Efficacy of Maxillomandibular Advancement Examined with Drug-Induced Sleep Endoscopy and Computational Fluid Dynamics Airflow Modeling

Abstract

Objectives

To use drug-induced sedation endoscopy (DISE) and computational fluid dynamics (CFD) modeling to study dynamic airway and airflow changes after maxillomandibular advancement (MMA), and how the changes correlate with surgical success based on polysomnography parameters.

Study Design

Retrospective cohort study.

Setting

University medical center.

Methods

DISE was rated with the VOTE (velum, oropharynx, tongue, epiglottis) classification, and CFD was used to model airflow velocity and negative pressure exerted on pharyngeal wall. Changes in VOTE score by site and CFD measurements were correlated with perioperative polysomnography outcomes of apnea-hypopnea index (AHI), apnea index (AI), oxygenation desaturation index (ODI), and lowest oxygen saturation.

Results

After MMA, 20 subjects (17 males, 3 females) with a mean age of 44 ± 12 years and body mass index of 27.4 ± 4.6 kg/m² showed mean decreases in AHI (53.6 ± 26.6 to 9.5 ± 7.4 events/h) and ODI (38.7 ± 30.3 to 8.1 ± 9.2 events/h; P < .001). Improvement in lateral pharyngeal wall collapse during DISE based on VOTE score correlated with the most decrease in AHI (60.0 ± 25.6 to 7.5 ± 3.4 events/h) and ODI (46.7 ± 29.8 to 5.3 ± 2 events/h; P = .002). CFD modeling showed significant positive Pearson correlations between reduction of retropalatal airflow velocity and AHI (r = 0.617, P = .04) and ODI (r = 0.773, P = .005).

Conclusion

AHI and ODI improvement after MMA is best correlated with (1) decreased retropalatal airflow velocity modeled by CFD and (2) increased lateral pharyngeal wall stability based on VOTE scoring from DISE.

Keywords

maxillomandibular advancement obstructive sleep apnea drug-induced sleep endoscopy computational fluid dynamics lateral pharyngeal wall collapse

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