Literature DB >> 28089607

Estimates of nasal airflow at the nasal cycle mid-point improve the correlation between objective and subjective measures of nasal patency.

Courtney Gaberino1, John S Rhee2, Guilherme J M Garcia3.   

Abstract

INTRODUCTION: The nasal cycle represents a significant challenge when comparing pre- and post-surgery objective measures of nasal airflow.
METHODS: Computational fluid dynamics (CFD) simulations of nasal airflow were conducted in 12 nasal airway obstruction patients showing significant nasal cycling between pre- and post-surgery computed tomography scans. To correct for the nasal cycle, mid-cycle models were created virtually. Subjective scores of nasal patency were obtained via the Nasal Obstruction Symptom Evaluation (NOSE) and unilateral visual analog scale (VAS).
RESULTS: The correlation between objective and subjective measures of nasal patency increased after correcting for the nasal cycle. In contrast to biophysical variables in individual patients, cohort averages were not significantly affected by the nasal cycle correction.
CONCLUSIONS: The ability to correct for the confounding effect of the nasal cycle is a key element that future virtual surgery planning software for nasal airway obstruction will need to account for when using anatomic models based on single instantaneous imaging. Copyright Â
© 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Computational fluid dynamics (CFD) simulations; Mucosal cooling; Nasal airway obstruction; Nasal cycle correction; Nasal resistance; Virtual surgery planning

Mesh:

Year:  2017        PMID: 28089607      PMCID: PMC5316304          DOI: 10.1016/j.resp.2017.01.004

Source DB:  PubMed          Journal:  Respir Physiol Neurobiol        ISSN: 1569-9048            Impact factor:   1.931


  45 in total

1.  Development and validation of the Nasal Obstruction Symptom Evaluation (NOSE) scale.

Authors:  Michael G Stewart; David L Witsell; Timothy L Smith; Edward M Weaver; Bevan Yueh; Maureen T Hannley
Journal:  Otolaryngol Head Neck Surg       Date:  2004-02       Impact factor: 3.497

2.  Septal deviation and nasal resistance: an investigation using virtual surgery and computational fluid dynamics.

Authors:  Guilherme J M Garcia; John S Rhee; Brent A Senior; Julia S Kimbell
Journal:  Am J Rhinol Allergy       Date:  2010 Jan-Feb       Impact factor: 2.467

Review 3.  Correlation between subjective and objective evaluation of the nasal airway. A systematic review of the highest level of evidence.

Authors:  R F André; H D Vuyk; A Ahmed; K Graamans; G J Nolst Trenité
Journal:  Clin Otolaryngol       Date:  2009-12       Impact factor: 2.597

4.  Experimental measurements and computational predictions of regional particle deposition in a sectional nasal model.

Authors:  Jeffry D Schroeter; Earl W Tewksbury; Brian A Wong; Julia S Kimbell
Journal:  J Aerosol Med Pulm Drug Deliv       Date:  2014-02-28       Impact factor: 2.849

5.  Assessment of airflow ventilation in human nasal cavity and maxillary sinus before and after targeted sinonasal surgery: a numerical case study.

Authors:  Jian Hua Zhu; Kian Meng Lim; Kim Thye Mark Thong; De Yun Wang; Heow Pueh Lee
Journal:  Respir Physiol Neurobiol       Date:  2014-01-10       Impact factor: 1.931

6.  The relationship between nasal resistance to airflow and the airspace minimal cross-sectional area.

Authors:  Guilherme J M Garcia; Benjamin M Hariri; Ruchin G Patel; John S Rhee
Journal:  J Biomech       Date:  2016-04-01       Impact factor: 2.712

7.  Olfactory deposition of inhaled nanoparticles in humans.

Authors:  Guilherme J M Garcia; Jeffry D Schroeter; Julia S Kimbell
Journal:  Inhal Toxicol       Date:  2015-07-21       Impact factor: 2.724

8.  Atrophic rhinitis: a CFD study of air conditioning in the nasal cavity.

Authors:  Guilherme J M Garcia; Neil Bailie; Dário A Martins; Julia S Kimbell
Journal:  J Appl Physiol (1985)       Date:  2007-06-14

9.  Predicting postsurgery nasal physiology with computational modeling: current challenges and limitations.

Authors:  Dennis O Frank-Ito; Julia S Kimbell; Purushottam Laud; Guilherme J M Garcia; John S Rhee
Journal:  Otolaryngol Head Neck Surg       Date:  2014-08-28       Impact factor: 3.497

Review 10.  The physiological mechanism for sensing nasal airflow: a literature review.

Authors:  Jeanie Sozansky; Steven M Houser
Journal:  Int Forum Allergy Rhinol       Date:  2014-07-30       Impact factor: 3.858

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  5 in total

1.  Normative ranges of nasal airflow variables in healthy adults.

Authors:  Azadeh A T Borojeni; Guilherme J M Garcia; Masoud Gh Moghaddam; Dennis O Frank-Ito; Julia S Kimbell; Purushottam W Laud; Lisa J Koenig; John S Rhee
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-07-02       Impact factor: 2.924

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

Authors:  Masoud Gh Moghaddam; Guilherme J M Garcia; Dennis O Frank-Ito; Julia S Kimbell; John S Rhee
Journal:  Int J Comput Assist Radiol Surg       Date:  2020-02-20       Impact factor: 2.924

3.  Virtual Surgery for the Nasal Airway: A Preliminary Report on Decision Support and Technology Acceptance.

Authors:  Derek L Vanhille; Guilherme J M Garcia; Onur Asan; Azadeh A T Borojeni; Dennis O Frank-Ito; Julia S Kimbell; Sachin S Pawar; John S Rhee
Journal:  JAMA Facial Plast Surg       Date:  2018-01-01       Impact factor: 4.611

4.  Sensitivity of nasal airflow variables computed via computational fluid dynamics to the computed tomography segmentation threshold.

Authors:  Giancarlo B Cherobin; Richard L Voegels; Eloisa M M S Gebrim; Guilherme J M Garcia
Journal:  PLoS One       Date:  2018-11-16       Impact factor: 3.240

5.  Three-dimensional modeling and automatic analysis of the human nasal cavity and paranasal sinuses using the computational fluid dynamics method.

Authors:  Dmitry Tretiakow; Krzysztof Tesch; Jarosław Meyer-Szary; Karolina Markiet; Andrzej Skorek
Journal:  Eur Arch Otorhinolaryngol       Date:  2020-10-17       Impact factor: 2.503

  5 in total

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