Clinical Investigation
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
Shao Xiaoliang, Niu Rong, Wang Yuetao, Jiang Zhenxing, Xu Mei, Shao Xiaonan
Published 2022-07-25
Cite as Chin J Nucl Med Mol Imaging, 2022, 42(7): 385-390. DOI: 10.3760/cma.j.cn321828-20201229-00462
Abstract
ObjectiveTo 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.
MethodsA 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 orχ2 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 (CTGGO), etc.) and quantitative functional parameters (SUVmax and SUVindex(GGNs SUVmax/liver SUVmean) 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.
ResultsA 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, CTGGO, SUVmax and SUVindex 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 (CTGGO, SUVindex), combined qualitative and quantitative parameters (GGNs type, edge characteristics, SUVindex) 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).
ConclusionThe 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.
Key words:
Lung neoplasms; Adenocarcinoma; Neoplasm invasiveness; Positron-emission tomography; Tomography, X-ray computed; Fluorodeoxyglucose F18; Forecasting
Contributor Information
Shao Xiaoliang
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Niu Rong
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Wang Yuetao
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Jiang Zhenxing
Department of Radiology, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou 213003, China
Xu Mei
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Shao Xiaonan
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
