CT-based radiomics model to predict spread through air space in resectable lung cancer.

ABSTRACT:

Background

Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS.

Method

There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient

SUBMITTER: Gong J 

PROVIDER: S-EPMC10557899 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature