This study identified 236 patients from two cohorts who underwent surgery for ground-glass nodules (GGNs). The novel marginal features described, when combined with a radiomics model, could help to differentiate invasive adenocarcinoma (IA) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) on preoperative CT scans.
Key points
- Our novel marginal features could improve the existing radiomics model to predict the degree of pathologic invasiveness in lung adenocarcinoma.
Article: Marginal radiomics features as imaging biomarkers for pathological invasion in lung adenocarcinoma
Authors: Hwan-ho Cho, Geewon Lee, Ho Yun Lee & Hyunjin Park
