• Hao Dong, Lekang Yin, Cuncheng Lou, Junjie Yang, Xinbin Wang, and Yonggang Qiu.
• Department of Radiology, First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.
• Medicine (Baltimore). 2022 Jun 24; 101 (25): e29373.

AbstractThe purpose of the study is to investigate the correlation of computed tomography (CT) quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma.The study involved 141 lesions in 141 patients with early lung adenocarcinoma. According to the degree of tumor invasion, the lesions were assigned into (adenocarcinoma in situ + minimally invasive adenocarcinoma) group and invasive adenocarcinoma (IAC) group. Artificial intelligence-assisted diagnostic software was used to automatically outline the lesions and extract corresponding quantitative parameters on CT images. Statistical analysis was performed to explore the correlation of these parameters with tumor invasion and Ki-67 expression.The results of logistic regression analysis showed that the short diameter of the lesion and the average CT value were independent predictors of IAC. Receiver operating characteristic curve analysis identified the average CT value as an independent predictor of IAC with the best performance, with the area under the receiver operating characteristic curve of 0.893 (P < .001), and the threshold of -450 HU. Besides, the predicted probability of logistic regression analysis model was detected to have the area under the curve of 0.931 (P < .001). The results of Spearman correlation analysis showed that the expression level of Ki-67 had the highest correlation with the average CT value of the lesion (r = 0.403, P < .001).The short diameter of the lesion and the average CT value are independent predictors of IAC, and the average CT value is significantly positively correlated with the expression of tumor Ki-67.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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