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ID06387004

Using Ultrasound to Predict Swallowing Problems During Radiotherapy for Head and Neck Cancer

Led by Hopital Forcilles · Updated on 2025-01-22

112

Participants Needed

1

Research Sites

N/A

Total Duration

AI-Summary

What this Trial Is About

Radiotherapy for head and neck cancers increases the risk of swallowing disorders, which can negatively affect nutrition, quality of life, and overall health, leading to more hospitalizations and higher mortality. This research aims to evaluate an ultrasound-based predictive model to detect the risk of swallowing disorders during radiotherapy. The study will assess the accuracy and reliability of ultrasound markers compared to current methods, which are often invasive, irradiating, and hard to access. The study will involve 124 outpatients starting radiotherapy for head and neck cancer at Forcilless Hospital over eighteen months. Participants will undergo three ultrasound examinations before treatment and after seven and fourteen days, performed by blinded ultrasonographers. Weekly clinical swallowing assessments will be done by speech-language therapists, with videofluoroscopy used when swallowing disorders are suspected. The study will analyze ultrasound measurements of structures involved in swallowing, such as the tongue and suprahyoid muscles, to develop and validate a predictive model. Participants will be monitored throughout their radiotherapy treatment, with data collected on swallowing function and nutritional status. Assessments include clinical evaluations, ultrasound exams, and videofluoroscopy when needed. Ultrasound measurement reliability will be tested with inter- and intra-operator evaluations. The main outcome is the ability of ultrasound markers to predict swallowing disorders during treatment. Safety and data accuracy will be overseen through monthly monitoring, with participation lasting the duration of radiotherapy plus minimal additional time for assessments.

CONDITIONS

Brief Title

Radiation-Related Dysphagia Development Prediction Using a Two-Step Ultrasonographic Model (R-2D-2)

Research Team

L

LE NEINDRE Aymeric, PhD

D

DIAZ LOPEZ Carlos, PhD st

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