Clinical-radiomics models based on plain X-rays for prediction of lung metastasis in patients with osteosarcoma.

ABSTRACT:

Objectives

Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents. Lung metastasis (LM) occurs in more than half of patients at different stages of the disease course, which is one of the important factors affecting the long-term survival of OS. To develop and validate machine learning radiomics model based on radiographic and clinical features that could predict LM in OS within 3 years.

Methods

486 patients (LM = 200, non-LM = 286) with histologically proven OS were retrospectively analyzed and divided into a training set (n = 389) and a validation set (n = 97). Radiographic features and risk factors (sex, age, tumor location, etc.) associated with LM of patients were evaluated. We built eight clinical-radiomics models (k-nearest neighbor [KNN], lo

SUBMITTER: Yin P 

PROVIDER: S-EPMC10037898 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature