Metastasis risk prediction model in osteosarcoma using metabolic imaging phenotypes: A multivariable radiomics model.

ABSTRACT:

Background

Osteosarcoma (OS) is the most common primary bone tumor affecting humans and it has extreme heterogeneity. Despite modern therapy, it recurs in approximately 30-40% of patients initially diagnosed with no metastatic disease, with the long-term survival rates of patients with recurrent OS being generally 20%. Thus, early prediction of metastases in OS management plans is crucial for better-adapted treatments and survival rates. In this study, a radiomics model for metastasis risk prediction in OS was developed and evaluated using metabolic imaging phenotypes.

Methods and findings

The subjects were eighty-three patients with OS, and all were treated with surgery and chemotherapy for local control. All patients underwent a pretreatment 18F-FDG-PET scan. Forty-five fe

SUBMITTER: Sheen H 

PROVIDER: S-EPMC6876771 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature