潜在的抗人表皮生长因子受体2靶向治疗受益者：基于MRI的放射组学在鉴别乳腺癌人表皮生长因子受体2低表达状态中的作用

Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI-Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2-Low Status of Breast Cancer.

作者信息

Bian Xiaoqian, Du Siyao, Yue Zhibin, Gao Si, Zhao Ruimeng, Huang Guoliang, Guo Liangcun, Peng Can, Zhang Lina

机构信息

Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.

School of Intelligent Medicine, China Medical University, Shenyang, China.

出版信息

J Magn Reson Imaging. 2023 Nov;58(5):1603-1614. doi: 10.1002/jmri.28628. Epub 2023 Feb 10.

DOI:10.1002/jmri.28628

PMID:36763035

Abstract

BACKGROUND

Multiparametric MRI radiomics could distinguish human epidermal growth factor receptor 2 (HER2)-positive from HER2-negative breast cancers. However, its value for further distinguishing HER2-low from HER2-negative breast cancers has not been investigated.

PURPOSE

To investigate whether multiparametric MRI-based radiomics can distinguish HER2-positive from HER2-negative breast cancers (task 1) and HER2-low from HER2-negative breast cancers (task 2).

STUDY TYPE

Retrospective.

POPULATION

Task 1: 310 operable breast cancer patients from center 1 (97 HER2-positive and 213 HER2-negative); task 2: 213 HER2-negative patients (108 HER2-low and 105 HER2-zero); 59 patients from center 2 (16 HER2-positive, 27 HER2-low and 16 HER2-zero) for external validation.

FIELD STRENGTH/SEQUENCE: A 3.0 T/T1-weighted contrast-enhanced imaging (T1CE), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC).

ASSESSMENT

Patients in center 1 were assigned to a training and internal validation cohort at a 2:1 ratio. Intratumoral and peritumoral features were extracted from T1CE and ADC. After dimensionality reduction, the radiomics signatures (RS) of two tasks were developed using features from T1CE (RS-T1CE), ADC (RS-ADC) alone and T1CE + ADC combination (RS-Com).

STATISTICAL TESTS

Mann-Whitney U tests, the least absolute shrinkage and selection operator, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

RESULTS

For task 1, RS-ADC yielded higher area under the ROC curve (AUC) in the training, internal, and external validation of 0.767/0.725/0.746 than RS-T1CE (AUC = 0.733/0.674/0.641). For task 2, RS-T1CE yielded higher AUC of 0.765/0.755/0.678 than RS-ADC (AUC = 0.706/0.608/0.630). For both of task 1 and task 2, RS-Com achieved the best performance with AUC of 0.793/0.778/0.760 and 0.820/0.776/0.711, respectively, and obtained higher clinical benefit in DCA compared with RS-T1CE and RS-ADC. The calibration curves of all RS demonstrated a good fitness.

DATA CONCLUSION

Multiparametric MRI radiomics could noninvasively and robustly distinguish HER2-positive from HER2-negative breast cancers and further distinguish HER2-low from HER2-negative breast cancers.

EVIDENCE LEVEL

TECHNICAL EFFICACY

Stage 2.

摘要

背景

多参数MRI放射组学能够区分人表皮生长因子受体2（HER2）阳性和HER2阴性乳腺癌。然而，其在进一步区分HER2低表达和HER2阴性乳腺癌方面的价值尚未得到研究。

目的

研究基于多参数MRI的放射组学能否区分HER2阳性和HER2阴性乳腺癌（任务1）以及HER2低表达和HER2阴性乳腺癌（任务2）。

研究类型

回顾性研究。

研究对象

任务1：来自中心1的310例可手术乳腺癌患者（97例HER2阳性，213例HER2阴性）；任务2：213例HER2阴性患者（108例HER2低表达，105例HER2零表达）；来自中心2的59例患者（16例HER2阳性，27例HER2低表达，16例HER2零表达）用于外部验证。

场强/序列：3.0 T/T1加权对比增强成像（T1CE）、扩散加权成像（DWI）衍生的表观扩散系数（ADC）。

评估

中心1的患者按2:1的比例分为训练组和内部验证队列。从T1CE和ADC中提取瘤内和瘤周特征。降维后，使用T1CE（RS-T1CE）、单独的ADC（RS-ADC）以及T1CE + ADC组合（RS-Com）的特征分别生成两个任务的放射组学特征（RS）。

统计检验

曼-惠特尼U检验、最小绝对收缩和选择算子、受试者操作特征（ROC）曲线、校准曲线以及决策曲线分析（DCA）。

结果

对于任务1，在训练组、内部验证组和外部验证组中，RS-ADC的ROC曲线下面积（AUC）分别为0.767/0.725/0.746，高于RS-T1CE（AUC = 0.733/0.674/ .641）。对于任务2，RS-T1CE的AUC为0.765/0.755/0.678，高于RS-ADC（AUC = 0.706/0.608/0.630）。对于任务1和任务2，RS-Com均表现最佳，AUC分别为0.793/0.778/0.760和0.820/ .776/0.711，并且与RS-T1CE和RS-ADC相比，在DCA中获得了更高的临床获益。所有RS的校准曲线均显示出良好的拟合度。