Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
Pharmaceutical Diagnostics, GE Healthcare, Beijing, China.
Korean J Radiol. 2022 Sep;23(9):921-930. doi: 10.3348/kjr.2022.0295.
To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19 del) and exon 21 L858R missense (21 L858R) mutations using FDG PET/CT radiomics.
We retrospectively analyzed 179 patients with lung adenocarcinoma. They were randomly assigned to training (n = 125) and testing (n = 54) cohorts in a 7:3 ratio. A total of 2632 radiomics features were extracted from the tumor region of interest from the PET (1316) and CT (1316) images. Six PET/CT radiomics features that remained after the feature selection step were used to calculate the radiomics model score (rad-score). Subsequently, a combined clinical and radiomics model was constructed based on sex, smoking history, tumor diameter, and rad-score. The performance of the combined model in identifying EGFR mutations was assessed using a receiver operating characteristic (ROC) curve. Furthermore, in a subsample of 99 patients, a PET/CT radiomics model for distinguishing 19 del and 21 L858R EGFR mutational subtypes was established, and its performance was evaluated.
The area under the ROC curve (AUROC) and accuracy of the combined clinical and PET/CT radiomics models were 0.882 and 81.6%, respectively, in the training cohort and 0.837 and 74.1%, respectively, in the testing cohort. The AUROC and accuracy of the radiomics model for distinguishing between 19 del and 21 L858R EGFR mutational subtypes were 0.708 and 66.7%, respectively, in the training cohort and 0.652 and 56.7%, respectively, in the testing cohort.
The combined clinical and PET/CT radiomics model could identify the EGFR mutational status in lung adenocarcinoma with moderate accuracy. However, distinguishing between EGFR 19 del and 21 L858R mutational subtypes was more challenging using PET/CT radiomics.
基于 F-氟脱氧葡萄糖（FDG）PET/CT 放射组学和临床特征，识别肺腺癌中的表皮生长因子受体（EGFR）突变，并使用 FDG PET/CT 放射组学区分 EGFR 外显子 19 缺失（19 del）和外显子 21 L858R 错义（21 L858R）突变。
我们回顾性分析了 179 例肺腺癌患者。他们按 7:3 的比例随机分配到训练（n=125）和测试（n=54）队列。从 PET（1316）和 CT（1316）图像的肿瘤感兴趣区域提取了 2632 个放射组学特征。经过特征选择步骤后，保留了 6 个 PET/CT 放射组学特征，用于计算放射组学模型得分（rad-score）。随后，基于性别、吸烟史、肿瘤直径和 rad-score，构建了一个联合临床和放射组学模型。使用接收者操作特征（ROC）曲线评估联合模型识别 EGFR 突变的性能。此外，在 99 例患者的亚样本中，建立了用于区分 19 del 和 21 L858R EGFR 突变亚型的 PET/CT 放射组学模型，并评估其性能。
在训练队列中，联合临床和 PET/CT 放射组学模型的 ROC 曲线下面积（AUROC）和准确率分别为 0.882 和 81.6%，在测试队列中分别为 0.837 和 74.1%。在训练队列中，用于区分 19 del 和 21 L858R EGFR 突变亚型的放射组学模型的 AUROC 和准确率分别为 0.708 和 66.7%，在测试队列中分别为 0.652 和 56.7%。
联合临床和 PET/CT 放射组学模型可以中等准确率识别肺腺癌中的 EGFR 突变状态。然而，使用 PET/CT 放射组学区分 EGFR 19 del 和 21 L858R 突变亚型更具挑战性。
