A Nomogram for the Prediction of Invasiveness in Invasive Pulmonary Adenocarcinoma on the Basis of Multimodal PET/CT Parameters

Abstract

Objective

We investigated the value of PET/CT-based multimodal parameters in predicting the degree of differentiation and epidermal growth factor receptor (EGFR) mutations in invasive lung adenocarcinoma (ILA) and assessed the correlation between PET/CT-based multimodal parameters and Ki67.

Methods

We retrospectively collected 113 patients with ILA who underwent PET/CT examination, and differences in PET/CT multimodal parameters between different differentiation groups were analyzed. Binary logistic regression was used to establish a multiparameter model for predicting EGFR mutation, and ROC curve was used to compare the diagnostic efficiency. Independent predictors of the Ki67 index were screened using multiple linear regression analysis.

Results

The poorly differentiated group was more likely to have large-diameter, solid foci, pleural pulling signs, and vacuolar signs compared with other groups (all P < 0.05). The differences in metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in all three different differentiated groups were statistically significant compared to the other parameters (all P < 0.05). The PET/CT regression model predicted EGFR mutations with an AUC of 0.820 and was higher than other models; the sensitivity, specificity, positive predictive value, and negative predictive value for discriminating EGFR mutations were 84.74%, 70.37%, 75.76%, and 80.85%, respectively. PET/CT multiple linear regression analysis showed that vascular convergence, SUVpeak, MTV, and TLG explaining 62.0% changes in Ki67 (R² = 0.620). SUVpeak, MTV, and TLG (r = 0.580, r = 0.662, and r = 0.680, all P < 0.001) were all strongly correlated with increased Ki67 index.

Conclusion

MTV and TLG can better identify the degree of ILA differentiation compared to CT and other PET parameters. The nomogram constructed by multimodal PET/CT parameters can better dynamically monitor the changes of EGFR status and Ki67 index.