PET/CT联合CT三维重建在鉴别早期肺腺癌不同病理亚型中的价值

BACKGROUND AND OBJECTIVE: The good prognosis of lepidic predominant invasive adenocarcinoma (LPA) and adenocarcinoma in situ (AIS)/microinvasive adenocarcinoma (MIA) in the pathological subtypes of early lung adenocarcinoma is similar, and the means to distinguish LPA from non-LPA is urgently needed in clinical practice. This study intends to analyze the correlation between positron emission computed tomography (PET)/computed tomography (CT) maximal standard uptake value (SUVmax) with CT three-dimensional reconstruction parameters and the pathological subtypes of early lung adenocarcinoma with part-solid nodules (PSNs) in preoperative imaging. METHODS: The data of early lung adenocarcinoma patients who underwent anatomical pneumonectomy at the Department of Thoracic Surgery of Northern Jiangsu People's Hospital from January 2016 to January 2019 retrospectively analyzed and subsolid nodules on imaging were showed. All patients with enhanced chest CT and PET/CT data can be obtained completely, using Mimics software to perform three-dimensional reconstruction to obtain tumor volume, 3-dimensional mean-CT value (3Dm-CT) of tumor and SUVmax, using SPSS 25.0 for statistical analysis and GraphPad Prism 8.3.0 for drawing receiver operating curve (ROC). P < 0.05 indicates that the difference is statistically significant. RESULTS: 67 patients were included in this study. All patients were divided into two groups according to different pathological subtypes. AIS, MIA and LPA in invasive adenocarcinoma (IAC) were in the low-risk group, 28 cases (41.8%), and the remaining non-LPA were in high-risk group, 39 cases (58.2%). SUVmax (t=3.153, P=0.002), tumor volume (t=3.331, P=0.001), solid/ground glass component volume (t=2.74, P=0.006)/(t=3.127, P=0.002) and 3Dm-CT of solid/ground glass component (t=3.655, P < 0.001)/(t=7.082, P < 0.001) between the two groups were all statistically significant. ROC curve prompts: SUVmax [area under curve (AUC)=0.727], tumor volume (AUC=0.740), ground glass component volume (AUC=0.725), 3Dm-CT of solid components (AUC=0.763), 3Dm-CT of ground glass components (AUC=0.756) have the best predictive performance. The above-mentioned covariates with AUC > 0.7 were included in the multivariate ROC curve analysis, and the joint predictor (AUC=0.835) was obtained with medium or above predictive value. CONCLUSION: PET/CT SUVmax and CT three-dimensional reconstruction parameters have a significant correlation with the different pathological subtypes of early lung adenocarcinoma with PSNs in imaging. The combination of SUVmax, tumor volume, ground glass component volume and 3Dm-CT of solid/ground glass component CT value has certain value in identifying the pathological subtype of early stage lung adenocarcinoma with PSNs nodules in imaging.