Background: Mechanical obstruction of odorant flow to the olfactory neuroepithelium may be a primary cause of olfactory loss in nasal-sinus disease patients. Surgical removal of nasal obstruction may facilitate the recovery of olfactory ability. Unfortunately, quantifying the functional impact of nasal obstruction and subsequent surgical outcomes using acoustic rhinometry, rhinomanometry, or CT scans is inadequate.
Methods: Using computational fluid dynamics (CFD) techniques, we can convert patient CT scans into anatomically accurate 3D numerical nasal models that can be used to predict nasal airflow and odorant delivery rates. These models also can be rapidly modified to reflect anatomic changes, e.g., surgical removal of polyps.
Results: CFD modeling of one patient's nose pre- and postsurgery showed significant improvement in postsurgical ortho- and retronasal airflow and odorant delivery rate to olfactory neuroepithelium (> 1000 times), which correlated well with olfactory recovery.
Conclusion: This study has introduced a novel technique (CFD) to calculate nasal airflow dynamics and its effects on olfaction, nasal obstruction, and sinus disease. In the future, such techniques may provide a quantitative evaluation of surgical outcome and an important preoperative guide to optimize nasal airflow and odorant delivery.