Department of Radiology, Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China.
Translational Medicine Team, GE Healthcare, Shanghai, China.
Eur Radiol. 2022 Feb;32(2):1065-1077. doi: 10.1007/s00330-021-08194-0. Epub 2021 Aug 28.
To assess methods to improve the accuracy of prognosis for clinical stage I solid lung adenocarcinoma using radiomics based on different volumes of interests (VOIs).
This retrospective study included patients with postoperative clinical stage I solid lung adenocarcinoma from two hospitals, center 1 and center 2. Three databases were generated: dataset A (training set from center 1), dataset B (internal test set from center 1), and dataset C (external validation test from center 2). Disease-free survival (DFS) data were collected. CT radiomics models were constructed based on four VOIs: gross tumor volume (GTV), 3 mm external to the tumor border (peritumoral volume [PTV]), 6 mm crossing tumor border (PTV), and 6 mm external to the tumor border (PTV). The area under the receiver operating characteristic curve (AUC) was used to compare the model accuracies.
A total of 334 patients were included (204 and 130 from centers 1 and 2). The model using PTV (AUC 0.81 [95% confidence interval {CI}: 0.75, 0.94], 0.81 [0.63, 0.90] for datasets B and C) outperformed the other three models, GTV (0.73 [0.58, 0.81], 0.73 [0.58, 0.83]), PTV (0.76 [0.52, 0.87], 0.75 [0.60, 0.83]), and PTV (0.72 [0.60, 0.81], 0.69 [0.59, 0.81]), in datasets B and C, all p < 0.05.
A radiomics model based on a VOI of 6 mm crossing tumor border more accurately predicts prognosis of clinical stage I solid lung adenocarcinoma than that based on VOIs including overall tumor or external rims of 3 mm and 6 mm.
• Radiomics is a useful approach to improve the accuracy of prognosis for stage I solid adenocarcinoma. • The radiomics model based on VOIs that includes 3 mm within and external to the tumor border (peritumoral volume [PTV]) outperformed models that included either only the tumor itself or those that only included the peritumoral volume.
评估基于不同感兴趣区(VOI)的放射组学方法来提高临床 I 期实性肺腺癌预后准确性的方法。
本回顾性研究纳入了来自两家医院(中心 1 和中心 2)的术后临床 I 期实性肺腺癌患者。生成了三个数据库:数据集 A(中心 1 的训练集)、数据集 B(中心 1 的内部测试集)和数据集 C(中心 2 的外部验证测试集)。收集无病生存(DFS)数据。基于四个 VOI 构建 CT 放射组学模型:大体肿瘤体积(GTV)、肿瘤边界外 3mm(肿瘤周围体积[PTV])、肿瘤边界外 6mm(PTV)和肿瘤边界外 6mm(PTV)。使用接收者操作特征曲线下面积(AUC)比较模型准确性。
共纳入 334 例患者(中心 1 和中心 2 分别为 204 例和 130 例)。与其他三个模型(GTV 为 0.73[0.58, 0.81],GTV 为 0.73[0.58, 0.83])相比,使用 PTV(AUC 为 0.81[0.75, 0.94],数据集 B 和 C 中的 AUC 为 0.81[0.63, 0.90])的模型表现更好,PTV(0.76[0.52, 0.87],PTV 为 0.75[0.60, 0.83])和 PTV(0.72[0.60, 0.81],PTV 为 0.69[0.59, 0.81]),所有 p 值均<0.05。
与基于包括整体肿瘤或 3mm 和 6mm 外肿瘤边缘的 VOI 的模型相比,基于跨越肿瘤边界的 6mm VOI 的放射组学模型更能准确预测临床 I 期实性肺腺癌的预后。
• 放射组学是提高 I 期实性腺癌预后准确性的一种有用方法。
• 基于包括肿瘤内部和外部 3mm 边界(肿瘤周围体积[PTV])的 VOI 的放射组学模型优于仅包含肿瘤本身或仅包含肿瘤周围体积的模型。