Correlation Study of 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Pathological Subtypes of Invasive Lung Adenocarcinoma and Prognosis - Yang, Bin; Ji, Hengshan; Ge, Yingqian; Chen, Sui; Zhu, Hong; Lu, Guangming (Frontiers in Oncology, 2019)
Abstract Purpose:To investigate the correlation between 18-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters and clinicopathological factors in pathological subtypes of invasive lung adenocarcinoma and prognosis. Patients and Methods: Metabolic parameters and clinicopathological factors from 176 consecutive patients with invasive lung adenocarcinoma between August 2008 and August 2016 who underwent 18F-FDG PET/CT examination were retrospectively analyzed. Invasive lung adenocarcinoma was divided into five pathological subtypes:lepidic predominant adenocarcinoma(LPA),acinar predominant adenocarcinoma(APA),papillary predominant adenocarcinoma(PPA),solid predominant adenocarcinoma(SPA),and micropapillary predominant adenocarcinoma(MPA).The differences in metabolic parameters(maximal standard uptake value[SUVmax],mean standard uptake value[SUVmean],total lesion glycolysis[TLG],and metabolic tumor volume [MTV]) and tumor diameter for different pathological subtypes were analyzed. Patients were divided into two groups according to their prognosis: good prognosis group [LPA, APA, PPA])and poor prognosis group[SPA, MPA]).Logistic regression was used to filter predictors and construct a predictive model, and areas under the receiver operating curve (AUC) were calculated. Cox regression analysis was performed on prognostic factors. Results:82(46.6%)females and 94 (53.4%)males of patients with invasive lung adenocarcinoma were enrolled in this study. Metabolic parameters and tumor diameter of different pathological subtype had statistically significant(P<0.05). The predictive model constructed using independent predictors (Distant metastasis,Ki-67 and SUVmax) had good classification performance for both groups.The AUC for SUVmax was 0.694 and combined with clinicopathological factors were 0.745. Cox regression analysis revealed that Stage, TTF-1, MTV and pathological subtype were independent risk factors for patient prognosis.The hazard ratio(HR) of the poor prognosis group was 1.948 (95% CI 1.042–3.641) times the good prognosis group. The mean survival times of good and poor prognosis group were 50.2621 (95% CI 47.818–52.706) and 35.8214 (95% CI 27.483–44.159) months respectively, while the median survival time was 47.00 (95% CI 45.000–50.000) and 31.50 (95% CI 23.000–49.000) months respectively. Conclusion: PET/CT metabolic parameters combined with clinicopathological factors had good classification performance for the different pathological subtypes, which may provide a reference for treatment strategies and prognosis evaluation of patients.