Incremental prognostic value of solid component volume ratio and entropy for pathological stage IA invasive lung adenocarcinoma after surgery.

ABSTRACT:

Background

The risk factors for postoperative recurrence in pathological stage IA invasive lung adenocarcinoma (LUAD) remain unclear. This study aimed to evaluate the incremental prognostic value of deep learning (DL)-based quantitative parameters for pathological stage IA invasive LUAD after surgery.

Methods

The maximum total size on axial images (MTSA) and the maximum solid component size on axial images (MSSA) of tumors were manually measured, and consolidation tumor ratio was calculated as MSSA/MTSA. Maximal total size on multiplanar reconstructed images, total volume, solid component volume, and solid component volume ratio (SV%) were evaluated by DL software, with different densities as thresholds to separate solid component. In addition, the radiomics parameters inclu

SUBMITTER: Liu Z 

PROVIDER: S-EPMC12605698 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature