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小儿神经母细胞瘤的放射组学:基于 CT 的放射组学特征预测 MYCN 扩增。

Radiogenomics of neuroblastoma in pediatric patients: CT-based radiomics signature in predicting MYCN amplification.

机构信息

Department of Radiology, Xinhua Hospital affiliated of Shanghai Jiao Tong University School of Medicine, No.1665 Kongjiang Road, Yangpu District, Shanghai City, 200082, China.

Department of Pathology, Xinhua Hospital affiliated of Shanghai Jiao Tong University School of Medicine, No.1665 Kongjiang Road, Yangpu District, Shanghai City, 200082, China.

出版信息

Eur Radiol. 2021 May;31(5):3080-3089. doi: 10.1007/s00330-020-07246-1. Epub 2020 Oct 29.

Abstract

OBJECTIVES

To construct a CT-based radiomics signature and assess its performance in predicting MYCN amplification (MNA) in pediatric patients with neuroblastoma.

METHODS

Seventy-eight pediatric patients with neuroblastoma were recruited (55 in training cohort and 23 in test cohort). Radiomics features were extracted automatically from the region of interest (ROI) manually delineated on the three-phase computed tomography (CT) images. Selected radiomics features were retained to construct radiomics signature and a radiomics score (rad-score) was calculated by using the radiomics signature-based formula. A clinical model was established with clinical factors, including clinicopathological data, and CT image features. A combined nomogram was developed with the incorporation of a radiomics signature and clinical factors. The predictive performance was assessed by receiver operating characteristics curve (ROC) analysis and decision curve analysis (DCA).

RESULTS

The radiomics signature was constructed using 7 selected radiomics features. The clinical radiomics nomogram, which was based on the radiomics signature and two clinical factors, showed superior predictive performance compared with the clinical model alone (area under the curve (AUC) in the training cohort: 0.95 vs. 0.82, the test cohort: 0.91 vs. 0.70). The clinical utility of clinical radiomics nomogram was confirmed by DCA.

CONCLUSIONS

This proposed CT-based radiomics signature was able to predict MNA. Combining the radiomics signature with clinical factors outperformed using clinical model alone for MNA prediction.

KEY POINTS

• A CT-based radiomics signature has the ability to predict MYCN amplification (MNA) in neuroblastoma. • Both pre- and post-contrast CT images are valuable in predicting MNA. • Associating the radiomics signature with clinical factors improved the predictive performance of MNA, compared with clinical model alone.

摘要

目的

构建基于 CT 的放射组学特征,并评估其在预测神经母细胞瘤患儿 MYCN 扩增(MNA)中的性能。

方法

共纳入 78 例神经母细胞瘤患儿(训练队列 55 例,测试队列 23 例)。从手动勾画的感兴趣区(ROI)的三期 CT 图像中自动提取放射组学特征。选择放射组学特征以构建放射组学特征,并使用放射组学特征构建公式计算放射组学评分(rad-score)。基于临床因素(包括临床病理数据和 CT 图像特征)构建临床模型。通过纳入放射组学特征和临床因素,开发联合列线图。通过受试者工作特征曲线(ROC)分析和决策曲线分析(DCA)评估预测性能。

结果

使用 7 个选定的放射组学特征构建放射组学特征。基于放射组学特征和两个临床因素的临床放射组学列线图,与单独的临床模型相比,具有更好的预测性能(训练队列的曲线下面积(AUC):0.95 比 0.82,测试队列:0.91 比 0.70)。DCA 证实了临床放射组学列线图的临床实用性。

结论

本研究提出的基于 CT 的放射组学特征能够预测 MNA。将放射组学特征与临床因素相结合,用于预测 MNA 优于单独使用临床模型。

关键点

• CT 基放射组学特征能够预测神经母细胞瘤中的 MYCN 扩增(MNA)。

• 增强和未增强 CT 图像均对预测 MNA 有价值。

• 将放射组学特征与临床因素相结合,与单独使用临床模型相比,提高了 MNA 的预测性能。

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