Wang Jie, Zheng Zhonghang, Zhang Yi, Tan Weiyue, Li Jing, Xing Ligang, Sun Xiaorong
Department of Graduate, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Front Oncol. 2023 Jul 21;13:1185808. doi: 10.3389/fonc.2023.1185808. eCollection 2023.
To explore a prediction model for lymphovascular invasion (LVI) on cTNM radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[F]fluoro-D-glucose ([F]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis.
The present work retrospectively included 148 patients receiving surgical resection and verified pathologically with cTNM radiologic solid NSCLC. The cases were randomized into training or validation sets in the ratio of 7:3. PET and CT images were used to select optimal radiomics features. Three radiomics predictive models incorporating CT, PET, as well as PET/CT images radiomics features (CT-RS, PET-RS, PET/CT-RS) were developed using logistic analyses. Furthermore, model performance was evaluated by ROC analysis for predicting LVI status. Model performance was evaluated in terms of discrimination, calibration along with clinical utility. Kaplan-Meier curves were employed to analyze the outcome of LVI.
The ROC analysis demonstrated that PET/CT-RS (AUCs were 0.773 and 0.774 for training and validation sets) outperformed both CT-RS(AUCs, 0.727 and 0.752) and PET-RS(AUCs, 0.715 and 0.733). A PET/CT radiology nomogram (PET/CT-model) was developed to estimate LVI; the model demonstrated conspicuous prediction performance for training (C-index, 0.766; 95%CI, 0.728-0.805) and validation sets (C-index, 0.774; 95%CI, 0.702-0.846). Besides, decision curve analysis and calibration curve showed that PET/CT-model provided clinically beneficial effects. Disease-free survival and overall survival varied significantly between LVI and non-LVI cases (P<0.001).
The PET/CT radiomics models could effectively predict LVI on early stage radiologic solid lung cancer and provide support for clinical treatment decisions.
基于2-脱氧-2[F]氟-D-葡萄糖（[F]F-FDG）正电子发射断层扫描-计算机断层扫描（PET-CT）影像组学分析，探索cTNM影像学实性非小细胞肺癌（NSCLC）中脉管侵犯（LVI）的预测模型。
本研究回顾性纳入148例行手术切除且经病理证实为cTNM影像学实性NSCLC的患者。病例按7:3的比例随机分为训练集或验证集。利用PET和CT图像选择最佳影像组学特征。采用逻辑分析建立了包含CT、PET以及PET/CT图像影像组学特征的三种影像组学预测模型（CT-RS、PET-RS、PET/CT-RS）。此外，通过ROC分析评估模型预测LVI状态的性能。从区分度、校准度以及临床实用性方面评估模型性能。采用Kaplan-Meier曲线分析LVI的预后。
ROC分析表明，PET/CT-RS（训练集和验证集的AUC分别为0.773和0.774）优于CT-RS（AUC分别为0.727和0.752）和PET-RS（AUC分别为0.715和0.733）。开发了一种PET/CT影像学列线图（PET/CT模型）来估计LVI；该模型在训练集（C指数，0.766；95%CI，0.728-0.805）和验证集（C指数，0.774；95%CI，0.702-0.846）中表现出显著的预测性能。此外，决策曲线分析和校准曲线表明PET/CT模型具有临床益处。LVI和非LVI病例之间的无病生存期和总生存期差异显著（P<0.001）。
PET/CT影像组学模型可有效预测早期影像学实性肺癌中的LVI，并为临床治疗决策提供支持。
