Background

The biologic meaning of prognostic radiomics phenotypes remains poorly understood, hampered in part by lack of multicenter reproducible evidence.

Purpose

To uncover the biologic meaning of individual prognostic radiomics phenotypes in glioblastomas using paired MRI and RNA sequencing data and to validate the reproducibility of the identified radiogenomics linkages externally.

Materials and Methods

This retrospective multicenter study included four data sets gathered between January 2015 and December 2016. From a radiomics analysis set, a 13-feature radiomics signature was built using preoperative MRI for overall survival prediction. Using a radiogenomics training set with both MRI and RNA sequencing, biologic pathways were enriched and correlated with each of the 13 radiomics phenotypes. Radiomics-correlated key genes were identified to derive a prognostic radiomics gene expression (RadGene) score. The reproducibility of identified pathways and genes was validated with an external test set and a public data set (The Cancer Genome Atlas [TCGA]). A log-rank test was performed to assess prognostic significance.

Results

A total of 435 patients (mean age, 55 years ± 15 [standard deviation]; 263 men) were enrolled. The radiomics signature was associated with overall survival (hazard ratio [HR], 3.68; 95% CI: 2.08, 6.52; P < .001) in the radiomics validation subset. Four types of prognostic radiomics phenotypes were correlated with distinct pathways: immune, proliferative, treatment responsive, and cellular functions (false-discovery rate < 0.10). Thirty radiomics-correlated genes were identified. The prognostic significance of the RadGene score was confirmed in an external test set (HR, 2.02; 95% CI: 1.19, 3.41; P = .01) and a TCGA test set (HR, 1.43; 95% CI: 1.001, 2.04; P = .048). The radiomics-associated pathways and key genes can be replicated in an external test set.

Conclusion

Individual radiomics phenotypes on MRI scans predictive of overall survival were driven by distinct key pathways involved in immune regulation, tumor proliferation, treatment responses, and cellular functions in glioblastoma, which could be reproduced externally.

© RSNA, 2021

Online supplemental material is available for this article.

中文翻译：

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成对的 MRI 和 RNA 测序在胶质母细胞瘤中作为预后放射组学表型的生物学途径

背景

预后放射组学表型的生物学意义仍然知之甚少，部分原因是缺乏多中心可重复的证据。

目的

使用成对的 MRI 和 RNA 测序数据揭示胶质母细胞瘤中个体预后放射组学表型的生物学意义，并在外部验证已识别的放射基因组学联系的可重复性。

材料和方法

这项回顾性多中心研究包括 2015 年 1 月至 2016 年 12 月期间收集的四个数据集。从放射组学分析集中，使用术前 MRI 构建了 13 个特征的放射组学特征，以预测总生存期。使用具有 MRI 和 RNA 测序的放射基因组学训练集，丰富了生物途径并与 13 种放射组学表型中的每一种相关联。确定了与放射组学相关的关键基因，以得出预后放射组学基因表达 (RadGene) 评分。使用外部测试集和公共数据集（癌症基因组图谱 [TCGA]）验证了已识别通路和基因的可重复性。进行对数秩检验以评估预后意义。

结果

总共招募了 435 名患者（平均年龄，55 岁 ± 15 [标准差]；263 名男性）。放射组学特征与放射组学验证子集中的总生存期相关（风险比 [HR]，3.68；95% CI：2.08，6.52 ；P < .001）。四种类型的预后放射组学表型与不同的途径相关：免疫、增殖、治疗反应和细胞功能（错误发现率 < 0.10）。确定了三十个放射组学相关基因。RadGene 评分的预后意义在外部测试集（HR，2.02；95% CI：1.19, 3.41；P = .01）和 TCGA 测试集（HR，1.43；95% CI：1.001，2.04；P = .048）。放射组学相关通路和关键基因可以在外部测试集中复制。

结论

MRI 扫描中预测总生存期的个体放射组学表型是由参与免疫调节、肿瘤增殖、治疗反应和胶质母细胞瘤细胞功能的不同关键途径驱动的，这些途径可以在外部复制。

©北美放射学会，2021

本文提供了在线补充材料。