Construction and validation of the predictive models for the pathological invasion of early lung adenocarcinoma presenting as ground glass nodules based on 18F-FDG PET/CT
10.3760/cma.j.cn321828-20201229-00462
- VernacularTitle:基于 18F-FDG PET/CT的磨玻璃结节早期肺腺癌浸润性预测模型的构建及验证
- Author:
Xiaoliang SHAO
1
;
Rong NIU
;
Yuetao WANG
;
Zhenxing JIANG
;
Mei XU
;
Xiaonan SHAO
Author Information
1. 苏州大学附属第三医院、常州市第一人民医院核医学科、常州市分子影像重点实验室，常州 213003
- Keywords:
Lung neoplasms;
Adenocarcinoma;
Neoplasm invasiveness;
Positron-emission tomography;
Tomography, X-ray computed;
Fluorodeoxyglucose F18;
Forecasting
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2022;42(7):385-390
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct and verify of the predictive models for pathologic invasion of early lung adenocarcinoma with ground glass nodules (GGNs) based on 18F-FDG PET/CT. Methods:A retrospective analysis was conducted on 149 patients (44 males, 105 females; age (61.1±8.9) years) with pre-invasive lesions/minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) confirmed by pathology after surgery in the First People′s Hospital of Changzhou from October 2011 to October 2019. All patients underwent PET/CT for GGNs. GGNs were randomly divided into a modeling group and validation group with the proportion of 1∶1. Mann-Whitney U test or χ2 test was used to compare the qualitative morphological characteristics (shape, edge characteristics, etc.), quantitative parameters (consolidation-to-tumor ratio, attenuation value of the ground glass opacity (GGO) component on CT (CT GGO), etc.) and quantitative functional parameters (SUV max and SUV index(GGNs SUV max/liver SUV mean) of pre-invasive lesions/MIA and IAC. Logistic regression analysis was used to construct the models, and the ROC curve was used to verify the models′ robustness. Different AUCs were compared by Delong test. Results:A total of 170 GGNs were removed by surgery and confirmed pathologically. In the modeling group ( n=89), the proportion of mixed GGNs, irregular shape, edge characteristics, bronchiectasis/twist/truncation sign, GGNs maximum diameter and solid component maximum diameter, consolidation-to-tumor ratio, CT GGO, SUV max and SUV index in IAC group were significantly higher than those in pre-invasive/MIA group ( χ2 values: 5.00-23.40, z values: from -6.53 to -2.70, all P<0.05). Models 1-3 were constructed based on the qualitative parameters (GGNs type, edge characteristics), quantitative parameters (CT GGO, SUV index), combined qualitative and quantitative parameters (GGNs type, edge characteristics, SUV index) of PET/CT, respectively, and the AUCs of ROC were 0.896, 0.880 and 0.931 in the modeling group, respectively. And the AUC of model 2 was not decreased significantly in the validation group ( n=81; AUC=0.802; z=0.81, P=0.417). Conclusion:The model combined with morphological and functional quantitative parameters of 18F-FDG PET/CT can effectively predict the pathological invasion of early lung adenocarcinoma, and the constructed model is robust.
