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。
