Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model.

ABSTRACT:

Purpose

To develop and validate an integrated model for discriminating tumor recurrence from radiation necrosis in glioma patients.

Methods

Data from 160 pathologically confirmed glioma patients were analyzed. The diagnostic model was developed in a primary cohort (n = 112). Textural features were extracted from postoperative ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET), ¹¹C-methionine (¹¹C-MET) PET, and magnetic resonance images. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a model for predicting tumor recurrence. The radiomics signature, quantitative PET par

SUBMITTER: Wang K 

PROVIDER: S-EPMC7188738 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature