Department of Nuclear Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Nuclear Medicine, Changshu No. 2 People's Hospital, Changshu, China.
J Cancer Res Ther. 2024 Apr 1;20(2):599-607. doi: 10.4103/jcrt.jcrt_1674_23. Epub 2024 Apr 30.
It is crucially essential to differentially diagnose single-nodule pulmonary metastases (SNPMs) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC), which has important clinical implications for treatment strategies. In this study, we aimed to establish a feasible differential diagnosis model by combining 18F-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) radiomics, computed tomography (CT) radiomics, and clinical features.
CRC patients with SNPM or SPLC who underwent 18F-FDG PET/CT from January 2013 to July 2022 were enrolled in this retrospective study. The radiomic features were extracted by manually outlining the lesions on PET/CT images, and the radiomic modeling was realized by various screening methods and classifiers. In addition, clinical features were analyzed by univariate analysis and logistic regression (LR) analysis to be included in the combined model. Finally, the diagnostic performances of these models were illustrated by the receiver operating characteristic (ROC) curves and the area under the curve (AUC).
We studied data from 61 patients, including 36 SNPMs and 25 SPLCs, with an average age of 65.56 ± 10.355 years. Spicule sign and ground-glass opacity (GGO) were significant independent predictors of clinical features (P = 0.012 and P < 0.001, respectively) to build the clinical model. We achieved a PET radiomic model (AUC = 0.789), a CT radiomic model (AUC = 0.818), and a PET/CT radiomic model (AUC = 0.900). The PET/CT radiomic models were combined with the clinical model, and a well-performing model was established by LR analysis (AUC = 0.940).
For CRC patients, the radiomic models we developed had good performance for the differential diagnosis of SNPM and SPLC. The combination of radiomic and clinical features had better diagnostic value than a single model.
对结直肠癌（CRC）患者的单发性肺转移瘤（SNPM）和第二原发性肺癌（SPLC）进行鉴别诊断至关重要，这对治疗策略具有重要的临床意义。本研究旨在建立一种基于 18F-氟脱氧葡萄糖正电子发射断层扫描（18F-FDG PET）放射组学、计算机断层扫描（CT）放射组学和临床特征的可行鉴别诊断模型。
本回顾性研究纳入了 2013 年 1 月至 2022 年 7 月期间接受 18F-FDG PET/CT 检查的 SNPM 或 SPLC 的 CRC 患者。通过手动勾画 PET/CT 图像上的病变提取放射组学特征，并通过各种筛选方法和分类器实现放射组学建模。此外，通过单变量分析和逻辑回归（LR）分析对临床特征进行分析，将其纳入联合模型。最后，通过受试者工作特征（ROC）曲线和曲线下面积（AUC）来展示这些模型的诊断性能。
我们研究了 61 例患者的数据，包括 36 例 SNPM 和 25 例 SPLC，平均年龄为 65.56±10.355 岁。刺状征和磨玻璃影（GGO）是临床特征的独立显著预测因子（P=0.012 和 P<0.001），用于构建临床模型。我们构建了一个 PET 放射组学模型（AUC=0.789）、一个 CT 放射组学模型（AUC=0.818）和一个 PET/CT 放射组学模型（AUC=0.900）。PET/CT 放射组学模型与临床模型相结合，通过 LR 分析建立了一个性能良好的模型（AUC=0.940）。
对于 CRC 患者，我们开发的放射组学模型对 SNPM 和 SPLC 的鉴别诊断具有良好的性能。放射组学特征与临床特征的结合比单一模型具有更好的诊断价值。
