Computational Fluid Dynamics and Virtual Septoplasty in Nasal Airway Obstruction: A Narrative Review.

Abstract

Nasal airway obstruction (NAO) is a common symptom with a substantial impact on quality of life. Septoplasty is frequently performed, yet outcomes remain variable and may decline over time. Computational fluid dynamics (CFD) enables patient-specific simulation of nasal airflow. Virtual septoplasty builds on this by allowing preoperative anatomical models to be digitally modified, with CFD used to estimate the functional impact of proposed surgical changes. This narrative review synthesises the contemporary CFD evidence base relevant to septoplasty and, to our knowledge, provides the first synthesis of the virtual septoplasty literature. A focused narrative review was undertaken. Database searches up to November 2025 were screened for relevance. Structured data extraction was performed for eligible studies, followed by full-text review, independent assessment by two reviewers, and narrative synthesis. CFD provides a detailed simulation of individualised nasal airflow but must be interpreted in the context of known limitations and modelling assumptions. Across studies, CFD metrics show stronger correlation with validated symptom scores than resistance measures, although reported correlations vary and are influenced by nasal cycle control and methodological heterogeneity. Virtual septoplasty studies demonstrate that digitally edited models can reproduce the direction and approximate magnitude of postoperative changes in airflow-related metrics, but evidence remains limited by small cohorts and limited comparison to validated symptom scores. CFD and virtual septoplasty represent promising technologies for individualised assessment and surgical planning. Wider adoption will require standardised modelling workflows, validated symptom-based endpoints, and prospective evidence demonstrating improved outcomes over current clinical practice.