Literature DB >> 23261244

Patient specific CFD models of nasal airflow: overview of methods and challenges.

Sung Kyun Kim1, Yang Na, Jee-In Kim, Seung-Kyu Chung.   

Abstract

Respiratory physiology and pathology are strongly dependent on the airflow inside the nasal cavity. However, the nasal anatomy, which is characterized by complex airway channels and significant individual differences, is difficult to analyze. Thus, commonly adopted diagnostic tools have yielded limited success. Nevertheless, with the rapid advances in computer resources, there have been more elaborate attempts to correlate airflow characteristics in human nasal airways with the symptoms and functions of the nose by computational fluid dynamics study. Furthermore, the computed nasal geometry can be virtually modified to reflect predicted results of the proposed surgical technique. In this article, several computational fluid mechanics (CFD) issues on patient-specific three dimensional (3D) modeling of nasal cavity and clinical applications were reviewed in relation to the cases of deviated nasal septum (decision for surgery), turbinectomy, and maxillary sinus ventilation (simulated- and post-surgery). Clinical relevance of fluid mechanical parameters, such as nasal resistance, flow allocation, wall shear stress, heat/humidity/NO gas distributions, to the symptoms and surgical outcome were discussed. Absolute values of such parameters reported by many research groups were different each other due to individual difference of nasal anatomy, the methodology for 3D modeling and numerical grid, laminar/turbulent flow model in CFD code. But, the correlation of these parameters to symptoms and surgery outcome seems to be obvious in each research group with subject-specific models and its variations (virtual- and post-surgery models). For the more reliable, patient-specific, and objective tools for diagnosis and outcomes of nasal surgery by using CFD, the future challenges will be the standardizations on the methodology for creating 3D airway models and the CFD procedures.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23261244     DOI: 10.1016/j.jbiomech.2012.11.022

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  14 in total

1.  First Steps to Develop and Validate a CFPD Model in Order to Support the Design of Nose-to-Brain Delivered Biopharmaceuticals.

Authors:  Lucas Engelhardt; Martina Röhm; Chrystelle Mavoungou; Katharina Schindowski; Annette Schafmeister; Ulrich Simon
Journal:  Pharm Res       Date:  2016-02-17       Impact factor: 4.200

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

Authors:  Courtney Gaberino; John S Rhee; Guilherme J M Garcia
Journal:  Respir Physiol Neurobiol       Date:  2017-01-09       Impact factor: 1.931

3.  Quantification of nasal airflow resistance in English bulldogs using computed tomography and computational fluid dynamics.

Authors:  Eric T Hostnik; Brian A Scansen; Rachel Zielinski; Samir N Ghadiali
Journal:  Vet Radiol Ultrasound       Date:  2017-07-17       Impact factor: 1.363

4.  Flow and air conditioning simulations of computer turbinectomized nose models.

Authors:  J Pérez-Mota; F Solorio-Ordaz; J Cervantes-de Gortari
Journal:  Med Biol Eng Comput       Date:  2018-04-16       Impact factor: 2.602

5.  Changes in nasal airflow and heat transfer correlate with symptom improvement after surgery for nasal obstruction.

Authors:  J S Kimbell; D O Frank; Purushottam Laud; G J M Garcia; J S Rhee
Journal:  J Biomech       Date:  2013-08-26       Impact factor: 2.712

6.  A CFD approach to understand nasoseptal perforations.

Authors:  M A Burgos; E Sanmiguel-Rojas; R Rodríguez; F Esteban-Ortega
Journal:  Eur Arch Otorhinolaryngol       Date:  2018-07-24       Impact factor: 2.503

7.  A hierarchical stepwise approach to evaluate nasal patency after virtual surgery for nasal airway obstruction.

Authors:  Dennis O Frank-Ito; Julia S Kimbell; Azadeh A T Borojeni; Guilherme J M Garcia; John S Rhee
Journal:  Clin Biomech (Bristol, Avon)       Date:  2018-12-19       Impact factor: 2.063

8.  Intranasal Volume Changes Caused by the Endoscopic Endonasal Transsphenoidal Approach and Their Effects on Nasal Functions.

Authors:  Do Hyun Kim; Yong-Kil Hong; Sin-Soo Jeun; Yong Jin Park; Soo Whan Kim; Jin Hee Cho; Boo Young Kim; Sungwoo Han; Yong Joo Lee; Jae Hyung Hwang; Sung Won Kim
Journal:  PLoS One       Date:  2016-03-24       Impact factor: 3.240

9.  Investigation on the nasal airflow characteristics of anterior nasal cavity stenosis.

Authors:  T Wang; D Chen; P H Wang; J Chen; J Deng
Journal:  Braz J Med Biol Res       Date:  2016-08-01       Impact factor: 2.590

10.  A Method for Accurate Reconstructions of the Upper Airway Using Magnetic Resonance Images.

Authors:  Huahui Xiong; Xiaoqing Huang; Yong Li; Jianhong Li; Junfang Xian; Yaqi Huang
Journal:  PLoS One       Date:  2015-06-11       Impact factor: 3.240

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