Baseline computed tomography imaging findings could assist in early diagnosis of visceral pleural invasion for newly discovered early subpleural non-small cell lung cancer: T1 or T2.

BACKGROUND

Preoperative accurate visceral pleural infiltration (VPI) diagnosis for T1-size non-small cell lung cancer (NSCLC) is significant for clinical decision-making. The study aimed to explore the diagnostic efficacy of computed tomography (CT) imaging features and serum biomarkers in diagnosing VPI in newly discovered subpleural NSCLC ≤3 cm.

METHODS

There were 447 patients with NSCLC ≤3 cm retrospectively enrolled and assigned to the VPI group (n=81) and the non-VPI group (n=366) based on elastic fiber staining results. The serum biomarkers and CT imaging features were obtained for each subject. Univariate and multivariate analyses were used to identify the independent predictors for VPI. Area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance of each independent predictor and combined predictors in predicting VPI, with performance compared using the DeLong test.

RESULTS

For tumor biomarkers, the VPI group had a significantly higher percentage of cases with abnormal carcino-embryonic antigen (CEA) level, cytokeratin 19 fragment (CYFRA21-1) level, and pro-gastrin-releasing peptide (ProGRP) level than that of the non-VPI group (P<0.001, P=0.003, P=0.004). However, in multivariate analysis, only the lesion-pleura relationship patterns type Ia [odds ratio (OR) =20.689; 95% confidence interval (CI): 5.058-84.622; P<0.001], type Ib (OR =5.155; 95% CI: 1.178-22.552; P=0.03), type II (OR =7.154; 95% CI: 1.733-29.53; P=0.007) with type III as reference, solid lesion density (OR =9.954; 95% CI: 4.976-19.911; P<0.001) with part-solid density as reference were identified as the independent predictors for VPI. In predicting VPI, the combined model (AUC =0.885) significantly outperformed models based on lesion density (AUC =0.833) and lesion-pleura relationship patterns (AUC =0.655) (all P<0.001).

CONCLUSIONS

The CT predictors for VPI in patients with subpleural NSCLC (≤3 cm) were lesion density and lesion-pleura relationship patterns (pleural attachment and indentation), but not serum tumor biomarkers.