The value of CT features in predicting visceral pleural invasion in clinical stage ⅠA peripheral lung adenocarcinoma under the pleura / 中华放射学杂志

ABSTRACT

Objective:To investigate the value of CT features in predicting visceral pleural invasion (VPI) in clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.Methods:The CT signs of 274 patients with clinical stage ⅠA peripheral lung adenocarcinoma under the pleura diagnosed in Changzheng Hospital of Naval Medical University from January 2015 to November 2021 were retrospectively analyzed. According to the ratio of 6∶4, 164 patients collected from January 2015 to August 2019 were used as the training group, and 110 patients collected from August 2019 to November 2021 were used as the validation group. The maximum diameter of the tumor (T), the maximum diameter of the consolidation part (C), and the minimum distance between the lesion and the pleura (DLP) were quantitatively measured, and the proportion of the consolidation part was calculated (C/T ratio, CTR). The CT signs of the tumor were analyzed, such as the relationship between the tumor and the pleura classification, the presence of a bridge tag sign, the location of the lesion, density type, shape, margin, boundary and so on. Variables with significant difference in the univariate analysis were entered into multivariate logistic regression analysis to explore predictors for VPI, and a binary logistic regression model was established. The predictive performance of the model was analyzed by receiver operating characteristic curve in the training and validation group.Results:There were 121 cases with VPI and 153 cases without VPI among the 274 patients with lung adenocarcinoma. There were 79 cases with VPI and 85 cases without VPI in the training group. Univariate analysis found that the maximum diameter of the consolidation part, CTR, density type, spiculation sign, vascular cluster sign, relationship of tumor and pleura and bridge tag sign between patients with VPI and those without VPI were significantly different in the training group( P<0.05). Multivariate logistic regression analysis found the relationship between tumor and pleura [taking type Ⅰ as reference, type Ⅱ (OR=6.662, 95%CI 2.364-18.571, P<0.001), type Ⅲ (OR=34.488, 95%CI 8.923-133.294, P<0.001)] and vascular cluster sign (OR=4.257, 95%CI 1.334-13.581, P=0.014) were independent risk factors for VPI in the training group. The sensitivity, specifcity, and area under curve (AUC) for the logistic model in the training group were 62.03%, 89.41% and 0.826, respectively, using the optimal cutoff value of 0.504. The validation group obtained an sensitivity, specifcity, and AUC of 92.86%, 47.06%, and 0.713, respectively, using the optimal cutoff value of 0.449. Conclusion:The relationship between the tumor and the pleura and the vascular cluster sign in the CT features can help to predict visceral pleural invasion in the clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.