Dysphagia in Head and Neck Radiotherapy: The Influence of Pharyngeal Constrictor Anatomy and Dosimetry.

The goal of this study was to identify which anatomical and dosimetric changes correlated with late patient-reported dysphagia throughout the course of head and neck chemo-radiotherapy treatment. The patient cohort (n = 64) considered oropharyngeal and nasopharyngeal patients treated with curative intent, exhibiting no baseline dysphagia with a follow-up time greater than one year. Patients completed the MD Anderson Dysphagia Inventory during a follow-up visit.

Developing and validating multi-omics prediction models for late patient-reported dysphagia in head and neck radiotherapy.

. To investigate models developed using radiomic and dosiomic (multi-omics) features from planning and treatment imaging for late patient-reported dysphagia in head and neck radiotherapy..

Pharyngeal Constrictor Dose-Volume Histogram Metrics and Patient-Reported Dysphagia in Head and Neck Radiotherapy.

Aims: Head and neck radiotherapy long-term survival continues to improve and the management of long-term side-effects is moving to the forefront of patient care. Dysphagia is associated with dose to the pharyngeal constrictors and can be measured using patient-reported outcomes to evaluate its effect on quality of life. The aim of the present study was to relate pharyngeal constrictor dose-volume parameters with patient-reported outcomes to identify prognostic dose constraints.

Can machine learning models improve early detection of brain metastases using diffusion weighted imaging-based radiomics?

Background: Metastatic complications are a major cause of cancer-related morbidity, with up to 40% of cancer patients experiencing at least one brain metastasis. Earlier detection may significantly improve patient outcomes and overall survival. We investigated machine learning (ML) models for early detection of brain metastases based on diffusion weighted imaging (DWI) radiomics.