Unknown

Dataset Information

Nomogram integrating clinical-radiological and radiomics features for differentiating invasive from non-invasive pulmonary adenocarcinomas presenting as ground-glass nodules.


ABSTRACT:

Objective

To construct a nomogram incorporating clinical-radiological and radiomics features from computed tomography (CT) for distinguishing invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) in ground-glass nodules (GGNs).

Methods

This retrospective study included 473 GGN patients with postoperative pathological confirmation of AIS, MIA, or IAC. The training set comprised 257 patients from Yantaishan Hospital, while the test set, used for external validation, included 216 patients from the Affiliated Hospital of Binzhou Medical College. Radiomics features were selected, and a radiomics model was constructed using least absolute shrinkage and selection operator (LASSO) and minimum redundancy maximum relevance (mRMR) m

SUBMITTER: Dong N 

PROVIDER: S-EPMC11897637 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature