Radiomic prediction models for the level of Ki-67 and p53 in glioma.

ABSTRACT:

Objective

To identify glioma radiomic features associated with proliferation-related Ki-67 antigen and cellular tumour antigen p53 levels, common immunohistochemical markers for differentiating benign from malignant tumours, and to generate radiomic prediction models.

Methods

Patients with glioma, who were scanned before therapy using standard brain magnetic resonance imaging (MRI) protocols on T1 and T2 weighted imaging, were included. For each patient, regions-of-interest (ROI) were drawn based on tumour and peritumoral areas (5/10/15/20 mm), and features were identified using feature calculations, and used to create and assess logistic regression models for Ki-67 and p53 levels.

Results

A total of 92 patients were included. The best area under the curve (AUC) for t

SUBMITTER: Sun X 

PROVIDER: S-EPMC7241212 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature