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1至2厘米胃胃肠道间质瘤的风险分层:CT和EUS高危特征的视觉评估与CT影像组学分析

Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.

作者信息

Jia Xiaoxuan, Wan Lijuan, Chen Xiaoshan, Ji Wanying, Huang Shaoqing, Qi Yuangang, Cui Jingjing, Wei Shengcai, Cheng Jin, Chai Fan, Feng Caizhen, Liu Yulu, Zhang Hongmei, Sun Yingshi, Hong Nan, Rao Shengxiang, Zhang Xinhua, Xiao Youping, Ye Yingjiang, Tang Lei, Wang Yi

机构信息

Department of Radiology, Peking University People's Hospital, Beijing, 100044, China.

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

出版信息

Eur Radiol. 2023 Apr;33(4):2768-2778. doi: 10.1007/s00330-022-09228-x. Epub 2022 Nov 30.

Abstract

OBJECTIVES

To investigate the ability of CT and endoscopic sonography (EUS) in predicting the malignant risk of 1-2-cm gastric gastrointestinal stromal tumors (gGISTs) and to clarify whether radiomics could be applied for risk stratification.

METHODS

A total of 151 pathologically confirmed 1-2-cm gGISTs from seven institutions were identified by contrast-enhanced CT scans between January 2010 and March 2021. A detailed description of EUS morphological features was available for 73 gGISTs. The association between EUS or CT high-risk features and pathological malignant potential was evaluated. gGISTs were randomly divided into three groups to build the radiomics model, including 74 in the training cohort, 37 in validation cohort, and 40 in testing cohort. The ROIs covering the whole tumor volume were delineated on the CT images of the portal venous phase. The Pearson test and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature selection, and the ROC curves were used to evaluate the model performance.

RESULTS

The presence of EUS- and CT-based morphological high-risk features, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not differ between very-low and intermediate risk 1-2-cm gGISTs (p > 0.05). The radiomics model consisting of five radiomics features showed favorable performance in discrimination of malignant 1-2-cm gGISTs, with the AUC of the training, validation, and testing cohort as 0.866, 0.812, and 0.766, respectively.

CONCLUSIONS

Instead of CT- and EUS-based morphological high-risk features, the CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs.

KEY POINTS

• The presence of EUS- and CT-based morphological high-risk factors, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not correlate with the pathological malignant potential of 1-2-cm gGISTs. • The CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs.

摘要

目的

探讨CT和内镜超声(EUS)预测直径1-2 cm胃胃肠道间质瘤(gGIST)恶性风险的能力,并阐明放射组学是否可用于风险分层。

方法

2010年1月至2021年3月期间,通过对比增强CT扫描从7家机构共识别出151例经病理证实的直径1-2 cm的gGIST。73例gGIST有EUS形态学特征的详细描述。评估EUS或CT高危特征与病理恶性潜能之间的关联。gGIST被随机分为三组以构建放射组学模型,其中训练队列74例,验证队列37例,测试队列40例。在门静脉期的CT图像上勾勒出覆盖整个肿瘤体积的感兴趣区(ROI)。采用Pearson检验和最小绝对收缩和选择算子(LASSO)算法进行特征选择,并用ROC曲线评估模型性能。

结果

基于EUS和CT的形态学高危特征,包括钙化、坏死、肿瘤内异质性、边界不规则或表面溃疡,在极低风险和中度风险的直径1-2 cm gGIST之间无差异(p>0.05)。由五个放射组学特征组成的放射组学模型在鉴别直径1-2 cm恶性gGIST方面表现良好,训练队列、验证队列和测试队列的AUC分别为0.866、0.812和0.766。

结论

CT放射组学模型而非基于CT和EUS的形态学高危特征,可能适用于直径1-2 cm gGIST的术前风险分层。

关键点

• 基于EUS和CT的形态学高危因素,包括钙化、坏死、肿瘤内异质性、边界不规则或表面溃疡,与直径1-2 cm gGIST的病理恶性潜能无关。• CT放射组学模型可能适用于直径1-2 cm gGIST的术前风险分层。

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