THE DIGITAL NOSE: COMPUTATIONAL FLUID DYNAMICS AS A NEW TOOL FOR THE ASSESSMENT OF PHYSIOLOGICAL, PATHOLOGICAL AND VIRTUAL POST-SURGICAL NASAL AIR FLOW

Nasal stenosis is the most common symptom of a variety of nasal pathologies. In a large study of 4,611 patients with rhinosinusitis, 66 percent of patients exhibited nasal stenosis. In a separate study, it was found in 70% of 755 patients. Several conditions, including rhinosinusitis, nasal septal deviation, concha bullosa (middle turbinate pneumatization), and turbinate hypertrophy, can cause nasal obstruction. All of these factors are prevalent among the general population. For instance, the prevalence of nasal septal deviation in the general population ranges from 9.5% in children to 19.4% in adults, and in the study by Smith et al analyzing 883 CT scans, 67.5% of patients exhibited pneumatization of at least one concha. If medical treatment fails to alleviate nasal obstruction, surgery may be the only option, but the surgical plan is largely dependent on the surgeon's experience. Existing methods for assessing nasal flow are inaccurate and unable to determine which of the singles considered anatomical abnormalities has the greatest impact on nasal flow modification. Consequently, it should be addressed with greater vigour during surgery. This lack of information leads to the performance of numerous procedures for which we have, at best, only anecdotal evidence of additional success, but which unquestionably prolong surgical time, which has a direct effect on the number of hours spent in the operating room, potential complications, and costs. Our research aims to examine the application of a new tool, Computational Fluid Dynamics (CFD), in a variety of clinical settings. CFD is the branch of Fluids Mechanics that studies the behaviour of fluids in their environments and in relation to solids. In otorhinolaryngology, for instance, CFD can be utilized to examine airflow in the nose or upper airways. Our multidisciplinary team believes that in the future, CFD could be used on a daily basis, moving from the research field to the clinical field. In this thesis, I would like to demonstrate how CFD works and how it can be applied to the study of nasal airflow, both physiologically, pathologically, and surgically. All the examples presented in this thesis are performed on actual CT scans, simulating realistic respiratory conditions, with the future goal of bringing CFD from the computer to the patient's bed.

Grantor dc:publisher

Università degli Studi di Milano

Year dc:date

2022

Author dc:creator

• BULFAMANTE, ANTONIO MARIO

Contributors dc:contributor

• tutor: C. Pipolo ; coordinatore: M. Del Fabbro ; revisore: M. Quadrio
• M. Trimarchi
• A.M. Bulfamante
• PIPOLO, GIORGIA CARLOTTA
• DEL FABBRO, MASSIMO

• Computational Fluid Dynamic
• CFD
• Rhinology
• Otorhinolaryngology
• Settore MED/31 - Otorinolaringoiatria

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

eng

Identifier

http://dx.doi.org/10.13130/bulfamante-antonio-mario_phd2022-12-14
10.13130/bulfamante-antonio-mario_phd2022-12-14

OAI identifier oai:identifier

oai:air.unimi.it:2434/947852