Dataset Information

Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance.

ABSTRACT: Monitoring of nasal airflow and conductance provides crucial insights into the variable nature of the nasal resistance, nasal cycle, and ventilation. We have previously shown that tracking of pressure swings at the entrance of each nasal passage by a dedicated catheter system allows bilateral monitoring of nasal airflow over several hours but requires complex linearization and calibration procedures. Side-selective nasal conductance is derived from linearized and calibrated bilateral nasal pressure swings and corresponding driving pressure, i.e., the transnasal pressure difference derived from an epipharyngeal catheter. Manual analysis of such recordings and computation of instantaneous conductance as the ratio of flow to driving pressure over several hours is extremely tedious, time consuming, and therefore not suitable for routine practice. To address this point, we developed and validated a software for automatic processing of nasal and epipharyngeal pressure recordings as a convenient tool for studying the nasal ventilation. The software applies an eight-parameter logistic model to transform nasal pressure swings into side-selective estimates of airflow that are calibrated and further processed along with epipharyngeal pressure to compute bilateral nasal conductance over consecutive, user-selectable time-segments. Essential processing steps include (1) offset correction, (2) low-pass filtering, (3) cross-correlation, (4) cutting of signals into individual breaths, (5) normalization, (6) ensemble averaging to obtain a mean pressure signal for each nasal side, (7) derivation of airflow, conductance, and further variables. Among four evaluated algorithms for calculation of nasal conductance, the derivative of the airflow-pressure curve according to the mean value theorem agreed closest with the gold standard, i.e., the conductance derived from airflow measured by a pneumotachograph attached to an oral-nasal mask and transnasal pressure. In combination with the nasal catheter system, our novel software represents a valuable tool for use in clinical practice and research to conveniently investigate nasal ventilation and its changes occurring spontaneously or in response to various exposures and therapeutic interventions.

SUBMITTER: Urner LM

PROVIDER: S-EPMC6330336 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance.

Urner Lorenz M LM Kohler Malcolm M Bloch Konrad E KE

Frontiers in physiology 20190107

Monitoring of nasal airflow and conductance provides crucial insights into the variable nature of the nasal resistance, nasal cycle, and ventilation. We have previously shown that tracking of pressure swings at the entrance of each nasal passage by a dedicated catheter system allows bilateral monitoring of nasal airflow over several hours but requires complex linearization and calibration procedures. Side-selective nasal conductance is derived from linearized and calibrated bilateral nasal press ...[more]

PMID: 30666209

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Project description:PurposeVirtual surgery planning based on computational fluid dynamics (CFD) simulations of nasal airflow has the potential to improve surgical outcomes for patients with nasal airway obstruction (NAO). Virtual surgery planning requires normative ranges of airflow variables, but few studies to date have quantified inter-individual variability of nasal airflow among healthy subjects. This study reports CFD simulations of nasal airflow in 47 healthy adults.MethodsAnatomically accurate three-dimensional nasal models were reconstructed from cone beam computed tomography scans and used for steady-state inspiratory airflow simulations with a bilateral flowrate of 250 ml/s. Normal subjective sensation of nasal patency was confirmed using the nasal obstruction symptom evaluation and visual analog scale. Healthy ranges for several CFD variables known to correlate with subjective nasal patency were computed, including unilateral airflow, nasal resistance, airspace minimal cross-sectional area (mCSA), heat flux (HF), and surface area stimulated by mucosal cooling (defined as the area where HF > 50 W/m2). The normative ranges were targeted to contain 95% of the healthy population and computed using a nonparametric method based on order statistics.ResultsA wide range of inter-individual variability in nasal airflow was observed among healthy subjects. Unilateral airflow varied from 60 to 191 ml/s, airflow partitioning ranged from 23.8 to 76.2%, and unilateral mCSA varied from 0.24 to 1.21 cm2. These ranges are in good agreement with rhinomanometry and acoustic rhinometry data from the literature. A key innovation of this study are the normative ranges of flow variables associated with mucosal cooling, which recent research suggests is the primary physiological mechanism of nasal airflow sensation. Unilateral HF ranged from 94 to 281 W/m2, while the surface area stimulated by cooling ranged from 27.4 to 64.3 cm2.ConclusionsThese normative ranges may serve as targets in future virtual surgery planning for patients with NAO.

Dataset Information

Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance.

Publications

Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance.

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