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Computational airflow analysis before and after maxillomandibular advancement surgery
Journal of the World Federation of Orthodontists 5 (2016) 2e8
Contents lists available at ScienceDirect
Journal of the World Federation of Orthodontists journal homepage: www.jwfo.org
Research
Computational airflow analysis before and after maxillomandibular advancement surgery Ki Beom Kim a, *, Patrick G. McShane a, Mark McQuilling b, Donald R. Oliver a, Michael Schauseil c a
Department of Orthodontics, Center for Advanced Dental Education, Saint Louis University, St. Louis, Missouri Parks College of Engineering, Aviation, and Technology, Saint Louis University, St. Louis, Missouri c Department of Orthodontics, University of Marburg, Marburg, Germany b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 26 July 2015 Accepted 7 December 2015 Available online 26 January 2016
Background: The purpose of this study was to analyze pharyngeal airflow using computational fluid dynamics (CFD) in obstructive sleep apnea (OSA) patients before and after maxillomandibular advancement (MMA). Methods: Digitized pharyngeal airway models of 19 obstructive sleep apnea patients were generated from cone beam computed tomography scans presurgery and an average of 18.3 17.3 days postsurgery. CFD was used to simulate and characterize pharyngeal airflow, which was assumed to be turbulent at an inspiration rate of 340 mL/s. Standard steady-state numerical formulation were used for airflow simulations. Results: Mean pressure drop during inspiration was significantly reduced from 34.82 65.65 Pa presurgery to 3.06 3.96 Pa postsurgery. Mean maximum airflow velocity along the airway was also significantly reduced from 11.14 8.49 m/s presurgery to 4.09 3.07 m/s postsurgery. There was a significant increase in mean airway volume of 66.8% postsurgery. There was a 75% mean reduction in airway resistance postsurgery. There was a decrease in the pressure gradient and total pressure drop postsurgery for all 19 patients. There was a statistically significant moderate, negative correlation between the change in airway resistance and the change in airway volume postsurgery. No correlation was found between skeletal advancement and airway volume or airway resistance. Conclusions: A decrease in relative pressure implies less effort required for maintaining constant pharyngeal airflow according to CFD analyses on airways of OSA patients after MMA surgery. Ó 2016 World Federation of Orthodontists.
Keywords: Airway Computational fluid dynamics Maxillomandibular advancement Obstructive sleep apnea
1. Introduction Obstructive sleep apnea (OSA) is a sleep-related breathing disorder characterized by the partial or complete collapse of the upper airway during both rapid eye motion (REM) and non-REM sleep [1,2]. Epidemiologic estimates of OSA prevalence are approximately 9%e24% for middle-aged adults with up to 80% of patients remaining undiagnosed [3]. Sleep-related breathing disorders, when left untreated, can increase the risk for cardiovascular diseases, hypertension, stroke, angina, headaches, excessive daytime sleepiness,
All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest, and none were reported. * Corresponding author: Department of Orthodontics, Center for Advanced Dental Education, Saint Louis University, 3320 Rutger Street, St. Louis, MO 63104. E-mail address: [email protected] (K.B. Kim). 2212-4438/$ e see front matter Ó 2016 World Federation of Orthodontists. http://dx.doi.org/10.1016/j.ejwf.2015.12.002
poor work performance, occupational accidents, cognitive dysfunction, depression, and exacerbation of type 2 diabetes [4e11]. Various therapies exist in the treatment of OSA. Continuous positive airway pressure is a highly effective therapeutic modality for the treatment of OSA and remains the gold standard [5]. Multilevel surgical interventions play an important role as secondline treatment for anatomical obstruction [12]. A highly effective stage 2 surgical option for the treatment of severe OSA is maxillomandibular advancement (MMA) surgery with success rates of 65e100% [13e17]. The study of pharyngeal airflow after MMA surgery has been targeted as an area of interest using computational fluid dynamics (CFD). CFD provides a method for the indirect study of pharyngeal airflow. Sung et al. [18] found maximum airflow velocity and lowest pressure at the narrowest part of the velopharynx. Using CFD, Yu et al. [19] showed the correlation between CFD simulation and apnea-hypopnea index (AHI). Ito et al. [20] constructed hybrid
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
models composed of posttreatment nasal cavities superimposed on pretreatment nasal cavities and posttreatment nasal and pharyngeal airway models to simulate airflow and found a decrease in pressure effort to breathe evidenced by a decrease in the negative pressure post MMA surgery. Last, numerous investigations found a decrease in airway resistance after MMA surgery [20e23]. The purposes of this study are to analyze and compare pharyngeal airflow characteristics in patients with OSA before and after MMA surgery using CFD and to validate previous research findings. 2. Materials and methods 2.1. Patient Selection Pretreatment and posttreatment cone beam computed tomography (CBCT) scans of 19 patients (9 male and 10 female) who had undergone both orthodontic treatment and MMA surgery were used in this retrospective study (Table 1). Inclusion criteria include (1) having a history of OSA and (2) being treated with both orthodontics and MMA surgery. Exclusion criteria included (1) having a craniofacial syndrome and (2) having surgical maxillary expansion. The surgical procedures completed were carried out by two oral surgeons using the same surgical techniques. A nonsegmental Le Fort I osteotomy was used to advance the maxilla, while bilateral sagittal split ramus osteotomies were used to advance the mandible. The presurgical and postsurgical AHI values were unavailable to the researchers for this study. 2.2. CBCTs
was subtracted. A perpendicular line was drawn through the corrected horizontal plane from nasion and then the distance to A-point and B-point was measured and compared before and after surgery (Fig. 1). 2.4. Isolating the pharyngeal airway The CBCT scans were imported into Mimics software as DICOM (Digital Imaging and Communications in Medicine) files to generate a volumetric image of the scanned region. Once the volume was generated, the pharyngeal airway of interest was isolated. The superior border was defined by creating a plane through left and right porus acousticus externus and nasion; the anterior border was defined by creating a perpendicular plane to the superior border going through the most anterior and middle point of the sella wall; and the inferior border was defined by creating a horizontal plane parallel to the superior plane through the most inferior and anterior point of C3. The anterior and posterior wall of the volume was defined by the natural border of the pharynx. The uvula was removed in all cases to avoid artifacts (Fig. 2). 2.5. Computer modeling and mesh generation Pharyngeal airway models were imported into Geomagic to check for model integrity. Models were transferred into SC/Tetra preprocessing software (version 9.0, Software Cradle Corporation, Osaka, Japan) for model and mesh generation. Inlet, outlet, and wall boundaries were defined manually (Fig. 3A). Appropriate grid size, number of tetrahedral elements, and octree size of 0.5 mm were chosen for the mesh model using the
CBCT scans were taken before and after MMA surgery using the same i-CAT machine (Imaging Sciences International, Hatfield, PA): T0 (presurgery) and T1 (2e4 weeks postsurgery; Table 1). Imaging field of view was 23 cm 19 cm with a voxel size of 0.4 mm. Presurgical scans were taken with an interocclusal wax bite in centric relation. Postsurgical scans were taken with the condyles in centric relation and no wax bite. Presurgery and postsurgery scans were taken with the patient standing upright and head position parallel to the Frankfort horizontal plane. The patients were instructed not to swallow and not to move the tongue during the scanning. Mimics 3D software (version 15.0, Materialise, Levuen, Belgium), Geomagic (version 2012, 3D Systems, Rock Hill, SC), and Dolphin 3D (version 11.0, Chatsworth, CA) were used to view, analyze, and manipulate the CBCT scans. 2.3. Calculation of surgical movement The calculation of the anteroposterior surgical movement was measured for the maxilla and mandible by converting the CBCT scan from a three-dimensional volume to a two-dimensional lateral cephalogram image. The skeletal landmarks used to measure surgical movement were sella, nasion, A-point, and B-point. A reference plane was drawn through sella and nasion and then 7 (SN-7 )
Table 1 Patient characteristics: age and time between CBCT scans Number of subjects
Age (y) Mean
SD
Mean
SD
Male Female
40.8 36.3
12.9 15.9
17.6 19.1
14.4 20.3
9 10
3
Time between scans (d)
Fig. 1. Lateral cephalograms demonstrating measurement of surgical movement.
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2.6. Solving methods Mesh models were imported into SC/Tetra Solver (version 9.0, Software Cradle Corporation) for airflow simulation. A turbulent model flow, the RNG k-ε model, was used to simulate turbulent airflow within the pharyngeal airway, similar to the turbulent model equations used in the Huynh et al. [22] and Sung et al. [18] studies. The RNG k-ε model was chosen because of its minimal computing power required for flow simulation. Using a volumetric flow rate of 340 mL/s, corresponding inlet boundary velocities were calculated for each model using the formula Q ¼ AV. Inlet area, A, was determined from the preprocessor function in SC/Tetra for each model. The outlet boundary condition was set at a static pressure of 0 Pa. The walls of the model, which were assumed to be rigid and noncompliant, were set to no-slip conditions. Air flow simulations were completed using the SC/Tetra Solver function on a PC with an IntelÒ CoreÔ i7 CPU Q740 (1.73 GHz) with 8 GB of RAM. After solver functions were completed, SC/Tetra postprocessor software (version 9.0) was used to analyze and visualize the fluid flow data. 2.7. Magnitude of airflow velocity measurements
Fig. 2. Airway volume model segmentation boundaries.
same protocol used by Huyhn et al. [22] (Fig. 3B). The final mesh models of the airways had an average of 314,193 tetrahedral elements.
The maximum magnitude of airflow velocity was measured for all 19 patients before and after surgery. All measurements were recorded in the mid-sagittal plane of the airway. Velocity measurements were made using the SC/Tetra postprocessor. 2.8. Pressure calculations and airway resistance The postprocessor function of SC/Tetra was used to calculate the change in pressure, Dp, from the inlet to outlet boundary over the
Fig. 3. (A) Three-dimensional airway model and (B) mesh model file demonstrating tetrahedral elements.
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
5
Table 2 Measurements of airway volume (mm3) and pressure change in the mid-sagittal plane (Pa) Measure
T0
Airway Volume Change in pressure *
T1
% Change
Paired t
Mean
SD
Mean
SD
Mean
SD
T0 to T1
1.3505 34.82
5.0006 65.65
2.2605 3.06
7.0506 3.96
66.80 75.35
55.23 23.04
6.722 2.230
Sig.
0.000* 0.039*
P < 0.05.
digitized model for all 19 patients before and after surgery. All measurements were recorded in the mid-sagittal plane of the airway. Airway resistance, R, was measured for all 19 patients before and after surgery. Resistance was calculated with Dp by using the equation R ¼ Dp/Fua, where Fua is the mass flow rate. The mass flow rate can be derived from the equation Fua ¼ Qr, where Q is the volumetric flow rate and r is the density of air [24]. 2.9. Statistical Analysis Analysis of the data was completed using IBM SPSS Statistics 19.0 (Armonk, NY). Descriptive statistics calculated the mean and standard deviation for maxillary and mandibular advancement, airway volume change, change in pressure, airway resistance, and maximum magnitude of velocity. Paired t-tests were used to test for significant differences for change in pressure, maximum velocities, and airway volume observed before and after surgery. Pearson correlations among airway resistance, airway volume change, and skeletal advancement were analyzed. A significance level of P < 0.05 was used. 3. Results
(ean SD ¼ 3.06 3.96 Pa) versus presurgery patients (mean SD ¼ 34.82 65.65 Pa). There was a statistically significant decrease in maximum airflow velocity along the airway after surgery. Postsurgery patients exhibited a significant decrease in maximum airflow velocity along the airway (mean SD ¼ 4.09 3.07 m/s) versus presurgery patients (mean SD ¼ 11.14 8.49 m/s). Tables 2 and 3 show differences at T0 to T1 at an average of 18.4 17.3 days after surgical advancement. 3.4. Correlation Analysis Correlations among airway resistance change and skeletal advancement and airway volume change and skeletal advancement are displayed in Tables 4 and 5, respectively. There was a statistically significant moderate, negative correlation between the change in airway resistance and the change in airway volume postsurgery. Very weak to weak, negative correlations were found between skeletal advancement and change in airway resistance, and weak, positive correlations were found between skeletal advancement and change in airway volume; however, those correlations were not statistically significant.
3.1. Cephalometric data
4. Discussion
The mean maxillary advancement was 4.5 2.2 mm, while the mean mandibular advancement was 9.1 3.8 mm. All measurements were taken in the horizontal plane.
In this study, we compared pharyngeal airflow characteristics using CBCT and CFD before and after maxillomandibular advancement surgery in patients with OSA. We found MMA led to an increase in airway volume and an alteration in airway geometry, thus leading to improvement in stenotic areas in the airway postsurgery. An increase in pharyngeal airway volume led to a decrease in airway resistance, which led to a decrease in pressure effort. Using anatomically correct airway models and an RNG k-ε turbulence flow model, we found a significant reduction in pressure drop and maximum airflow velocity after MMA. In general, as airway constriction was relieved post MMA, the pressure effort required to maintain the same constant airflow as the presurgery models decreased as well. While the current number of studies quantifying MMA treatment results using CFD are limited, completed research in this area of interest has shown results similar to the present study. Huynh et al. found similar results for pressure drop changes and reduction in airway resistance (90%) post MMA surgery using CFD [22]. Powell et al. found a 65% reduction in mean maximum airflow velocity and an 83% reduction in mean airway resistance for patients with sleep-
3.2. Volumetric data Means and standard deviations for airway volume before and after MMA surgery and percentage change in airway volume are presented in Table 2. There was a statistically significant increase in postsurgery airway volume. 3.3. Airflow data Means and standard deviations for change in pressure and percent change in airway resistance and maximum airflow velocity in the mid-sagittal plane before and after surgery are presented in Tables 2 and 3, respectively. There was a statistically significant decrease in pressure drop along the airway after surgery. The mean decrease in airway resistance was 75.35 23.04%. Postsurgery patients exhibited a significantly greater reduction in pressure drop along the airway
Table 3 Maximum velocity in the mid-sagittal plane (m/s) Measure
Velocity *
P < 0.05.
T0
Table 4 Correlations among airway volume and skeletal advancement
Pearson correlation
T1
Paired t
Mean
SD
Mean
SD
T0 to T1
11.14
8.49
4.09
3.07
3.503
Sig.
0.003*
Measure
DVol
Sig.
DA-point DB-point DR
0.327 0.217 0.682
0.086 0.187 0.001*
* P < 0.05; DA-point is the amount of maxillary advancement, DB-point is the amount of mandibular advancement, DR is the change in airway resistance, DVol is the change in airway volume.
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Table 5 Correlations among airway volume and skeletal advancement
Pearson correlation
Measure
DVol
Sig.
DA-point DB-point DR
0.327 0.217 0.682
0.086 0.187 0.001*
* P < 0.05; DA-point is the amount of maxillary advancement, DB-point is the amount of mandibular advancement, DR is the change in airway resistance, DVol is the change in airway volume.
disordered breathing [23]. Fan et al. found airway resistance decreased by 40% after surgical procedures to improve airway size [25]. Our study found a 48% reduction in mean maximum airflow velocity and a 75% reduction in mean airway resistance after MMA surgery. The airflow characteristics analyzed in this study demonstrated a clear improvement postsurgery. Detailed airway analyses of patient 1 before and after surgery show an area of obvious constriction and the resultant effects of the stenosis at the minimum cross-sectional area (Fig. 4). As the pressure begins to drop near the constriction, the axial velocity increases, which causes vortices to be formed at the anterior and posterior pharyngeal wall by the jet instabilities. This reduction in static pressure may lead to increased susceptibility to collapse. Figure 5 demonstrates the improvement in airway stenosis and the resultant effects of airway widening on airflow for patient 1 after surgery. The static pressures above the airway constrictions were significantly higher in the presurgery models with the pressure dropping post constriction versus the same areas in the postsurgery models, where the pressure drop was minimal. The average airflow
velocities distal to the constriction were significantly higher in the presurgery models relative to the postsurgery models. The inverse relationship between pressure and velocity post airway constriction is best demonstrated within each presurgery model from patient to patient. According to the Bernoulli principle, pressure and velocity are inversely related within a given tube for a given streamline. The results of the present study demonstrate the adherence to the Bernoulli principle [26]. The authors of this study acknowledge the following limitations: truncation of the airway domain, measurements for airflow characteristics were taken in the mid-sagittal plane only, patients were awake during scans, the stage of respiration was unknown, patients were scanned in an upright position, wax bites were used during presurgery but not postsurgery scans, and the AHI was unknown. This study does not take into account the effects of inspiration and expiration on airway rigidity; therefore, the value of movement and compliance of the soft tissue of the airway was not considered. It has been documented that the pharyngeal airway resistance for a given person changes over the respiratory cycle, showing the influence of dynamic airway geometry. Toward the end of the inspiratory cycle, increased resistance causes increased breathing effort due to the increased negative intraluminal pressure buildup [27]. In light of these limitations, the pressure distribution and resistance in the upper airway of patients with OSA were found to be significantly less after surgery and validate the results of other studies with similar methodology. More realistic simulations could be made possible by using a model approach that accounts for the deformability of the soft tissue of the pharyngeal airway, while including calculations for the interaction between the fluid flow and the compliant airway wall.
Fig. 4. Presurgery (A) pressure, (B) velocity, and (C) eddy viscosity coefficient contours for maximum pressure drop reduction (patient 1).
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
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Fig. 5. Postsurgery (A) pressure, (B) velocity, and (C) eddy viscosity contours for maximum pressure drop reduction (patient 1).
This methodology is known as fluidestructure interaction (FSI) and includes movement of the airway wall due to pressure and shear forces that act on the wall. The FSI model was not available to the researchers at the time this study was completed. Only a few studies using FSI have been completed, and most have used simplified or two-dimensional airway models that require a large amount of computational power [28e32]. Combining FSI with dynamic imaging, such as sleep magnetic resonance imaging, which has shown to be useful in identifying areas of airway obstruction during both the inspiratory and expiratory phases of respiration [33] may lead to more anatomically and functionally accurate airway models that allow for the improved study of pharyngeal airflow in patients with OSA. 5. Conclusions Through CFD modeling, the current study demonstrated that there was a statistically significant reduction in the pressure drop after MMA surgery and serves to validate similar past studies in the literature. The mean airway resistance was reduced by 75%, indicating an improvement in airflow after MMA surgery, thus requiring less pressure effort to breathe. References [1] Friedlander AH, Walker LA, Friedlander IK, et al. Diagnosing and comanaging patients with obstructive sleep apnea syndrome. J Am Dent Assoc 2000;131:1178e84. [2] Loadsman JA, Wilcox I. Is obstructive sleep apnoea a rapid eye movementpredominant phenomenon? Br J Anaesth 2000;85:354e8. [3] Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993;328:1230e5. [4] Kohler M, West S, Stradling J. Diabetes in obstructive sleep apnea. Am J Respir Crit Care Med 2010;182:286e7.
[5] Fleisher KE, Krieger AC. Current trends in the treatment of obstructive sleep apnea. J Oral Maxillofac Surg 2007;65:2056e68. [6] Padma A, Ramakrishnan NV. Managment of obstructive sleep apnea: A dental perspective. Indian J Dent Res 2007;18:201e9. [7] Schlosshan D, Elliott MW. Sleep, 3: Clinical presentation and diagnosis of the obstructive sleep apnoea hypopnoea syndrome. Thorax 2004;59: 347e52. [8] Baran AS, Richert AC. Obstructive sleep apnea and depression. CNS Spectr 2003;8:128e34. [9] Goncalves MA, Paiva T, Ramos E, Guilleminault C. Obstructive sleep apnea syndrome, sleepiness, and quality of life. Chest 2004;125:2091e6. [10] Britton TC, O’Donoghue M, Duncan JS, Hirsch NP. Exacerbation of epilepsy by obstructive sleep apnoea. J Neurol Neurosurg Psychiatry 1997;63:808. [11] Bohadana AB, Hannhart B, Teculescu DB. Nocturnal worsening of asthma and sleep-disordered breathing. J Asthma 2002;39:85e100. [12] Basner RC. Continuous positive airway pressure for obstructive sleep apnea. N Engl J Med 2007;356:1751e8. [13] Prinsell JR. Maxillomandibular advancement surgery in a site-specific treatment approach for obstructive sleep apnea in 50 consecutive patients. Chest 1999;116:1519e29. [14] Riley RW, Powell NB, Guilleminault C. Obstructive sleep apnea syndrome: A review of 306 consecutively treated surgical patients. Otolaryngol Head Neck Surg 1993;108:117e25. [15] Waite PD, Wooten V, Lachner J, Guyette RF. Maxillomandibular advancement surgery in 23 patients with obstructive sleep apnea syndrome. J Oral Maxillofac Surg 1989;47:1256e61. [16] Hochban W, Conradt R, Brandenburg U, Heitmann J, Peter JH. Surgical maxillofacial treatment of obstructive sleep apnea. Plast Reconstr Surg 1997;99:619e26. [17] Prinsell JR. Maxillomandibular advancement surgery for obstructive sleep apnea syndrome. J Am Dent Assoc 2002;133:1489e97. [18] Sung SJ, Jeong SJ, Yu YS, Hwang CJ, Pae EK. Customized three-dimensional computational fluid dynamics simulation of the upper airway of obstructive sleep apnea. Angle Orthod 2006;76:791e9. [19] Yu CC, Hsiao HD, Tseng TI, et al. Computational fluid dynamics study of the inspiratory upper airway and clinical severity of obstructive sleep apnea. J Craniofac Surg 2012;23:401e5. [20] Ito Y, Cheng GC, Shih AM, et al. Patient-specific geometry modeling and mesh generation for simulating obstructive sleep apnea syndrome cases by maxillomandibular advancement. Math Comput Simul 2011;81:1876e91. [21] Cheng GC, Koomullil RP, Ito Y, et al. Assessment of surgical effects on patients with obstructive sleep apnea syndrome using computational fluid dynamics simulations. Math Comput Simul 2014;106:44e59.
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[22] Huynh J, Kim KB, McQuilling M. Pharyngeal airflow analysis in obstructive sleep apnea patients pre- and post-maxillomandibular advancement surgery. J Fluid Eng-T ASME 2009;131:091101e10. [23] Powell NB, Mihaescu M, Mylavarapu G, et al. Patterns in pharyngeal airflow associated with sleep-disordered breathing. Sleep Med 2011;12: 966e74. [24] De Backer JW, Vanderveken OM, Vos WG, et al. Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing. J Biomech 2007;40:3708e14. [25] Fan YC, Chong LK, Chua MM, et al. Computational fluid dynamics analysis on the upper airways of obstructive sleep apnea using patient-specific models. Int J Comput Sci 2011;38:401e8. [26] Streeter VL. Fluid Mechanics. Example 35. New York: McGraw-Hill Inc.; 1966. [27] Persak SC, Sin S, McDonough JM, Arens R, Wootton DM. Noninvasive estimation of pharyngeal airway resistance and compliance in children based on volume-gated dynamic MRI and computational fluid dynamics. J Appl Physiol 2011;111:1819e27.
[28] Chouly F, Van Hirtum A, Lagree PY, Pelorson X, Payan Y. Modelling the human pharyngeal airway: Validation of numerical simulations using in vitro experiments. Med Biol Eng Comput 2009;47:49e58. [29] Paulsen FP, Steven P, Tsokos M, et al. Upper airway epithelial structural changes in obstructive sleep-disordered breathing. Am J Respir Crit Care Med 2002;166:501e9. [30] Mylavarapu GM, Murugappan S, Gutmark EJ, Kalra M. Fluid Structure Interaction Analysis in Human Upper Airways to Understand Sleep Apnea. 48th AIAA Aerospace Science Meeting 2010; Orlando, Florida. [31] Balint TS. Instability of a cantilevered flexible plate in viscous channel flow. J Fluids Struct 2005;20:893e912. [32] Zhao M, Barber T, Cistulli PA, Sutherland K, Rosengarten G. Simulation of upper airway occlusion without and with mandibular advancement in obstructive sleep apnea using fluid-structure interaction. J Biomech 2013;46:2586e92. [33] Barrera JE. Sleep magnetic resonance imaging: Dynamic characteristics of the airway during sleep in obstructive sleep apnea syndrome. Laryngoscope 2011;121:1327e35.
Contents lists available at ScienceDirect
Journal of the World Federation of Orthodontists journal homepage: www.jwfo.org
Research
Computational airflow analysis before and after maxillomandibular advancement surgery Ki Beom Kim a, *, Patrick G. McShane a, Mark McQuilling b, Donald R. Oliver a, Michael Schauseil c a
Department of Orthodontics, Center for Advanced Dental Education, Saint Louis University, St. Louis, Missouri Parks College of Engineering, Aviation, and Technology, Saint Louis University, St. Louis, Missouri c Department of Orthodontics, University of Marburg, Marburg, Germany b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 26 July 2015 Accepted 7 December 2015 Available online 26 January 2016
Background: The purpose of this study was to analyze pharyngeal airflow using computational fluid dynamics (CFD) in obstructive sleep apnea (OSA) patients before and after maxillomandibular advancement (MMA). Methods: Digitized pharyngeal airway models of 19 obstructive sleep apnea patients were generated from cone beam computed tomography scans presurgery and an average of 18.3 17.3 days postsurgery. CFD was used to simulate and characterize pharyngeal airflow, which was assumed to be turbulent at an inspiration rate of 340 mL/s. Standard steady-state numerical formulation were used for airflow simulations. Results: Mean pressure drop during inspiration was significantly reduced from 34.82 65.65 Pa presurgery to 3.06 3.96 Pa postsurgery. Mean maximum airflow velocity along the airway was also significantly reduced from 11.14 8.49 m/s presurgery to 4.09 3.07 m/s postsurgery. There was a significant increase in mean airway volume of 66.8% postsurgery. There was a 75% mean reduction in airway resistance postsurgery. There was a decrease in the pressure gradient and total pressure drop postsurgery for all 19 patients. There was a statistically significant moderate, negative correlation between the change in airway resistance and the change in airway volume postsurgery. No correlation was found between skeletal advancement and airway volume or airway resistance. Conclusions: A decrease in relative pressure implies less effort required for maintaining constant pharyngeal airflow according to CFD analyses on airways of OSA patients after MMA surgery. Ó 2016 World Federation of Orthodontists.
Keywords: Airway Computational fluid dynamics Maxillomandibular advancement Obstructive sleep apnea
1. Introduction Obstructive sleep apnea (OSA) is a sleep-related breathing disorder characterized by the partial or complete collapse of the upper airway during both rapid eye motion (REM) and non-REM sleep [1,2]. Epidemiologic estimates of OSA prevalence are approximately 9%e24% for middle-aged adults with up to 80% of patients remaining undiagnosed [3]. Sleep-related breathing disorders, when left untreated, can increase the risk for cardiovascular diseases, hypertension, stroke, angina, headaches, excessive daytime sleepiness,
All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest, and none were reported. * Corresponding author: Department of Orthodontics, Center for Advanced Dental Education, Saint Louis University, 3320 Rutger Street, St. Louis, MO 63104. E-mail address: [email protected] (K.B. Kim). 2212-4438/$ e see front matter Ó 2016 World Federation of Orthodontists. http://dx.doi.org/10.1016/j.ejwf.2015.12.002
poor work performance, occupational accidents, cognitive dysfunction, depression, and exacerbation of type 2 diabetes [4e11]. Various therapies exist in the treatment of OSA. Continuous positive airway pressure is a highly effective therapeutic modality for the treatment of OSA and remains the gold standard [5]. Multilevel surgical interventions play an important role as secondline treatment for anatomical obstruction [12]. A highly effective stage 2 surgical option for the treatment of severe OSA is maxillomandibular advancement (MMA) surgery with success rates of 65e100% [13e17]. The study of pharyngeal airflow after MMA surgery has been targeted as an area of interest using computational fluid dynamics (CFD). CFD provides a method for the indirect study of pharyngeal airflow. Sung et al. [18] found maximum airflow velocity and lowest pressure at the narrowest part of the velopharynx. Using CFD, Yu et al. [19] showed the correlation between CFD simulation and apnea-hypopnea index (AHI). Ito et al. [20] constructed hybrid
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
models composed of posttreatment nasal cavities superimposed on pretreatment nasal cavities and posttreatment nasal and pharyngeal airway models to simulate airflow and found a decrease in pressure effort to breathe evidenced by a decrease in the negative pressure post MMA surgery. Last, numerous investigations found a decrease in airway resistance after MMA surgery [20e23]. The purposes of this study are to analyze and compare pharyngeal airflow characteristics in patients with OSA before and after MMA surgery using CFD and to validate previous research findings. 2. Materials and methods 2.1. Patient Selection Pretreatment and posttreatment cone beam computed tomography (CBCT) scans of 19 patients (9 male and 10 female) who had undergone both orthodontic treatment and MMA surgery were used in this retrospective study (Table 1). Inclusion criteria include (1) having a history of OSA and (2) being treated with both orthodontics and MMA surgery. Exclusion criteria included (1) having a craniofacial syndrome and (2) having surgical maxillary expansion. The surgical procedures completed were carried out by two oral surgeons using the same surgical techniques. A nonsegmental Le Fort I osteotomy was used to advance the maxilla, while bilateral sagittal split ramus osteotomies were used to advance the mandible. The presurgical and postsurgical AHI values were unavailable to the researchers for this study. 2.2. CBCTs
was subtracted. A perpendicular line was drawn through the corrected horizontal plane from nasion and then the distance to A-point and B-point was measured and compared before and after surgery (Fig. 1). 2.4. Isolating the pharyngeal airway The CBCT scans were imported into Mimics software as DICOM (Digital Imaging and Communications in Medicine) files to generate a volumetric image of the scanned region. Once the volume was generated, the pharyngeal airway of interest was isolated. The superior border was defined by creating a plane through left and right porus acousticus externus and nasion; the anterior border was defined by creating a perpendicular plane to the superior border going through the most anterior and middle point of the sella wall; and the inferior border was defined by creating a horizontal plane parallel to the superior plane through the most inferior and anterior point of C3. The anterior and posterior wall of the volume was defined by the natural border of the pharynx. The uvula was removed in all cases to avoid artifacts (Fig. 2). 2.5. Computer modeling and mesh generation Pharyngeal airway models were imported into Geomagic to check for model integrity. Models were transferred into SC/Tetra preprocessing software (version 9.0, Software Cradle Corporation, Osaka, Japan) for model and mesh generation. Inlet, outlet, and wall boundaries were defined manually (Fig. 3A). Appropriate grid size, number of tetrahedral elements, and octree size of 0.5 mm were chosen for the mesh model using the
CBCT scans were taken before and after MMA surgery using the same i-CAT machine (Imaging Sciences International, Hatfield, PA): T0 (presurgery) and T1 (2e4 weeks postsurgery; Table 1). Imaging field of view was 23 cm 19 cm with a voxel size of 0.4 mm. Presurgical scans were taken with an interocclusal wax bite in centric relation. Postsurgical scans were taken with the condyles in centric relation and no wax bite. Presurgery and postsurgery scans were taken with the patient standing upright and head position parallel to the Frankfort horizontal plane. The patients were instructed not to swallow and not to move the tongue during the scanning. Mimics 3D software (version 15.0, Materialise, Levuen, Belgium), Geomagic (version 2012, 3D Systems, Rock Hill, SC), and Dolphin 3D (version 11.0, Chatsworth, CA) were used to view, analyze, and manipulate the CBCT scans. 2.3. Calculation of surgical movement The calculation of the anteroposterior surgical movement was measured for the maxilla and mandible by converting the CBCT scan from a three-dimensional volume to a two-dimensional lateral cephalogram image. The skeletal landmarks used to measure surgical movement were sella, nasion, A-point, and B-point. A reference plane was drawn through sella and nasion and then 7 (SN-7 )
Table 1 Patient characteristics: age and time between CBCT scans Number of subjects
Age (y) Mean
SD
Mean
SD
Male Female
40.8 36.3
12.9 15.9
17.6 19.1
14.4 20.3
9 10
3
Time between scans (d)
Fig. 1. Lateral cephalograms demonstrating measurement of surgical movement.
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2.6. Solving methods Mesh models were imported into SC/Tetra Solver (version 9.0, Software Cradle Corporation) for airflow simulation. A turbulent model flow, the RNG k-ε model, was used to simulate turbulent airflow within the pharyngeal airway, similar to the turbulent model equations used in the Huynh et al. [22] and Sung et al. [18] studies. The RNG k-ε model was chosen because of its minimal computing power required for flow simulation. Using a volumetric flow rate of 340 mL/s, corresponding inlet boundary velocities were calculated for each model using the formula Q ¼ AV. Inlet area, A, was determined from the preprocessor function in SC/Tetra for each model. The outlet boundary condition was set at a static pressure of 0 Pa. The walls of the model, which were assumed to be rigid and noncompliant, were set to no-slip conditions. Air flow simulations were completed using the SC/Tetra Solver function on a PC with an IntelÒ CoreÔ i7 CPU Q740 (1.73 GHz) with 8 GB of RAM. After solver functions were completed, SC/Tetra postprocessor software (version 9.0) was used to analyze and visualize the fluid flow data. 2.7. Magnitude of airflow velocity measurements
Fig. 2. Airway volume model segmentation boundaries.
same protocol used by Huyhn et al. [22] (Fig. 3B). The final mesh models of the airways had an average of 314,193 tetrahedral elements.
The maximum magnitude of airflow velocity was measured for all 19 patients before and after surgery. All measurements were recorded in the mid-sagittal plane of the airway. Velocity measurements were made using the SC/Tetra postprocessor. 2.8. Pressure calculations and airway resistance The postprocessor function of SC/Tetra was used to calculate the change in pressure, Dp, from the inlet to outlet boundary over the
Fig. 3. (A) Three-dimensional airway model and (B) mesh model file demonstrating tetrahedral elements.
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
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Table 2 Measurements of airway volume (mm3) and pressure change in the mid-sagittal plane (Pa) Measure
T0
Airway Volume Change in pressure *
T1
% Change
Paired t
Mean
SD
Mean
SD
Mean
SD
T0 to T1
1.3505 34.82
5.0006 65.65
2.2605 3.06
7.0506 3.96
66.80 75.35
55.23 23.04
6.722 2.230
Sig.
0.000* 0.039*
P < 0.05.
digitized model for all 19 patients before and after surgery. All measurements were recorded in the mid-sagittal plane of the airway. Airway resistance, R, was measured for all 19 patients before and after surgery. Resistance was calculated with Dp by using the equation R ¼ Dp/Fua, where Fua is the mass flow rate. The mass flow rate can be derived from the equation Fua ¼ Qr, where Q is the volumetric flow rate and r is the density of air [24]. 2.9. Statistical Analysis Analysis of the data was completed using IBM SPSS Statistics 19.0 (Armonk, NY). Descriptive statistics calculated the mean and standard deviation for maxillary and mandibular advancement, airway volume change, change in pressure, airway resistance, and maximum magnitude of velocity. Paired t-tests were used to test for significant differences for change in pressure, maximum velocities, and airway volume observed before and after surgery. Pearson correlations among airway resistance, airway volume change, and skeletal advancement were analyzed. A significance level of P < 0.05 was used. 3. Results
(ean SD ¼ 3.06 3.96 Pa) versus presurgery patients (mean SD ¼ 34.82 65.65 Pa). There was a statistically significant decrease in maximum airflow velocity along the airway after surgery. Postsurgery patients exhibited a significant decrease in maximum airflow velocity along the airway (mean SD ¼ 4.09 3.07 m/s) versus presurgery patients (mean SD ¼ 11.14 8.49 m/s). Tables 2 and 3 show differences at T0 to T1 at an average of 18.4 17.3 days after surgical advancement. 3.4. Correlation Analysis Correlations among airway resistance change and skeletal advancement and airway volume change and skeletal advancement are displayed in Tables 4 and 5, respectively. There was a statistically significant moderate, negative correlation between the change in airway resistance and the change in airway volume postsurgery. Very weak to weak, negative correlations were found between skeletal advancement and change in airway resistance, and weak, positive correlations were found between skeletal advancement and change in airway volume; however, those correlations were not statistically significant.
3.1. Cephalometric data
4. Discussion
The mean maxillary advancement was 4.5 2.2 mm, while the mean mandibular advancement was 9.1 3.8 mm. All measurements were taken in the horizontal plane.
In this study, we compared pharyngeal airflow characteristics using CBCT and CFD before and after maxillomandibular advancement surgery in patients with OSA. We found MMA led to an increase in airway volume and an alteration in airway geometry, thus leading to improvement in stenotic areas in the airway postsurgery. An increase in pharyngeal airway volume led to a decrease in airway resistance, which led to a decrease in pressure effort. Using anatomically correct airway models and an RNG k-ε turbulence flow model, we found a significant reduction in pressure drop and maximum airflow velocity after MMA. In general, as airway constriction was relieved post MMA, the pressure effort required to maintain the same constant airflow as the presurgery models decreased as well. While the current number of studies quantifying MMA treatment results using CFD are limited, completed research in this area of interest has shown results similar to the present study. Huynh et al. found similar results for pressure drop changes and reduction in airway resistance (90%) post MMA surgery using CFD [22]. Powell et al. found a 65% reduction in mean maximum airflow velocity and an 83% reduction in mean airway resistance for patients with sleep-
3.2. Volumetric data Means and standard deviations for airway volume before and after MMA surgery and percentage change in airway volume are presented in Table 2. There was a statistically significant increase in postsurgery airway volume. 3.3. Airflow data Means and standard deviations for change in pressure and percent change in airway resistance and maximum airflow velocity in the mid-sagittal plane before and after surgery are presented in Tables 2 and 3, respectively. There was a statistically significant decrease in pressure drop along the airway after surgery. The mean decrease in airway resistance was 75.35 23.04%. Postsurgery patients exhibited a significantly greater reduction in pressure drop along the airway
Table 3 Maximum velocity in the mid-sagittal plane (m/s) Measure
Velocity *
P < 0.05.
T0
Table 4 Correlations among airway volume and skeletal advancement
Pearson correlation
T1
Paired t
Mean
SD
Mean
SD
T0 to T1
11.14
8.49
4.09
3.07
3.503
Sig.
0.003*
Measure
DVol
Sig.
DA-point DB-point DR
0.327 0.217 0.682
0.086 0.187 0.001*
* P < 0.05; DA-point is the amount of maxillary advancement, DB-point is the amount of mandibular advancement, DR is the change in airway resistance, DVol is the change in airway volume.
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Table 5 Correlations among airway volume and skeletal advancement
Pearson correlation
Measure
DVol
Sig.
DA-point DB-point DR
0.327 0.217 0.682
0.086 0.187 0.001*
* P < 0.05; DA-point is the amount of maxillary advancement, DB-point is the amount of mandibular advancement, DR is the change in airway resistance, DVol is the change in airway volume.
disordered breathing [23]. Fan et al. found airway resistance decreased by 40% after surgical procedures to improve airway size [25]. Our study found a 48% reduction in mean maximum airflow velocity and a 75% reduction in mean airway resistance after MMA surgery. The airflow characteristics analyzed in this study demonstrated a clear improvement postsurgery. Detailed airway analyses of patient 1 before and after surgery show an area of obvious constriction and the resultant effects of the stenosis at the minimum cross-sectional area (Fig. 4). As the pressure begins to drop near the constriction, the axial velocity increases, which causes vortices to be formed at the anterior and posterior pharyngeal wall by the jet instabilities. This reduction in static pressure may lead to increased susceptibility to collapse. Figure 5 demonstrates the improvement in airway stenosis and the resultant effects of airway widening on airflow for patient 1 after surgery. The static pressures above the airway constrictions were significantly higher in the presurgery models with the pressure dropping post constriction versus the same areas in the postsurgery models, where the pressure drop was minimal. The average airflow
velocities distal to the constriction were significantly higher in the presurgery models relative to the postsurgery models. The inverse relationship between pressure and velocity post airway constriction is best demonstrated within each presurgery model from patient to patient. According to the Bernoulli principle, pressure and velocity are inversely related within a given tube for a given streamline. The results of the present study demonstrate the adherence to the Bernoulli principle [26]. The authors of this study acknowledge the following limitations: truncation of the airway domain, measurements for airflow characteristics were taken in the mid-sagittal plane only, patients were awake during scans, the stage of respiration was unknown, patients were scanned in an upright position, wax bites were used during presurgery but not postsurgery scans, and the AHI was unknown. This study does not take into account the effects of inspiration and expiration on airway rigidity; therefore, the value of movement and compliance of the soft tissue of the airway was not considered. It has been documented that the pharyngeal airway resistance for a given person changes over the respiratory cycle, showing the influence of dynamic airway geometry. Toward the end of the inspiratory cycle, increased resistance causes increased breathing effort due to the increased negative intraluminal pressure buildup [27]. In light of these limitations, the pressure distribution and resistance in the upper airway of patients with OSA were found to be significantly less after surgery and validate the results of other studies with similar methodology. More realistic simulations could be made possible by using a model approach that accounts for the deformability of the soft tissue of the pharyngeal airway, while including calculations for the interaction between the fluid flow and the compliant airway wall.
Fig. 4. Presurgery (A) pressure, (B) velocity, and (C) eddy viscosity coefficient contours for maximum pressure drop reduction (patient 1).
K.B. Kim et al. / Journal of the World Federation of Orthodontists 5 (2016) 2e8
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Fig. 5. Postsurgery (A) pressure, (B) velocity, and (C) eddy viscosity contours for maximum pressure drop reduction (patient 1).
This methodology is known as fluidestructure interaction (FSI) and includes movement of the airway wall due to pressure and shear forces that act on the wall. The FSI model was not available to the researchers at the time this study was completed. Only a few studies using FSI have been completed, and most have used simplified or two-dimensional airway models that require a large amount of computational power [28e32]. Combining FSI with dynamic imaging, such as sleep magnetic resonance imaging, which has shown to be useful in identifying areas of airway obstruction during both the inspiratory and expiratory phases of respiration [33] may lead to more anatomically and functionally accurate airway models that allow for the improved study of pharyngeal airflow in patients with OSA. 5. Conclusions Through CFD modeling, the current study demonstrated that there was a statistically significant reduction in the pressure drop after MMA surgery and serves to validate similar past studies in the literature. The mean airway resistance was reduced by 75%, indicating an improvement in airflow after MMA surgery, thus requiring less pressure effort to breathe. References [1] Friedlander AH, Walker LA, Friedlander IK, et al. Diagnosing and comanaging patients with obstructive sleep apnea syndrome. J Am Dent Assoc 2000;131:1178e84. [2] Loadsman JA, Wilcox I. Is obstructive sleep apnoea a rapid eye movementpredominant phenomenon? Br J Anaesth 2000;85:354e8. [3] Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993;328:1230e5. [4] Kohler M, West S, Stradling J. Diabetes in obstructive sleep apnea. Am J Respir Crit Care Med 2010;182:286e7.
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