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International Journal of Computer Assisted Radiology and Surgery

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27-11-2021 | Original Article

Toward automatic atlas-based surgical planning for septoplasty

Authors: Jared Vicory, Guilherme J. M. Garcia, John S. Rhee, Andinet Enquobahrie

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 2/2022

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Abstract

Purpose

Surgery for nasal airway obstruction (NAO) has a high failure rate, with up to 50% of patients reporting persistent symptoms postoperatively. Virtual surgery planning has the potential to improve surgical outcomes, but current manual methods are too labor-intensive to be adopted on a large scale. This manuscript introduces an automatic atlas-based approach for performing virtual septoplasties.

Methods

A cohort of 47 healthy subjects and 26 NAO patients was investigated. An atlas of healthy nasal geometry was constructed. The automatic virtual septoplasty method consists of a multi-stage registration approach to fit the atlas to a target NAO patient, automatically segment the patient’s septum and airway, and deform the patient image to have a non-deviated septum.

Results

Our automatic virtual septoplasty method straightened the septum successfully in 18 out of 26 NAO patients (69% of cases). In these cases, the ratio of the higher to the lower airspace cross-sectional areas in the left and right nasal cavities improved from 1.47 ± 0.45 to 1.16 ± 0.33 in the region surrounding the septal deviation, showing that the nasal airway became more symmetric after virtual septoplasty.

Conclusion

This automated virtual septoplasty technique has the potential to greatly reduce the effort required to perform computational fluid dynamics (CFD) analysis of nasal airflow for NAO surgical planning. Future studies are needed to investigate if virtual surgery planning using this method is predictive of subjective symptoms in NAO patients after septoplasty.

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Title: Toward automatic atlas-based surgical planning for septoplasty
Authors: Jared Vicory
Guilherme J. M. Garcia
John S. Rhee
Andinet Enquobahrie
Publication date: 27-11-2021
Publisher: Springer International Publishing
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 2/2022
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-021-02524-9

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Abstract

Purpose

Methods

Results

Conclusion

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