JUNE Project: Does the Modeling of Nasal Airflows Improve the Pathophysiological Understanding and the Diagnosis of Functional Respiratory Disorders?

What this Trial Is About

Chronic Nasal Obstruction (CNO) affects 20 to 25% of people and has many causes such as septal deviation, polyps, chronic rhinosinusitis, and post-therapeutic cancer effects. It can disrupt sleep and lower quality of life, sometimes leading to depression. Current diagnosis relies on self-reported questionnaires, which can be influenced by many factors and lack objective measurement, causing uncertainties in diagnosis and treatment. Researchers are evaluating the use of Computational Fluid Dynamic Simulation (CDFS) to model air passage in the nasal cavities. This method aims to provide a functional analysis that complements anatomical studies by measuring airflow parameters associated with nasal obstruction. The study uses retrospective, pseudo-anonymized clinical and scan data from routine rhinosinusology consultations, including 100 patients without obstruction and 200 patients with anatomical obstruction. Participants' data will be analyzed to find correlations and physical airflow values related to their nasal condition. Researchers will assess flow parameters and their weighting coefficients at the time of inclusion. There is no patient follow-up in this study. The goal is to improve the understanding and diagnosis of nasal airflow disorders, potentially reducing unnecessary surgeries and healthcare costs. The study runs from July 2024 to July 2026, involving adults aged 18 to 69 years.

Diagnosis of Respiratory Disorders by the Numerical Modeling.