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Automated 3-Dimensional Airway Analysis From Cone-Beam Computed Tomography Data

2010; Elsevier BV; Volume: 68; Issue: 3 Linguagem: Inglês

10.1016/j.joms.2009.07.040

1531-5053

Stephen A. Schendel, David C. Hatcher,

Airway Management and Intubation Techniques

The analysis and 3-dimensional (3D) imaging of the airway have become more common as technological developments in both imaging and computer analysis have advanced and converged during the past few years. 1 Mah J.K. Danforth R.A. Bumann A. et al. Radiation absorbed in maxillofacial imaging with a new dental computed tomography device. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2003; 96: 508 Abstract Full Text Full Text PDF PubMed Scopus (262) Google Scholar , 2 Loubele M. Bogaerts R. Van Dijck E. et al. Comparison between effective radiation dose of CBCT and MSCT scanners for dentomaxillofacial applications. Eur J Radiol. 2009; 71: 461 Abstract Full Text Full Text PDF PubMed Scopus (404) Google Scholar These advances have been especially beneficial for the ability to understand and diagnose obstructed sleep disordered breathing (OSDB) and its relationship to the craniofacial anatomy. The improved availability of cone-beam computed tomography (CBCT), 3D imaging, and computer simulation in dentofacial analysis and treatment planning has facilitated the use of this method for evaluation of the airway. 3 Muto T. Yamazaki A. Takeda S. et al. Accuracy of predicting the pharyngeal airway space on the cephalogram after mandibular setback surgery. J Oral Maxillofac Surg. 2008; 66: 1099 Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar , 4 Ogawa T. Enciso R. Shintaku W.H. et al. Evaluation of cross-section airway configuration of obstructive. Oral Surg Oral Med Oral Path. 2007; 103: 102 Abstract Full Text Full Text PDF Scopus (175) Google Scholar , 5 Barkdul G.C. Kohl C.A. Patel M. et al. Computed tomography imaging of patients with obstructive sleep apnea. Laryngoscope. 2008; 118: 1486 Crossref PubMed Scopus (65) Google Scholar , 6 Chen N.H. Li K.K. Li S.Y. et al. Airway assessment by volumetric computed tomography in snorers and subjects with obstructive sleep apnea in a Far-East Asian population. Laryngoscope. 2002; 112 (Chinese): 721 Crossref PubMed Scopus (71) Google Scholar , 7 Yamashina A. Tanimoto K. Sutthiprapaporn P. et al. The reliability of computed tomography (CT) values and dimensional measurements of the oropharyngeal region using cone beam CT: Comparison with multidetector CT. Dentomaxollofac Radiol. 2008; 37: 245 Crossref PubMed Scopus (94) Google Scholar , 8 Lowe A.A. Gionhaku N. Takeuchi K. et al. Three-dimensional CT reconstructions of tongue and airway in adult subjects with obstructive sleep apnea. Am J Orthod Dentofac Orthop. 1986; 90: 364 Abstract Full Text PDF PubMed Scopus (171) Google Scholar , 9 Avrahami E. Englender M. Relation between CT axial cross-sectional area of the oropharynx and obstructive sleep apnea syndrome in adults. AJNR Am J Neuroradiol. 1995; 16: 135 PubMed Google Scholar , 10 Consentini T. Le Donne R. Mancini D. et al. Magnetic resonance imaging of the upper airway in obstructive sleep apnea. Radiol Med. 2004; 108: 404 PubMed Google Scholar , 11 Li H.Y. Chen N.H. Wang C.R. et al. Use of 3-dimensional computed tomography scan to evaluate upper airway patency for patients undergoing sleep-disordered breathing surgery. Otolaryngol Head Neck Surg. 2003; 1294: 336 Crossref Scopus (99) Google Scholar , 12 Ogawa T. Enciso R. Shintaku W.H. et al. Evaluation of cross-section airway configuration of obstructive sleep apnea. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2007; 103: 102 Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar , 13 Diniz P. da Silva E. Netto S. Digital Signal Processing: System Analysis and Design. in: Cambridge University Press, Cambridge, UK2002: 24 Google Scholar , 14 Blackledge J. Digital Signal Processing: Mathematical and Computational Methods, Software Development and Applications. in: Horwood Publishing, Chichester, West Sussex, UK2003: 93 Google Scholar The currently available diagnosis and treatment planning methods for OSDB have limitations despite inclusion of the patient's sleep history, nasendoscopy, polysomnography, and conventional imaging. A precise anatomic analysis of the airway that could be correlated with the severity of OSDB and be easily obtainable would be valuable for diagnosis and treatment planning. At present, the airway calculation from computed tomography data requires time-consuming manual data segmentation, the accuracy of which could be questionable. Automatic data segmentation has the ability to provide rapid and reliable airway analysis results.