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Virtual septoplasty: a method to predict surgical outcomes for patients with nasal airway obstruction

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

A deviated nasal septum is the most common etiology for nasal airway obstruction (NAO), and septoplasty is the most common surgical procedure performed by ear–nose–throat surgeons in adults. However, quantitative criteria are rarely adopted to select patients for surgery, which may explain why up to 50% of patients report persistent or recurrent symptoms of nasal obstruction postoperatively. This study reports a systematic virtual surgery method to identify patients who may benefit from septoplasty.

Methods

One patient with symptoms of NAO due to a septal deviation was selected to illustrate the virtual surgery concept. Virtual septoplasty was implemented in three steps: (1) determining if septal geometry is abnormal preoperatively, (2) virtually correcting the deviation while preserving the anatomical shape of the septum, and (3) estimating the post-surgical improvement in airflow using computational fluid dynamics. Anatomical and functional changes predicted by the virtual surgery method were compared to a standard septoplasty performed independently from the computational analysis.

Results

A benchmark healthy nasal septum geometry was obtained by averaging the septum dimensions of 47 healthy individuals. A comparison of the nasal septum geometry in the NAO patient with the benchmark geometry identified the precise locations where septal deviation and thickness exceeded the healthy range. Good agreement was found between the virtual surgery predictions and the actual surgical outcomes for both airspace minimal cross-sectional area (0.05 cm2 pre-surgery, 0.54 cm2 virtual surgery, 0.50 cm2 actual surgery) and nasal resistance (0.91 Pa.s/ml pre-surgery, 0.08 Pa.s/ml virtual surgery, 0.08 Pa.s/ml actual surgery).

Conclusions

Previous virtual surgery methods for NAO were based on manual edits and subjective criteria. The virtual septoplasty method proposed in this study is objective and has the potential to be fully automated. Future implementation of this method in virtual surgery planning software has the potential to improve septoplasty outcomes.

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Funding

This study was funded by Grant R01EB009557 from the National Institutes of Health/National Institute of Biomedical Imaging and Bioengineering to the Medical College of Wisconsin (MCW) and by subcontract from MCW to the University of North Carolina at Chapel Hill and Duke University.

Author information

Author notes

  1. Masoud Gh. Moghaddam and Guilherme J. M. Garcia have contributed equally to this paper.

Authors and Affiliations

  1. Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee, WI, USA

    Masoud Gh. Moghaddam, Guilherme J. M. Garcia & John S. Rhee

  2. Joint Department of Biomedical Engineering, Marquette University and The Medical College of Wisconsin, Milwaukee, WI, USA

    Masoud Gh. Moghaddam & Guilherme J. M. Garcia

  3. Department of Head and Neck Surgery and Communication Sciences, Duke University Medical Center, Durham, NC, USA

    Dennis O. Frank-Ito

  4. Computational Biology and Bioinformatics Program, Duke University, Durham, NC, USA

    Dennis O. Frank-Ito

  5. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA

    Dennis O. Frank-Ito

  6. Department of Otolaryngology/Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA

    Julia S. Kimbell

Authors
  1. Masoud Gh. Moghaddam
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  2. Guilherme J. M. Garcia
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Corresponding author

Correspondence to Guilherme J. M. Garcia.

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All procedures were performed in accordance with the ethical standards of the institutional review boards at The Medical College of Wisconsin and Marquette University and of the 1964 Helsinki Declaration and its later amendments.

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Informed consent was obtained from all individual participants included in the study.

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Moghaddam, M.G., Garcia, G.J.M., Frank-Ito, D.O. et al. Virtual septoplasty: a method to predict surgical outcomes for patients with nasal airway obstruction. Int J CARS 15, 725–735 (2020). https://doi.org/10.1007/s11548-020-02124-z

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