RÉSUMÉ
Purpose To investigate the clinical value of artificial intelligence(AI)quantitative parameters in predicting the invasion degree of lung adenocarcinoma with diameter≤2 cm of ground-glass density.Materials and Methods A total of 80 patients with lung adenocarcinoma with diameter≤2 cm ground-glass density confirmed by pathology from March 2019 to April 2022 were retrospectively analyzed.A total of 90 nodules were rerolled,including 8 adenocarcinomas in situ(AIS),34 minimally invasive adenocarcinomas(MIA)and 48 invasive adenocarcinomas(IAC).They were divided into the experimental group(IAC)and the control group(AIS and MIA).The differences of the AI quantitative parameters such as volume,three-dimensional length diameter,maximum area,maximum CT value,minimum CT value and average CT value were compared between two groups,and the predictive values of AI quantitative parameters for the invasion degree of lung adenocarcinoma was evaluated.Results There were statistically significant differences with age,volume,three-dimensional length diameter,maximum area,maximum CT value and average CT value between the two groups(all P<0.05),but no statistically significant differences in gender and minimum CT value(both P>0.05).Binary Logistic regression analysis showed that the three-dimensional length diameter(odd ratio=2.020,P=0.034)and the maximum CT value(odd ratio=1.008,P=0.013)were independent predictors for lung adenocarcinoma with diameter≤2 cm of ground-glass density.The regression model based on the three-dimensional length diameter and the maximum CT value had the best predictive performance,and its AUC was 0.901.When the critical value was 2.432,its sensitivity and specificity were 93.75%and 71.43%,respectively.Conclusion AI quantitative parameters have a high value in predicting the degree of invasion of lung adenocarcinoma with diameter≤2 cm of ground-glass density,and the combined model with three dimensional long diameter and maximum CT value has the highest diagnostic efficiency.