Parametric models for characterizing respiratory input impedance

AVATREE: An open-source computational modelling framework modelling Anatomically Valid Airway TREE conformations

This paper presents AVATREE, a computational modelling framework that generates Anatomically Valid Airway tree conformations and provides capabilities for simulation of broncho-constriction apparent in obstructive pulmonary conditions. Such conformations are obtained from the personalized 3D geometry generated from computed tomography (CT) data through image segmentation. The patient-specific representation of the bronchial tree structure is extended beyond the visible airway generation depth using a knowledge-based technique built from morphometric studies. Additional functionalities of AVATREE include visualization of spatial probability maps for the airway generations projected on the CT imaging data, and visualization of the airway tree based on local structure properties. Furthermore, the proposed toolbox supports the simulation of broncho-constriction apparent in pulmonary diseases, such as chronic obstructive pulmonary disease (COPD) and asthma. AVATREE is provided as an open-source toolbox in C++ and is supported by a graphical user interface integrating the modelling functionalities. It can be exploited in studies of gas flow, gas mixing, ventilation patterns and particle deposition in the pulmonary system, with the aim to improve clinical decision making.

Association of respiratory integer and fractional-order models with structural abnormalities in silicosis

BACKGROUND AND OBJECTIVE

Integer and fractional-order models have emerged as powerful methods for obtaining information regarding the anatomical or pathophysiological changes that occur during respiratory diseases. However, the precise interpretation of the model parameters in light of the lung structural changes is not known. This study analyzed the associations of the integer and fractional-order models with structural changes obtained using multidetector computed tomography densitometry (MDCT) and pulmonary function analysis.

METHODS

Integer and fractional-order models were adjusted to data obtained using the forced oscillation technique (FOT). The results obtained in controls (n = 20) were compared with those obtained in patients with silicosis (n = 32), who were submitted to spirometry, body plethysmograph, FOT, diffusing capacity of the lungs for carbon monoxide (DLCO), and MDCT. The diagnostic accuracy was also investigated using ROC analysis.

RESULTS

The observed changes in the integer and fractional-order models were consistent with the pathophysiology of silicosis. The integer-order model showed association only between inertance and the non-aerated compartment (R = -0.69). This parameter also presented the highest associations with spirometry (R = 0.81), plethysmography (-0.61) and pulmonary diffusion (R = 0.53). Considering the fractional-order model, the increase in the poorly aerated and non-aerated regions presented direct correlations with the fractional inertance (R = 0.48), respiratory damping (R = 0.37) and hysteresivity (R = 0.54) and inverse associations with its fractional exponent (R = -0.62) and elastance (-0.35). Significant associations were also observed with spirometry (R = 0.63), plethysmography (0.37) and pulmonary diffusion (R = 0.51). Receiver operator characteristic analysis showed a higher accuracy in the FrOr model (0.908) than the eRIC model (0.789).

CONCLUSIONS

Our study has shown clear associations of the integer and fractional-order parameters with anatomical changes obtained via MDCT and pulmonary function measurements. These findings help to elucidate the physiological interpretation of the integer and fractional-order parameters and provide evidence that these parameters are reflective of the abnormal changes in silicosis. We also observed that the fractional-order model showed smaller curve-fitting errors, which resulted in a higher diagnostic accuracy than that of the eRIC model. Taken together, these results provide strong motivation for further studies exploring the clinical and scientific use of these models in respiratory medicine.

Forced oscillations and respiratory system modeling in adults with cystic fibrosis

Background

The Forced Oscillation Technique (FOT) has the potential to increase our knowledge about the biomechanical changes that occur in Cystic Fibrosis (CF). Thus, the aims of this study were to investigate changes in the resistive and reactive properties of the respiratory systems of adults with CF.

Methods

The study was conducted in a group of 27 adults with CF over 18 years old and a control group of 23 healthy individuals, both of which were assessed by the FOT, plethysmography and spirometry. An equivalent electrical circuit model was also used to quantify biomechanical changes and to gain physiological insight.

Results and discussion

The CF adults presented an increased total respiratory resistance (p < 0.0001), increased resistance curve slope (p < 0.0006) and reduced dynamic compliance (p < 0.0001). In close agreement with the physiology of CF, the model analysis showed increased peripheral resistance (p < 0.0005) and reduced compliance (p < 0.0004) and inertance (p < 0.005). Significant reasonable to good correlations were observed between the resistive parameters and spirometric and plethysmographic indexes. Similar associations were observed for the reactive parameters. Peripheral resistance, obtained by the model analysis, presented reasonable (R = 0.35) to good (R = 0.64) relationships with plethysmographic parameters.

Conclusions

The FOT adequately assessed the biomechanical changes associated with CF. The model used provides sensitive indicators of lung function and has the capacity to differentiate between obstructed and non-obstructed airway conditions. The FOT shows great potential for the clinical assessment of respiratory mechanics in adults with CF.

A recurrent parameter model to characterize the high-frequency range of respiratory impedance in healthy subjects

In this work, a re-visited model of the respiratory system is proposed. Identification of a recurrent electrical ladder network model of the lungs, which incorporates their specific morphology and anatomical structure, is performed on 31 healthy subjects. The data for identification has been gathered using the forced oscillation lung function test, which delivers a non-parametric model of the impedance. On the measured frequency response, the ladder network parameters have been identified and a fractional order has been calculated from the recurrent ratios of the respiratory mechanics (resistance and compliance). The paper includes also a comparison of our recurrent parameter model with another parametric model for high frequency range. The results suggest that the two models can equally well characterize the respiratory impedance over a long range of frequencies. Additionally, we have shown that the fractional order resulting from the recurrent properties of resistance and compliance in the ladder network model is independent of frequency and is not biased by the nose clip wore by the patients during measurements. An illustrative example shows that our re-visited model is sensitive to changes in respiratory mechanics and the fractional order value is a reliable parameter to capture these changes.

Computer assessment of indirect insight during an airflow interrupter maneuver of breathing

The paper answers the questions if it is possible to conclude in objective way on more (than one -Rint - in a classical IT) number of parameters from the time domain post-interrupter signals during the occlusional measurement of respiratory mechanics and also verifies what accuracy can be achieved in such attempt. To obtain reported results, the time-domain enhanced interrupter technique (TD-EIT) was developed in this paper using computer simulations. Three-stage scheme of work was assumed in the project. First, the quality of the model identification was assessed for various combinations of pressure and flow signals recorded during the interruption. Then, the correlation between the working characteristics of the interrupter valve and the precision of the parameter estimation were assessed for the TD-EIT algorithm. Finally, a verification experiment by forward-inverse modeling was organized, in which the mechanical characteristics of a complex model were mapped with reduced analogs and with the use of neural networks for three typical modes: 'Normal state', 'Airway constriction' and 'Cheeks supported'. Obtained results show that to became effective in time-domain post-interrupter data exploration, both pressure and flow signals should be used in assessment of respiratory mechanics, taken in a range of at least 100ms and when both slopes (valve closing and opening) of quasi-step excitation are included. What is more, the faster the valve the smaller error of parameter estimation in proposed TD-EIT was observed, and this uncertainty importantly falls down for the length of time window exceeding the limit of 100ms. The pioneering use of neural network for mapping the mechanical properties of lungs with the use of interrupter experiment methodology proves that it is possible to conclude about more (than one) number of parameters characterizing the complex system and that this insight is biased with the error not exceeding of 10%; only peripheral properties are estimated worse. Such observation has a potential to change the experimental protocol, which was used in interrupter measurements up to date and to make this technique more attractive in comparison to other method, i.e. forced oscillation technique or impulse oscillometry. As regards the practical meaning of reported results for engineers and end-users (physicians and patients), proposed solution can be applied in simple portable devices with a feature of easy operation (important for e-monitoring).

Is multidimensional scaling suitable for mapping the input respiratory impedance in subjects and patients?

This paper presents the application of multidimensional scaling (MDS) analysis to data emerging from noninvasive lung function tests, namely the input respiratory impedance. The aim is to obtain a geometrical mapping of the diseases in a 3D space representation, allowing analysis of (dis)similarities between subjects within the same pathology groups, as well as between the various groups. The adult patient groups investigated were healthy, diagnosed chronic obstructive pulmonary disease (COPD) and diagnosed kyphoscoliosis, respectively. The children patient groups were healthy, asthma and cystic fibrosis. The results suggest that MDS can be successfully employed for mapping purposes of restrictive (kyphoscoliosis) and obstructive (COPD) pathologies. Hence, MDS tools can be further examined to define clear limits between pools of patients for clinical classification, and used as a training aid for medical traineeship.

Adaptive control of a pressure-controlled artificial ventilator: a simulator-based evaluation using real COPD patient data

The paper discusses the application of a direct adaptive controller to a pressure controlled artificial ventilation problem. In pressure controlled ventilators, the manipulated variable is the maximum flow applied to the patient during the active phase (inspiration), and the regulated variable is the peak pressure at end-inspiration. This simulation case study focuses on patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD), which require artificial/mechanical ventilation. An adaptive PID controller ensures peak pressures below critical values, by manipulating the flow delivered by the ventilator. The simulation study is performed on fractional-order models of the respiratory impedance identified from lung function data obtained from 21 COPD patients. Additional simulation studies show the robustness of the controller in presence of varying model parameters from the respiratory impedance of the patient. Possibilities to implement the control strategy as an online adaptive algorithm are also explored. The results show that the design of the control is suitable for this kind of application and provides useful insight on realistic scenarios.

Measurement of fractional order model parameters of respiratory mechanical impedance in total liquid ventilation

This study presents a methodology for applying the forced-oscillation technique in total liquid ventilation. It mainly consists of applying sinusoidal volumetric excitation to the respiratory system, and determining the transfer function between the delivered flow rate and resulting airway pressure. The investigated frequency range was f ∈ [0.05, 4] Hz at a constant flow amplitude of 7.5 mL/s. The five parameters of a fractional order lung model, the existing "5-parameter constant-phase model," were identified based on measured impedance spectra. The identification method was validated in silico on computer-generated datasets and the overall process was validated in vitro on a simplified single-compartment mechanical lung model. In vivo data on ten newborn lambs suggested the appropriateness of a fractional-order compliance term to the mechanical impedance to describe the low-frequency behavior of the lung, but did not demonstrate the relevance of a fractional-order inertance term. Typical respiratory system frequency response is presented together with statistical data of the measured in vivo impedance model parameters. This information will be useful for both the design of a robust pressure controller for total liquid ventilators and the monitoring of the patient's respiratory parameters during total liquid ventilation treatment.

Fractional order model parameters for the respiratory input impedance in healthy and in asthmatic children

This paper provides an evaluation of a fractional order model for the respiratory input impedance, using two groups of subjects, respectively healthy and asthmatic children. The purpose is to verify if the model is able to deliver statistically meaningful parameter values in order to classify the two groups. The data are gathered with the non-invasive lung function test of forced oscillations technique, by means of a multisine signal within the 4-48Hz frequency range. Based on our previous work, a fractional order model for this range of frequencies is obtained. Additional parameters are proposed to evaluate the two groups. The results indicate that the model was unable to detect significant changes between the asthmatic children with normal spirometry results (as result of medication) and the healthy children. Due to medication intake during the hours prior to the exam, bronchial challenge did not modify substantially the respiratory parameters. Our findings correspond to similar studies reported in the specialized literature. Combined model parameters, such as the tissue damping and the tissue elastance were significantly different in the two groups (p<0.01). Two extra indexes are introduced: the quality factor and the power factor, providing significantly different results between the two groups (p≪0.01). We conclude that the model can be used in the respective frequency range to characterize the two groups efficiently.

Airway and tissue loading in postinterrupter response of the respiratory system - an identification algorithm construction

The paper offers an enhancement of the classical interrupter technique algorithm dedicated to respiratory mechanics measurements. Idea consists in exploitation of information contained in postocclusional transient states during indirect measurement of parameter characteristics by model identification. It needs the adequacy of an inverse analogue to general behavior of the real system and a reliable algorithm of parameter estimation. The second one was a subject of reported works, which finally showed the potential of the approach to separation of airway and tissue response in a case of short-term excitation by interrupter valve operation. Investigations were conducted in a regime of forward-inverse computer experiment.

Assessment of respiratory mechanical properties with constant-phase models in healthy and COPD lungs

This study employs the concept of applying constant-phase models to input respiratory impedance data obtained with the non-invasive Forced Oscillation Technique (FOT) lung function test. Changes in respiratory mechanics from healthy and chronic obstructive pulmonary disease (COPD) diagnosed patients are observed with a four- and a five-parameter constant-phase model. Tissue damping (p<<0.01), tissue elastance (p<0.02) and tissue hysteresivity (p<<0.01) are calculated from the identified model parameters, providing significant separation between healthy and COPD groups. Limitations of the four-parameter constant-phase model are shown in relation to frequency-dependent impedance values within the range 4-48 Hz. The results clearly show that the five-parameter constant-phase model outperforms the four-parameter constant-phase model in this frequency range. The averaged error is 0.02 and 0.04 for healthy subjects in the five-parameter and four-parameter constant-phase models, respectively. The results show that the identified model values are sensitive to variations between healthy and COPD lungs.

Mechanical properties of the respiratory system derived from morphologic insight

This paper aims to provide the mechanical parameters of the respiratory airways (resistance, inertance, and compliance) from morphological insight, in order to facilitate the correlations of fractional-order models with pathologic changes. The approach consists of taking into account wall thickness, inner radius, tube length, and tissue structure for each airway level to combine them into a set of equations for modeling the pressure drop, flow, wall elasticity, and air velocity (axial and radial). Effects of pulmonary disease affecting the inner radius and elastic modulus of bronchial tree are discussed. A brief comparison with the circulatory system, which poses similarities with the respiratory system, is also given. The derived mechanical parameters can serve as elements in a transmission line equivalent, whose structure preserves the geometry of the human respiratory tree. The mechanical parameters derived in this paper offer the possibility to evaluate input impedance by altering the morphological parameters in relation to the pulmonary disease. In this way, we obtain a simple, yet accurate, model to simulate and understand specific effects in respiratory diseases; e.g., airway remodeling. The final scope of the research is to relate the variations in airway structure with disease to the values of fractional-order model parameters.

Relations between fractional-order model parameters and lung pathology in chronic obstructive pulmonary disease

In this study, changes in respiratory mechanics from healthy and chronic obstructive pulmonary disease (COPD) diagnosed patients are observed from identified fractional-order (FO) model parameters. The noninvasive forced oscillation technique is employed for lung function testing. Parameters on tissue damping and elastance are analyzed with respect to lung pathology and additional indexes developed from the identified model. The observations show that the proposed model may be used to detect changes in respiratory mechanics and offers a clear-cut separation between the healthy and COPD subject groups. Our conclusion is that an FO model is able to capture changes in viscoelasticity of the soft tissue in lungs with disease. Apart from this, nonlinear effects present in the measured signals were observed and analyzed via signal processing techniques and led to supporting evidence in relation to the expected phenomena from lung pathology in healthy and COPD patients.