Impact of CT acquisition settings on the stability of radiomic features and the performance of pulmonary nodule classification models.

ABSTRACT:

Objectives

To evaluate the stability of radiomic features under different CT acquisition settings and investigate its impact on diagnostic model performance and generalizability.

Materials and methods

198 patients with 1227 pulmonary nodules underwent chest CT scans using varied settings (three slice thicknesses, two reconstruction matrices, six convolution kernels, two transmission methods). 1394 radiomic features were extracted per nodule. Feature stability was evaluated using the Intraclass Correlation Coefficient (ICC, stable: ICC ≥ 0.8, intermediate stable: 0.4 < ICC < 0.8, unstable: ICC ≤ 0.4). Four diagnostic models (Full-feature, Stable, Unstable, Intermediate stable) were developed using two datasets (lung cancer screening, n = 184; clinical scenarios, n = 1192). In

SUBMITTER: Zhou Q 

PROVIDER: S-EPMC12770142 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature