0.863;在外部验证中,预测1年和3年生存的PFS AUC分别为0.860和0.826,OS AUC分别为0.859和0.748。

数据结论

将基于多序列MR的放射组学模型纳入临床模型可提高PCNSL预后评估的准确性。

证据水平

4级 技术效能:2级

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