Constructing an imagomics model for high resolution CT to predict the benign and malignant characteristics of solitary ground glass nodules in the lung

Objective To explore the value of radiomics model based on high-resolution computed tomography (HRCT) in predicting the benign and malignant pulmonary solitary ground glass nodule (GGN) before operation.

Methods The preoperative HRCT images of 152 patients with pulmonary solitary GGN from January 2019 to October 2022 in Shanghai Fengxian District Central Hospital were analyzed retrospectively. Patients were randomly divided into training group (n＝106) and validation group (n＝46) according to the proportion of 7∶3. According to the pathological results, patients in training group were divided into malignant group (n＝56) and benign group (n＝50), and clinical characteristics were compared between the two groups. The routine CT features of pulmonary solitary GGN in the training group were evaluated. PyRodiomics software was used to extract 107 radiomics features in the whole volume of interest (VOI) of each lesion and Lasso regression was used to screen the radiomics features. Logistic regression was used to establish three regression models (clinical model, radiomics model and combined model). The efficacy of the three prediction models was evaluated by the receiver operating characteristic (ROC) curve and area under the curve (AUC).

Results A total of 13 radiomics features were screened by Lasso regression. Three clinical characteristics were significantly different between the malignant group and benign group. Radiomics features NCCT_original_firstorder_10Percentile, NCCT_original_glrlm_RunEntropy, and NCCT_original_shape_Sphericity, clinical features CT value, clinical feature score and radiomics score could be predictive factors for malignant pulmonary solitary GGN. AUC of the radiomicss model, clinical model, and combined model were 0.971 (95%CI 0.884-0.996), 0.866 (95%CI 0.786-0.925) and 0.977 (95%CI 0.827-0.996) in the train group and 0.883 (95%CI 0.763-0.961), 0.692 (95%CI 0.538-0.819) and 0.934 (95%CI 0.820-0.986) in validation group, respectively.

Conclusions The radiomics model based on HRCT can effectively predict the benign and malignant of pulmonary solitary GGN.