Longitudinal and Multimodal Radiomics Models for Head and Neck Cancer Outcome Prediction.

ABSTRACT: Radiomics analysis provides a promising avenue towards the enabling of personalized radiotherapy. Most frequently, prognostic radiomics models are based on features extracted from medical images that are acquired before treatment. Here, we investigate whether combining data from multiple timepoints during treatment and from multiple imaging modalities can improve the predictive ability of radiomics models. We extracted radiomics features from computed tomography (CT) images acquired before treatment as well as two and three weeks after the start of radiochemotherapy for 55 patients with locally advanced head and neck squamous cell carcinoma (HNSCC). Additionally, we obtained features from FDG-PET images taken before treatment and three weeks after the start of therapy. Cox proportional haz

SUBMITTER: Starke S 

PROVIDER: S-EPMC9913206 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature