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基于CT的影像组学特征预测非小细胞肺癌中CD8+肿瘤浸润淋巴细胞

CT-based radiomics signature to predict CD8+ tumor infiltrating lymphocytes in non-small-cell lung cancer.

作者信息

Chen Yaxi, Xu Ting, Jiang Changsi, You Shuyuan, Cheng Zhiqiang, Gong Jingshan

机构信息

The Second Clinical Medical College, Jinan University, Shenzhen, PR China.

Department of Radiology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, PR China.

出版信息

Acta Radiol. 2023 Apr;64(4):1390-1399. doi: 10.1177/02841851221126596. Epub 2022 Sep 18.

Abstract

BACKGROUND

An abundance of CD8+ tumor infiltrating lymphocytes (TILs) in the center of solid tumors is a reliable predictive biomarker for patients eligible for immunotherapy.

PURPOSE

To develop a computed tomography (CT)-based radiomics signature for a preoperative prediction of an abundance of CD8+ TILs in non-small-cell lung cancer (NSCLC).

MATERIAL AND METHODS

In this retrospective study, 117 consecutive patients with pathologically confirmed NSCLC were included and randomly divided into training (n = 77) and test sets (n = 40). A total of 107 radiomics features were extracted from the three-dimensional volumes of interest of each patient. Least absolute shrinkage and selection operator (LASSO) regression was used to select the strongest features for abundance of CD8+ TILs in NSCLC, and the radiomics score was constructed through a linear combination of these selected features. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the radiomics score.

RESULTS

The radiomics score was associated with an abundance of CD8+ TILs in NSCLC, which achieved an area under the curve (AUC) of 0.83 (95% CI=0.73-0.92) and 0.68 (95% CI=0.54-0.87) in the training and test sets, respectively. The difference was not statistically significant ( = 0.20). The tumors with high CD8+ TILs tended to have heterogeneous dependences (high value of Dependence Non-Uniformity Normalized) and complicated texture (high value of Informational Measure of Correlation 1).

CONCLUSION

CT-based radiomics features have the ability to predict CD8+ TILs expression levels of an abundance of CD8+ TILs in NSCLC, which was shown to be a potential imaging biomarker for stratifying patients who may benefit from immunotherapy.

摘要

背景

实体瘤中心大量的CD8 +肿瘤浸润淋巴细胞(TILs)是适合免疫治疗患者的可靠预测生物标志物。

目的

开发一种基于计算机断层扫描(CT)的放射组学特征,用于术前预测非小细胞肺癌(NSCLC)中CD8 + TILs的数量。

材料与方法

在这项回顾性研究中,纳入了117例经病理证实的NSCLC患者,并随机分为训练组(n = 77)和测试组(n = 40)。从每位患者的三维感兴趣体积中提取了总共107个放射组学特征。使用最小绝对收缩和选择算子(LASSO)回归来选择NSCLC中CD8 + TILs数量的最强特征,并通过这些选定特征的线性组合构建放射组学评分。采用受试者操作特征(ROC)曲线分析来评估放射组学评分的预测性能。

结果

放射组学评分与NSCLC中CD8 + TILs的数量相关,在训练组和测试组中,曲线下面积(AUC)分别为0.83(95%CI = 0.73 - 0.92)和0.68(95%CI = 0.54 - 0.87)。差异无统计学意义(P = 0.20)。CD8 + TILs数量高的肿瘤往往具有异质性依赖性(依赖性非均匀性标准化值高)和复杂纹理(相关性信息度量1值高)。

结论

基于CT的放射组学特征能够预测NSCLC中大量CD8 + TILs的CD8 + TILs表达水平,这被证明是用于对可能从免疫治疗中获益的患者进行分层的潜在影像学生物标志物。

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