A new segmentation algorithm for measuring CBCT images of nasal airway: a pilot study.
Publication year
2019Source
PeerJ, 7, (2019), pp. e6246, article e6246ISSN
Publication type
Article / Letter to editor

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Organization
Dentistry
Oral and Maxillofacial Surgery
Journal title
PeerJ
Volume
vol. 7
Page start
p. e6246
Subject
Radboudumc 10: Reconstructive and regenerative medicine RIHS: Radboud Institute for Health SciencesAbstract
Background: Three-dimensional (3D) modeling of the nasal airway space is becoming increasingly important for assessment in breathing disorders. Processing cone beam computed tomography (CBCT) scans of this region is complicated, however, by the intricate anatomy of the sinuses compared to the simpler nasopharynx. A gold standard for these measures also is lacking. Previous work has shown that software programs can vary in accuracy and reproducibility outcomes of these measurements. This study reports the reproducibility and accuracy of an algorithm, airway segmentor (AS), designed for nasal airway space analysis using a 3D printed anthropomorphic nasal airway model. Methods: To test reproducibility, two examiners independently used AS to edit and segment 10 nasal airway CBCT scans. The intra- and inter-examiner reproducibility of the nasal airway volume was evaluated using paired t-tests and intraclass correlation coefficients. For accuracy testing, the CBCT data for pairs of nasal cavities were 3D printed to form hollow shell models. The water-equivalent method was used to calculate the inner volume as the gold standard, and the models were then embedded into a dry human skull as a phantom and subjected to CBCT. AS, along with the software programs MIMICS 19.0 and INVIVO 5, was applied to calculate the inner volume of the models from the CBCT scan of the phantom. The accuracy was reported as a percentage of the gold standard. Results: The intra-examiner reproducibility was high, and the inter-examiner reproducibility was clinically acceptable. AS and MIMICS presented accurate volume calculations, while INVIVO 5 significantly overestimated the mockup of the nasal airway volume. Conclusion: With the aid of a 3D printing technique, the new algorithm AS was found to be a clinically reliable and accurate tool for the segmentation and reconstruction of the nasal airway space.
This item appears in the following Collection(s)
- Academic publications [227425]
- Electronic publications [107155]
- Faculty of Medical Sciences [86157]
- Open Access publications [76288]
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