External validation of radiomics-based predictive models in low-dose CT screening for early lung cancer diagnosis.

ABSTRACT:

Purpose

Low-dose CT screening allows early lung cancer detection, but is affected by frequent false positive results, inter/intra observer variation and uncertain diagnoses of lung nodules. Radiomics-based models have recently been introduced to overcome these issues, but limitations in demonstrating their generalizability on independent datasets are slowing their introduction to clinic. The aim of this study is to evaluate two radiomics-based models to classify malignant pulmonary nodules in low-dose CT screening, and to externally validate them on an independent cohort. The effect of a radiomics features harmonization technique is also investigated to evaluate its impact on the classification of lung nodules from a multicenter data.

Methods

Pulmonary nodules from two indep

SUBMITTER: Garau N 

PROVIDER: S-EPMC7708421 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature