Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes.

ABSTRACT:

Background

Radiomics-based non-invasive biomarkers are promising to facilitate the translation of therapeutically related molecular subtypes for treatment allocation of patients with head and neck squamous cell carcinoma (HNSCC).

Methods

We included 113 HNSCC patients from The Cancer Genome Atlas (TCGA-HNSCC) project. Molecular phenotypes analyzed were RNA-defined HPV status, five DNA methylation subtypes, four gene expression subtypes and five somatic gene mutations. A total of 540 quantitative image features were extracted from pre-treatment CT scans. Features were selected and used in a regularized logistic regression model to build binary classifiers for each molecular subtype. Models were evaluated using the average area under the Receiver Operator Characteristic curve

SUBMITTER: Huang C 

PROVIDER: S-EPMC6642281 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature