Functional imaging improves patient selection for mandibular advancement device treatment outcome in sleep-disordered breathing: a prospective study

Abstract

Study objectives: Mandibular advancement devices (MADs) are a noninvasive treatment option for patients with obstructive sleep apnea (OSA) and act by increasing the upper airway volume. However, the exact therapeutic mechanism of action remains unclear. The aim of this study was to assess MAD mechanisms using functional imaging that combines imaging techniques and computational fluid dynamics and assess associations with treatment outcome.

Methods: One hundred patients with OSA were prospectively included and treated with a custom-made MAD at a fixed 75% protrusion. A low-dose computed tomography scan was made with and without MADs for computational fluid dynamics analysis. Patients underwent a baseline and 3-month follow-up polysomnography to evaluate treatment efficacy. A reduction in apnea-hypopnea index ≥ 50% defined treatment response.

Results: Overall, 71 patients completed both 3-month follow-up polysomnography and low-dose computed tomography scan with computational fluid dynamics analysis. MAD treatment significantly reduced the apnea-hypopnea index (16.5 [10.4-23.6] events/h to 9.1 [3.9-16.4] events/h; P < .001, median [quartile 1-quartile 3]) and significantly increased the total upper airway volume (8.6 [5.4-12.8] cm³ vs 10.7 [6.4-15.4] cm³; P = .003), especially the velopharyngeal volume (2.1 [0.5-4.1] cm³ vs 3.3 [1.8-6.0] cm³; P < .001). However, subanalyses in responders and nonresponders only showed a significant increase in the total upper airway volume in responders, not in nonresponders.

Conclusions: MAD acts by increasing the total upper airway volume, predominantly due to an increase in the velopharyngeal volume. Responders showed a significant increase in the total upper airway volume with MAD treatment, while there was no significant increase in nonresponders. Findings add evidence to implement functional imaging using computational fluid dynamics in routine MAD outcome prediction.

Clinical trial registration: Registry: ClinicalTrials.gov; Name: Predicting Therapeutic Outcome of Mandibular Advancement Device Treatment in Obstructive Sleep Apnea; URL: https://clinicaltrials.gov/ct2/show/NCT01532050; Identifier: NCT01532050.

Citation: Van Gaver H, Op de Beeck S, Dieltjens M, et al. Functional imaging improves patient selection for mandibular advancement device treatment outcome in sleep-disordered breathing: a prospective study. J Clin Sleep Med. 2022;18(3):739-750.

Keywords: CFD; MAD; OSA; obstructive sleep apnea; oral appliances.

Figure 1. Study flowchart and patient flow.

(A) Flowchart. (B) Patient flow. AHI = apnea-hypopnea index, CFD = computational fluid dynamics, CT = computed tomography, MAD = mandibular advancement device, OSA = obstructive sleep apnea, PSG = polysomnography.

Figure 2. Low-dose CT scan images.

Subsegments of the UA on a midsagittal CT scan (A), UA changes due to MAD treatment on a midsagittal CT scan of a responder (B), velopharyngeal changes due to MAD treatment on an axial CT scan of a responder (C), and hypopharyngeal changes due to MAD treatment on an axial CT scan of a responder (D). A = anterior, CT = computed tomography, H = head, F = feet, MAD = mandibular advancement device, P = posterior, UA = upper airway.

Figure 3. Change in UA volume.

Total UA volume without and with MAD in responders (A), velopharynx volume without and with MAD in responders (B), total UA volume without and with MAD in nonresponders (C), velopharynx volume without and with MAD in nonresponders (D), velopharynx volume without and with MAD in deteriorated patients (E), and velopharynx volume without and with MAD in nondeteriorated patients (F). The outliers are plotted as individuals points. MAD = mandibular advancement device, UA = upper airway.