Machine-learning radiomics to predict bone marrow metastasis of neuroblastoma using magnetic resonance imaging.

ABSTRACT:

Background

Neuroblastoma is one common pediatric malignancy notorious for high temporal and spatial heterogeneities. More than half of its patients develop distant metastases involving vascularized organs, especially the bone marrow. It is thus necessary to have an economical, noninvasive method without much radiation for follow-ups. Radiomics has been used in many cancers to assist accurate diagnosis but not yet in bone marrow metastasis in neuroblastoma.

Methods

A total of 182 patients with neuroblastoma were retrospectively collected and randomly divided into the training and validation sets. Five-hundred and seventy-two radiomics features were extracted from magnetic resonance imaging, among which 41 significant ones were selected via T-test for model development.

SUBMITTER: Lv L 

PROVIDER: S-EPMC10686185 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature