Computational fluid dynamics for assessing nasal ventilation and virtual surgery in pediatric cleft patients

Background Cleft lip and/or palate causes complex nasal deformities that result in persistent obstruction. This study aimed to quantitatively assess nasal airflow and simulate virtual surgical interventions using CT-based Computational Fluid Dynamics (CFD) in pediatric cleft patients. Methods CT scans from two pediatric cleft patients (10 months and 5 years old) and age-matched controls were used to generate 3-dimensional nasal models. CFD simulations quantified mass flow rate, pressure drop, and nasal resistance during peak inspiration and expiration. Time-varying pressure–flow data allowed generation of virtual rhinomanometry curves. Virtual surgeries included isolated rhinoplasty, isolated septoplasty, and combined rhinoseptoplasty. Results Baseline cleft models exhibited markedly elevated nasal resistance and asymmetric airflow. The functional effects of virtual anatomical correction differed between patients. Septal correction accounted for most of the resistance reduction in the 10-month-old model, whereas combined correction of the septum and nasal framework produced the closest approximation to control airflow in the 5-year-old model. Conclusions CFD provides a quantitative, patient-specific characterization of the airflow mechanics underlying nasal obstruction in pediatric cleft patients. The magnitude of functional improvement produced by virtual anatomical correction varied markedly between the two patients, underscoring the patient-specific nature of nasal airflow mechanics across early childhood. Virtual surgery, coupled with CFD, offers a realistic framework for exploring the mechanical determinants of nasal obstruction in this population, with future automation potentially facilitating its integration into individualized, physiology-based assessment.