基于 2-[F]FDG PET/CT 影像组学特征对免疫组化结果不确定的原发性乳腺癌 HER2 状态判断的预测价值。

Predictive value of radiomic signature based on 2-[F]FDG PET/CT in HER2 status determination for primary breast cancer with equivocal IHC results.

机构信息

Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China; National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.

Department of Nuclear Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510289, China.

出版信息

Eur J Radiol. 2023 Oct;167:111050. doi: 10.1016/j.ejrad.2023.111050. Epub 2023 Aug 16.

DOI:10.1016/j.ejrad.2023.111050

PMID:37598640

Abstract

PURPOSE

To evaluate the predictive power of 2-[F]FDG PET/CT-derived radiomic signature in human epidermal growth factor receptor 2 (HER2) status determination for primary breast cancer (BC) with equivocal immunohistochemistry (IHC) results for HER2.

METHODS

A total of 154 primary BC with equivocal IHC results for HER2 were retrospectively enrolled in the study. First, the following five conventional PET parameters (SUVmax, SUVmean, SUVpeak, MTV, TLG) were measured and compared between HER2-positive and HER2-negative cohorts. After quantitative radiomic features extraction and reduction, the least absolute shrinkage and selection operator (LASSO) algorithm was used to establish a radiomic signature model. Then, the area under the curve (AUCs) after a receiver operator characteristic (ROC) analysis, accuracy, sensitivity and specificity were calculated and used as the main outcomes. Finally, a total of 37 BC patients from an external institution were included to perform an external validation.

RESULTS

All the five conventional PET parameters were unable to discriminate between HER2-positive and HER2-negative cohorts for BC (P = 0.104-0.544). Whereas, the developed radiomic signature model was potentially predictive of HER2 status with an of AUC 0.887 (95% confidence interval [CI], 0.824-0.950) in the training cohort and 0.766 (95% CI, 0.616-0.916) in the validation cohort, respectively. For external validation, the AUC for the external test cohort was 0.788 (95% CI, 0.633-0.944).

CONCLUSIONS

Radiomic signature based on 2-[F]FDG PET/CT images was capable of non-invasively predicting the HER2 status with a comparable ability to FISH assay, especially for those with equivocal IHC results for HER2.

摘要

目的

评估 2-[F]FDG PET/CT 衍生的放射组学特征在人表皮生长因子受体 2（HER2）状态确定方面的预测能力，该特征用于原发性乳腺癌（BC），HER2 的免疫组织化学（IHC）结果不确定。

方法

本研究回顾性纳入了 154 例 HER2 IHC 结果不确定的原发性 BC 患者。首先，在 HER2 阳性和 HER2 阴性队列之间测量并比较了以下五个常规 PET 参数（SUVmax、SUVmean、SUVpeak、MTV、TLG）。在进行定量放射组学特征提取和降维后，使用最小绝对收缩和选择算子（LASSO）算法建立放射组学特征模型。然后，通过接受者操作特征（ROC）分析计算曲线下面积（AUC）、准确性、敏感性和特异性，并将其作为主要结果。最后，从外部机构纳入了 37 例 BC 患者进行外部验证。

结果

对于 BC，所有五个常规 PET 参数均无法区分 HER2 阳性和 HER2 阴性队列（P=0.104-0.544）。然而，所开发的放射组学特征模型具有预测 HER2 状态的潜力，在训练队列中的 AUC 为 0.887（95%置信区间 [CI]，0.824-0.950），在验证队列中的 AUC 为 0.766（95% CI，0.616-0.916）。对于外部验证，外部测试队列的 AUC 为 0.788（95% CI，0.633-0.944）。