To investigate the diagnostic value of CT texture features in the invasiveness of 5-10 mm ground glass pulmonary nodules.

A total of 67 patients with 5-10 mm diameter pulmonary nodules confirmed by operation and pathology were analyzed retrospectively from January 2010 to November 2019 in Northern Jiangsu People's Hospital Affiliated to Yangzhou University. All the patients were divided into two groups according to the pathological results (36 cases of microinvasive adenocarcinoma and 31 cases of invasive adenocarcinoma). The image morphology of pulmonary nodules (solid composition, burr, boundary) was evaluated and counted. Four kinds of texture eigenvalues of pulmonary nodules, including gray histogram, absolute gradient, run-length matrix and co-occurrence matrix, were extracted automatically by using MaZda 4.6 software to draw the region of interest at the maximum level of lesions in thin-slice CT images. The differences of morphological and texture features between the two groups of pulmonary nodules were compared. WeKa 3.8 software was used to rank the importance of features from high to low and then incorporated into the training multivariate logistics regression model. The area under the curve (AUC) values corresponding to different number of features were obtained and the best AUC values were selected to construct the receiver operating characteristic (ROC) curve to evaluate the diagnostic effectiveness of the model in distinguishing the invasiveness of pulmonary nodules. 10-fold cross-validation was used to prevent over-fitting.

There were statistically significant differences in CT imaging characteristics such as pulmonary tubercle boundary, solid component and burr sign between the two groups. The diagnostic efficiency of the top 12 texture features was the best after the establishment of multivariate logistics regression model, the AUC was 0.845, and the specificity and sensitivity were 80.6% and 74.2% respectively. The model was cross-verified by 10% discount, and the accuracy of the model was 77.6%.

The texture analysis based on chest CT scan can effectively identify the invasiveness of 5-10 mm ground glass lung nodules.