Virtual laryngoscopy: a noninvasive tool for the assessment of laryngeal tumor extent.
OBJECTIVE
Present a clinical application of virtual laryngoscopy (VL) in the assessment of laryngeal tumor and its extent.


METHODS
CT data from two subjects are acquired for this preliminary study. One subject is a healthy volunteer and the other is a patient with laryngeal tumor. The laryngeal framework and upper airway are reconstructed using CT data, which allows for computer-aided internal and external anatomical views and interactive fly-through.


METHODS
These CT data are reconstructed into 0.5 mm slice images, resulting in a total of 200-300 image slices. An advanced commercial visualization software (AMIRA) is used for 3D image segmentation, reconstruction and surface rendering of laryngeal anatomical structures.


RESULTS
The 3D laryngeal framework and upper airway are reconstructed for both the tumor patient and the healthy subject. The conventional views of the reconstructed vocal folds are compared with those obtained from fiber-optic laryngoscope. Additionally, unique views of the vocal folds obtained from retrograde visualization and fly-through are presented, which are not possible to obtain using conventional endoscope imaging. The segmented anatomical model and the tumor from the patient's CT images were displayed individually to show the distribution of the tumor and its extent as well as spatial and contextual relationships to the larynx and airway anatomical structures.


CONCLUSIONS
This study demonstrated the potential application of VL as a noninvasive clinical diagnostic tool for the assessment of laryngeal tumor and its extent. Our preliminary results demonstrated that the VL may provide valuable insights for the diagnosis and treatment planning for laryngeal and airway tumors. The noninvasive VL may complement the invasive laryngoscopic examinations for the staging of tumors and follow-ups on surgical interventions.
Yan
Yuling
Y
Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA. yyan@ohns.stanford.edu
Luo
Shouhua
S
McWhorter
Andrew
A
D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007822:Laryngeal Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery*; D007828:Laryngoscopy / Q000379:methods*; D009361:Neoplasm Invasiveness / Q000000981:diagnostic imaging / Q000473:pathology; D014057:Tomography, X-Ray Computed; D014584:User-Computer Interface; D014827:Vocal Cords / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery