New advances for imaging of laryngotracheal stenosis by post processing of spiral-CT data

  • E. Sorantin
  • C. Halmai
  • B. Erdhelyi
  • L. Martonossy
  • K. Palagy
  • B. Geiger


Endotracheal intubation is the most common cause of laryngotracheal stenosis (LTS), followed by external trauma and prior airway surgery [4,8,13]. In rare cases LTS may have resulted also from inhalation injuries, gastroesophageal reflux disease, neoplasia and autoimmune diseases like Wegeners granulomatosis or relapsing polychondritis [4,21]. In paediatric patients vascular compression of the trachea is a common cause of tracheal indentations. Clinical management of these conditions requires information on localization, grade, length and dynamics of the stenosis. The gold standard for airway evaluation is fiberoptic endoscopy (FE) [4]. Imaging modalities like conventional radiography, fluoroscopy, tracheal tomograms, Magnetic Resonance Imaging and above all Spiral Computed Tomography (S-CT) are an essential part of the clinical work up [5]. S-CT allows volumetric data acquisition during a short time span. Decreased motion artefacts and the possibility of reconstructing overlapping slices are the basis for high quality post processing [11,23].


Spiral Compute Tomography Medial Axis Tracheal Stenosis Cross Sectional Profile Relapse Polychondritis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    Blezek D, Robb R (1997) Evaluating virtual endos-copy for clinical use. J of Digital Imag 3 (Suppl 1): 51–55CrossRefGoogle Scholar
  2. [2]
    Boissonnat J, Geiger B (1993) Three dimensional reconstruction of complex shapes based on the (delaunay) triangulation. In: Acharya R, Goldgof D (eds) Biomedical Image Processing and Biomedical Visualization. SPIE Proceedings, San Jose, CA, pp 964–975CrossRefGoogle Scholar
  3. [3]
    Carey R, Bell G (1996) The Annotated VRML 2. 0 Reference Manual. Addison Wesely Developers PressGoogle Scholar
  4. [4]
    Couray M, Ossoff R (1998) Laryngeal stenosis: A review of staging, treatment, and current research. Current opinion in Otolaryngology, Head and Neck Surgery 6: 407–410Google Scholar
  5. [5]
    Czaja J, McCaffrey T (1996) Acoustic measurement of subglottic stenosis. Ann Otol Rhinol Laryngol 105: 504–509PubMedGoogle Scholar
  6. [6]
    Frey E, Smith W, Grandgeorge S, McCray P, Wagener J Jr, Franken EA Jr, Sato Y (1987) Chronic airway obstruction in children: Evaluation with cine-ct. AJR 148: 347–352Google Scholar
  7. [7]
    Gonzalez C, Woods R (1993) Morphology. AddisonWesley-Publishing CompanyGoogle Scholar
  8. [8]
    Grillo H, Dnonahue D, Mathiesen D, Wain J, Wright C (1995) Postintubation tracheal stenosis: Treatment and results. J. Thorax Cardiovasc Surg 109: 486–492Google Scholar
  9. [9]
    Huber M, Henderson R, Finn-Bodner S, Macinitre D, Wrigh J, Hankes G (1997) Assessment of current techniques for determining tracheal luminal stenosis in dogs. AJVR 10: 1051–1054Google Scholar
  10. [10]
    Jewett B, Cook R, Johnson K, Logan T, Rosbe K, Mukherji S, Shockley W (1999) Subglottic stenosis: Correlation between computed tomography and bronchoscopy. Ann Otol Rhinol Laryngol 108: 837–841Google Scholar
  11. [11]
    Kuszyk B, Heath D, Bliss D, Fishman E (1996) Skeletal 3d-ct: Advantages of volume rendering over surface rendering. Skeletal Radiol 25: 207–214Google Scholar
  12. [12]
    Lacrosse M, Trigaux J, van Beers B, Weynants P (1995) 3d spiral ct of the tracheobronchial tree. J Comput Assist Tomogr 19 (3): 341–347Google Scholar
  13. [13]
    Lano C, Duncavage J, Reinisch L, Ossoff R, Couray M, Netterville J (1998) Laryngotracheal reconstruction in the adult: A ten year experience. Ann Otol Rhinol Laryngol 107: 92–96Google Scholar
  14. [14]
    McAdams H, Palmer S, Erasmus J, Patz E, Connolly J, Goodman P, Delong D, Tapson V (1998) Bronchial anastomotic complications in lung transplant recipients: Virtual bronchoscopy for noninvasive assessment. Radiology 209: 689–695Google Scholar
  15. [15]
    McCaffrey T, Czaja J (1992) Classification of laryngeal stenosis. Laryngoscope 102: 1335–1340PubMedCrossRefGoogle Scholar
  16. [16]
    Palagyi K, Kuba A (1998) A 3d 6-subiteration thinning algorithm for extracting medial lines. Pattern Recognition Letters 19: 613–627CrossRefGoogle Scholar
  17. [17]
    Park W, Hoffman E, Sonka M (1996) Fuzzy logic approach to extraction of intrathoracic airway trees from three dimensional ct images. SPIE 2710: 210–217CrossRefGoogle Scholar
  18. [18]
    Remy-Jardin M, Remy J, Artaud D, Fribourg M, Duhamel A (1998) Volume rendering of tracheobronchial tree: Clinical evaluation of bronchographic images. Radiology 208: 761–770Google Scholar
  19. [19]
    Rogers L (1998) A day in the court of lexicon: Virtual endoscopy. AJR 171: 11–85Google Scholar
  20. [20]
    Rubin G, Beaulieu C, Argiro V (1996) Perspective volume rendering of ct and mr images: Applications for endoscopic imaging. Radiology 199: 321–330Google Scholar
  21. [21]
    Spraggs H, Tostevin P (1997) Management of laryngotracheobronchial sequelae and complications of relapsing polychondritis. Laryngoscope 107: 936–941PubMedCrossRefGoogle Scholar
  22. [22]
    Stern E, Graham C, Webb R, Gamsu G (1993) Normal trachea during forced exspiration: Dynamic ct measurements. Radiology 187: 27–31Google Scholar
  23. [23]
    Zeiberg A, Silverman P, Sessions R, Troost T, Davros W, Zeman R (1996) Helical (spiral) ct of the upper airway with three-dimensional imaging: Technique and clinical assessment. AJR 166: 293–299Google Scholar

Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • E. Sorantin
    • 1
  • C. Halmai
    • 2
  • B. Erdhelyi
    • 2
  • L. Martonossy
    • 2
  • K. Palagy
    • 2
  • B. Geiger
    • 3
  1. 1.Division of Digital Information and Image Processing, Department of RadiologyUniversity Hospital GrazGrazAustria
  2. 2.Department of Applied InformaticsJosef Attila University SzegedSzegedHungary
  3. 3.Siemens Corporate Research Princeton Inc.Josef Attila University SzegedUSA

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