Body composition radiomic features as a predictor of survival in patients with non-small cellular lung carcinoma: A multicenter retrospective study

Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule

“…However, the traditional imaging modalities for judging benign and malignant nodules are greatly influenced by the subjective impact of the diagnostic physician, and when the nodules are too small or the imaging characteristics are not obvious, the diagnostic accuracy will significantly decrease. Several studies have shown that compared to traditional CT signs, radiomics has a higher accuracy in differentiating benign and malignant GGNs and predicting the pathological classification of GGN-type lung adenocarcinoma ( 7 , 9 ). In this study, a computer-based model was established to analyze GGNs to predict the invasion and instability of GGN-type lung adenocarcinoma.…”

“…In recent years, radiomics has been widely used in various clinical stages. Many studies have confirmed that radiomics has unique advantages for cancer in the differentiation of benign and malignant tumors, pathological classification, evaluation of curative effects after adjuvant treatment and the risk of recurrence in cancer ( 7 - 10 ). In 2015, the World Health Organization (WHO) classification published by the International Agency for Cancer Research classified AAH and AIS as noninvasive lesions and MIA and IAC as invasive lesions ( 11 ).…”