Prediction of tumor spread through air spaces of stage Ⅰ lung adenocarcinoma by 18F-FDG PET/CT imaging signs combined with metabolic parameters / 中华核医学与分子影像杂志

ABSTRACT

Objective:To investigate the value of 18F-FDG PET/CT imaging signs and metabolic parameters in predicting tumor spread through air spaces (STAS) of stage Ⅰ lung adenocarcinoma. Methods:From January 2019 to December 2021, clinical, imaging and metabolic parameters of 381 patients (126 males, 255 females, age (61.2±9.2) years) with stage Ⅰ lung adenocarcinoma were retrospectively analyzed in the Affiliated Hospital of Qingdao University. According to the postoperative pathological results, patients were divided into STAS positive group and STAS negative group. According to the operation time, patients were divided into training set ( n=254) and verification set ( n=127). χ2 test or Mann-Whitney U test was used to compare the differences of different parameters between patients with STAS positive and negative, and binary logistic regression analysis was used to select the predictors of STAS status. The prediction model was established, and ROC curve was used to evaluate the predictive efficacy. Results:There were 49(19.3%, 49/254) patients with STAS positive and 205(80.7%, 205/254) patients with STAS negative in the training set, while those were 35(27.6%, 35/127) and 92(72.4%, 92/127) in the verification set. In the training set, the differences of age ( z=-2.30, P=0.021), type of lesions ( χ2=6.81, P=0.009), spiculation ( χ2=12.64, P<0.001), bronchus truncation ( χ2=6.98, P=0.008), ground glass ribbon sign ( χ2=26.93, P<0.001) and SUV max ( z=-4.62, P<0.001) between the two groups were statistically significant. Multivariate logistic regression analysis showed that age (odds ratio ( OR)=1.048, 95% CI: 1.004-1.094, P=0.032), ground glass ribbon sign ( OR=3.857, 95% CI: 1.693-8.788, P=0.001) and SUV max ( OR=1.133, 95% CI: 1.001-1.282, P=0.049) were independent predictors of STAS status in stage Ⅰ lung adenocarcinoma patients. The logistic regression model was P=1/(1+ e - x), x=-5.292+ 0.480×age (year)+ 1.493×ground glass ribbon sign+ 0.170×SUV max. The AUCs of the model in the training set and verification set were 0.770 and 0.801, with the sensitivity of 81.6%(40/49) and 82.9%(29/35), and the specificity of 69.8%(143/205) and 65.2%(60/92), respectively. Conclusion:Age, ground glass ribbon sign and SUV max have good predictive effects on the occurrence of STAS in stage Ⅰ lung adenocarcinoma.