Michael D. Goldman

Clinical applications of forced oscillation to assess peripheral airway function

Forced oscillation applies external pressures to the respiratory system to measure respiratory impedance. Impedance of larger central airways may be dissected from that of peripheral airways using multiple oscillation frequencies. Respiratory impedance is calculated by computer-assisted methods that yield separate resistive and reactive components. The reactive component includes respiratory system capacitative and inertive properties, which may be separately visualized for clinical purposes using resonance as a rough dividing line. Low oscillation frequencies comprise those below resonance, and relate most prominently to capacitative properties of peripheral airways. High oscillation frequencies comprise those greater than resonance, which relate most prominently to inertial properties of larger central airways. Measurements of resistance and reactance in patients with peripheral airway disease, before and after therapeutic intervention, manifest characteristic patterns of response in low frequency resistance and reactance measures that appear to be closely correlated with each other. In contrast, changes in large central airways manifest resistance change uniformly over low and high frequencies.

Inert Gas Washout: Theoretical Background and Clinical Utility in Respiratory Disease

Inert gas washout was first described more than 60 years ago and 2 principal tests have been developed from it: the single breath and multiple breath washout (MBW) techniques. The invention of fast responding gas analysers almost 60 years ago and small computers 30 years later have facilitated breath-by-breath analysis and the development of sophisticated analysis techniques. It is now possible to detect not only the degree of pulmonary ventilation inhomogeneity, but also to gain important insight into the location of the underlying disease process. While single breath washout requires a full vital capacity effort, tidal breathing during the multiple breath test requires minimal co-operation and co-ordination, and is feasible in subjects of all ages. Available MBW normative data from parameters, such as the lung clearance index, appears to vary minimally with age, making MBW particularly useful to follow children longitudinally. Multiple breath inert gas washout has demonstrated improved sensitivity, in comparison to spirometry, in the early detection of a number of important disease processes, including cystic fibrosis. Despite this, these important techniques remain under-utilised in the clinical setting and there is a lack of commercially available devices currently available. The recent resurgence of research in this area has produced a large number of important studies and a pronounced international interest has developed in these techniques. This review article will provide an overview of the theoretical background of inert gas washout and analysis indices, review important physiological and clinical insights gained from research to date (as well as from our own experience) to illustrate its utility, and outline the challenges that lie ahead in incorporating these techniques into the mainstream clinical setting.

Can asthma in children be detected by the estimated parameter values of the augmented RIC model

This paper describes the estimation of the parameter values for the recently introduced augmented RIC respiratory system model from impulse oscillometry data obtained from both asthmatic and normal children. An analysis of these values has indicated that one of the capacitance parameters of the model provides good discrimination between these two groups of children; moreover, this finding corresponds well with current medical understanding of the pathology of asthma

A Comparison of Various Respiratory System Models Based on Parameter Estimates From Impulse Oscillometry Data

Impulse oscillometry offers an advantage over spirometry when conducting pulmonary function tests. Not only does it require minimal patient cooperation, it provides useful data in a form amenable to engineering methods. In particular, the data can be used to obtain parameter estimates for electric circuit-based models of the respiratory system, which can in turn aid the detection and diagnosis of various diseases/pathologies. Of the six models analyzed during this study, the DuBois model and a newly proposed extended RIC model seem to provide the most robust parameter estimates for our entire data set of 106 subjects with various respiratory ailments such as asthma and chronic obstructive pulmonary disease. Such a diagnostic approach, relying on estimated parameter values, may require additional measures to ensure proper identification of diseases/pathologies but the preliminary results are promising.

Respiratory Impedance Values in Adults Are Relatively Insensitive to Mead Model Lung Compliance and Chest Wall Compliance Parameters

Impulse Oscillometry (IOS) measures respiratory resistance and reactance from 5 to 35 Hz. These data were obtained from 2 groups of adults enrolled in a study of IOS compared to other lung function testing methods: 1 group of 10 adults with no identifiable respiratory disease and 1 group of 10 adults with varying degrees of COPD. We used Mead’s model of the respiratory system to derive parameter estimates of central inertance (I), central and peripheral resistances (R c , R p ), and lung, chest wall, bronchial, and extrathoracic compliances (C l , C w , C b , C e ) by least-squares-optimal fitting to the IOS data. This procedure typically produced multiple optimal solutions, with estimates ofC l and ofC w that varied by 2 to 3 orders of magnitude and were several orders of magnitude larger than expected physiological values, up to 8.6x105 L/kPa for C l and 2.6x105 L/kPa for C w . We then performed constrained optimization of normal adult data with both C l and C w parameters fixed at 2 L/kPa, which produced a group-averaged LS error that was 19.3% larger than for unconstrained optimization: R c , I, R p , C b and C e parameters changed by 0.99%, 1.76%, 22.0%, 11.9% and 10.6%, respectively. Constrained optimization of the COPD adults data with the C w fixed at 2 L/kPa and C l fixed first at 1.5 L/kPa and then at 1.1 L/kPa produced group-averaged LS errors that were 23.8% larger and 23.6% larger, respectively, than for unconstrained optimization: R c , I, R p , C b and C e parameters changed by 2.12%, 4.88%, 18.5%, 6.46% and 25.5%, respectively, for C l = 1.5 L/kPa; they changed by 1.64%, 4.30%, 18.4%, 6.64% and 18.5%, respectively, for C l = 1.1 L/kPa, all relative to the unconstrained case. We conclude that the Mead model’s impedance and its parameter estimates for normal and COPD adults are relatively insensitive to the C l and C w parameters.

Evaluation of Respiratory System Models Based on Parameter Estimates from Impulse Oscillometry Data

Impulse oscillometry offers advantages over spirometry because it requires minimal patient cooperation, it yields pulmonary function data in a form that is readily amenable to engineering analysis. In particular, the data can be used to obtain parameter estimates for electric circuit-based models of the respiratory system, which in turn may assist the detection and diagnosis of various diseases/pathologies. Of the six models analyzed during this study, Meads model seems to provide the most robust and accurate parameter estimates for our data set of 5 subjects with airflow obstruction including asthma and chronic obstructive pulmonary disease and another 5 normal subjects with no identifiable respiratory disease. Such a diagnostic approach, relying on estimated parameter values from a respiratory system model estimate and the degree of their deviation from the normal range, may require additional measures to ensure proper identification of diseases/pathologies but the preliminary results are promising

Impulse oscillometric features of lung function: Towards computer-aided classification of respiratory diseases in children

Asthma is the most prevalent chronic respiratory disease in children. Reliable and patient-friendly instruments and methods are required to help pulmonologists accurately detect asthma with acceptable clinical accuracy, specificity and sensitivity. Impulse Oscillometry System (IOS) based on the Forced Oscillation Technique (FOT) has been successfully used to measure lung function in children with a high degree of sensitivity and specificity to small airway dysfunction (SAD). IOS measures the mechanical impedance of the respiratory system. Equivalent electrical circuit models of lung function have been developed that can be used to quantify severity of SAD. It has been shown that impulse oscillometric parameters as well as parameter estimates of these electrical models provide useful indicators of lung function and therefore have the potential to be used as sensitive features for computer-aided classification of pulmonary function in health and disease.

Electrical circuit models of the human respiratory system reflect small airway impairment measured by impulse oscillation (IOS)

The use of the forced oscillatory input impedance parameter, frequency-dependence of Resistance (fdR), to assess small airway impairment (SAI) has not been widely accepted due to concern about the effects of “upper airway shunt” on oscillometric resistance and low frequency reactance. On the other hand, recent medical studies suggest that low frequency reactance is a very sensitive index of treatment intervention directed at small airways. The present study was undertaken to analyze and compare Impulse Oscillometry (IOS) resistance and reactance data with model-derived indices of small airway function from two models of the respiratory impedance, one with, and the other without an element for upper airway shunt capacitance. Fifty six patients with stable chronic obstructive lung disease of varying severity due to Cystic Fibrosis (CF) and 21 patients with asthma were evaluated by IOS testing. IOS data were input into the augmented RIC (aRIC) model with an upper airway shunt capacitance, and the extended RIC (eRIC) model, without a shunt capacitance element. Model-derived indices were compared between the two models for CF patients separately from asthma patients. We conclude that IOS indices of SAI are modeled equally well with or without upper airway shunt capacitance, and do not seem to be dependent on upper airway shunt capacitance.

Classification of Impulse Oscillometric Patterns of Lung Function in Asthmatic Children using Artificial Neural Networks

Impulse oscillometry (IOS) is an innovative patient-friendly pulmonary testing technique which measures the respiratory system impedance (Z) by using the spectral components of pressure to flow ratio which yields resistance and reactance values at different frequencies. The high dimensionality of IOS measurement data makes the analysis of this information difficult. Artificial neural networks (ANNs) are mathematical models composed of a large number of highly interconnected neurons that are able to learn and generalize from data. An ANN-based approach to the analysis of IOS data can potentially provide an efficient and automatic method to recognize and classify pulmonary diseases. This would help characterize major respiratory illnesses such as asthma based on IOS measurements. Asthma can be difficult to diagnose, because the symptoms are sometimes similar to other lung conditions. A data set composed of 361 impulse oscillometric patterns from asthmatic children was used in this study. The ANN was capable of distinguishing between relatively constricted and nonconstricted airway conditions in these patients. Using all of the 361 patterns during training as well as in the feed-forward stage, a classification accuracy of 95.01% was obtained for validation. When the ANN was presented with only 60% of the original 361 patterns in the data set during training and with the remaining 40% as unseen patterns, the generalization stage, a classification accuracy of 98.61% was achieved. These results show that ANNs can successfully be trained with the IOS data, enabling them to generalize the IOS parameter relationships to classify previously unseen pulmonary patterns, such as in asthma. The next step is to obtain expert rules by extracting them from the knowledge acquired by the neural network and develop a fully automated classification system to aid physicians in classifying and characterizing pulmonary diseases based on the patient-friendly IOS measurements

Use of thoracic impedance sensors to screen for sleep-disordered breathing in patients with cardiovascular disease

Screening patients for the possibility of sleep apnoea, one of the most common forms of sleep-disordered breathing, requires measurement of respiration. We propose a simple method to estimate the amplitude modulation of a respiratory tidal volume, using a semi-quantitative measure of respiration based on thoracic impedance (TI). Because respiratory volume changes may be accommodated by varying displacements of the rib cage (RC) and abdomen (AB), the latter produced by outward motion of the diaphragm, it is necessary for any useful measure of respiration to be closely related to both RC and AB displacements. Because the relative contributions of RC and AB displacements to respiratory tidal volume vary in different body positions, the present measurements were recorded from subjects in supine, and right and left lateral decubitus postures. We observed a clear linear relationship between TI and both RC and AB signals in all three body positions. There were no statistically significant differences between observed relationships between TI and AB and between TI and RC, and these relationships were independent of the body position. TI sensors appear to be a useful candidate for a simple method of screening for sleep apnoea, especially in a cardiology clinical setting. Further investigation is warranted for the refinement of algorithms to detect changes in amplitude modulation occurring with apnoeas and to remove artefacts due to gross body movements.