My research interests include studying the anatomical risk factors for sleep apnea in children utilizing novel MRI methodology (1-3). These studies provide insight on the anatomical contribution to the pathophysiology of sleep apnea in children.
The geometric and architectural information related to the upper airway in these studies are obtained only from imaging; therefore effective image processing to extract this information becomes vital. The lack of a readily available system to quantify and analyze upper airways from routine MRI protocols motivated our group and our collaborators from the University of Pennsylvania and Drexel University to develop a methodology of our own three years ago (4-5).
The goal for this methodology was to analyze the morphology and architecture of upper airway and its surrounding tissues using a novel, efficient, and reliable method. We have developed a new set of algorithms and implemented in the software system 3DVIEWNIX for 3D airway construction, visualization, and analysis. This method enables accurate representation of the airway as it relates to airflow and surrounding tissues and is significantly more efficient than manual segmentation.
In addition, we have developed a dynamic technique to image the upper airway using respiratory-gated MRI (6). This method can determine the temporal changes in airway size and shape during inspiratory and expiratory phases of breathing. The most recent development by our group relates to the used of computational fluid dynamics to model the upper airway in children with obstructive sleep apnea (7). This methodology uses the advantages of computer science to simulate upper airway mechanics in a non-invasive way.
1. Arens R, McDonough JM, Costarino AT, Tayag-Kier CE, Mahboubi S, Maislin G, Schwab RJ, Pack AI. Magnetic resonance imaging of the upper airway structure in children with obstructive sleep apnea syndrome. Am J Respir Crit Care Med 2001; 164:698-703.
2. Arens R, McDonough JM, Corbin AM, Hernandez EM, Maislin G, Schwab RJ, Pack AI. Linear dimensions of the upper airway structure during development: assessment by magnetic resonance imaging. Am J Respir Crit Care Med 2002; 165:117-22.
3. Schiffman PH, Rubin NK, Domingues T, Mahboubi S, Udupa JK, O’Donnell AR, Maislin G, Schwab RJ, McDonough JM, Arens R. Mandibular dimensions in children with obstructive sleep apnea syndrome. Sleep 2004; 27:959-65.
4. Arens R, McDonough JM, Corbin AM, Rubin NK, Carroll, M, Pack AI, Liu J, Udupa JK. Upper airway size analysis by magnetic resonance imaging of children with obstructive sleep apnea syndrome. Am J Respir Crit Care Med 2003; 167:65-70.
5. Liu J, Udupa JK, Odhner D, McDonough JM, Arens R. System for upper airway segmentation and measurements with MR imaging and fuzzy connectedness. Acad Radiol 2003; 10:13-24.
6. Arens R, Sin S, McDonough JM, Palmer J, Dominguez T, Meyer H, Wootton DM, Pack. AI. Changes in upper airway size during tidal breathing in children with obstructive sleep apnea. Am J Respir Crit Care Med 2005; 1298-1304.
7. Xu C, Sin S, McDonough JM, Udupa JK, Guez A, Arens R, Wootton DM. Computational fluid dynamics modeling of the upper airway in children with obstructive sleep apnea in steady flow. J Biomech 2006; 39:2043-54.
8. Arens R, Marcus CL. Pathophysiology of upper airway obstruction: a developmental perspective. Sleep 2004; 27:997-1019.
9. Traeger N, Schultz B, Pollock AA, Mason T, Marcus CL, Arens R. Polysomnographic values in children 2-9 years old: additional data and a review of the literature. Pediatr Pulmonol 2005; 40: 22-30.