Artificial intelligence-measured nodule mass for determining the invasiveness of neoplastic ground glass nodules.

ABSTRACT:

Background

The nodule mass is an important indicator for evaluating the invasiveness of neoplastic ground-glass nodules (GGNs); however, the efficacy of nodule mass acquired by artificial intelligence (AI) has not been validated. This study thus aimed to determine the efficacy of nodule mass measured by AI in predicting the invasiveness of neoplastic GGNs.

Methods

From May 2019 to September 2023, a retrospective study was conducted on 755 consecutive patients comprising 788 pathologically confirmed neoplastic GGNs, among which 259 were adenocarcinoma in situ (AIS), 282 minimally invasive adenocarcinoma (MIA), and 247 invasive adenocarcinoma (IAC). Nodule mass was quantified using AI software, and other computed tomography (CT) features were concurrently evaluated. Clinical d

SUBMITTER: Xiong TW 

PROVIDER: S-EPMC11400670 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature