Radiomics in differential diagnosis of Wilms tumor and neuroblastoma with adrenal location in children.

ABSTRACT:

Objectives

Machine learning methods can be applied successfully to various medical imaging tasks. Our aim with this study was to build a robust classifier using radiomics and clinical data for preoperative diagnosis of Wilms tumor (WT) or neuroblastoma (NB) in pediatric abdominal CT.

Material and methods

This is a single-center retrospective study approved by the Institutional Ethical Board. CT scans of consecutive patients diagnosed with WT or NB admitted to our hospital from January 2005 to December 2021 were evaluated. Three distinct datasets based on clinical centers and CT machines were curated. Robust, non-redundant, high variance, and relevant radiomics features were selected using data science methods. Clinically relevant variables were integrated into the final mode

SUBMITTER: Koska IO 

PROVIDER: S-EPMC11255001 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature