On the respiratory mechanics measured by forced oscillation technique in patients with systemic sclerosis

Respiratory oscillometry and functional analyses in patients with idiopathic scoliosis

Scoliosis is a condition that affects the spine and causes chest rotation and trunk distortion. Individuals with severe deformities may experience dyspnea on exertion and develop respiratory failure. Respiratory oscillometry is a simple and non-invasive method that provides detailed information on lung mechanics. This work aims to investigate the potential of oscillometry in the evaluation of respiratory mechanics in patients with scoliosis and its association with physical performance. We analyzed 32 volunteers in the control group and 32 in the scoliosis group. The volunteers underwent traditional pulmonary function tests, oscillometry, and the 6-minute walk test (6MWT). Oscillometric analysis showed increased values of resistance at 4 Hz (R4, P<0.01), 12 Hz (R12, P<0.0001), and 20 Hz (R20, P<0.01). Similar analysis showed reductions in dynamic compliance (Cdyn, P<0.001) and ventilation homogeneity, as evaluated by resonance frequency (fr, P<0.001) and reactance area (Ax, P<0.001). Respiratory work, described by the impedance modulus, also showed increased values (Z4, P<0.01). Functional capacity was reduced in the group with scoliosis (P<0.001). A significant direct correlation was found between Cobb angle and R12, AX, and Z4 (P=0.0237, P=0.0338, and P=0.0147, respectively), and an inverse correlation was found between Cdyn and Cobb angle (P=0.0190). These results provided new information on respiratory mechanics in scoliosis and are consistent with the involved pathophysiology, suggesting that oscillometry may improve lung function tests for patients with scoliosis.

Oscillometry of the respiratory system in Parkinson's disease: physiological changes and diagnostic use

BACKGROUND

Lung function analysis in Parkinson's disease (PD) is often difficult due to the demand for adequate forced expiratory maneuvers. Respiratory oscillometry exams require onlyquiet tidal breathing and provide a detailed analysis of respiratory mechanics. We hypothesized that oscillometry would simplify the diagnosis of respiratory abnormalitiesin PD and improve our knowledge about the pathophysiological changes in these patients.

MATERIALS AND METHODS

This observational study includes 20 controls and 47 individuals with PD divided into three groups (Hoehn and Yahr Scale 1-1.5; H&Y scale 2-3 and PD smokers).The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC).

RESULTS

Initial stages are related to increased peripheral resistance (Rp; p = 0.001). In more advanced stages, a restrictive pattern is added, reflected by reductions in dynamic compliance (p < 0.05) and increase in resonance frequency (Fr; p < 0.001). Smoking PD patients presented increased Rp (p < 0.001) and Fr (p < 0.01). PD does not introduce changes in the central airways. Oscillometric changes were correlated with respiratory muscle weakness (R = 0.37, p = 0.02). Rp showed adequate accuracy in the detection of early respiratory abnormalities (AUC = 0.858), while in more advanced stages, Fr showed high diagnostic accuracy (AUC = 0.948). The best parameter to identify changes in smoking patients was Rp (AUC = 0.896).

CONCLUSION

The initial stages of PD are related to a reduction in ventilation homogeneity associated with changes in peripheral airways. More advanced stages also include a restrictive ventilatory pattern. These changes were correlated with respiratory muscle weakness and were observed in mild and moderate stages of PD in smokers and non-smokers. Oscillometry may adequately identify respiratory changes in the early stages of PD and obtain high diagnostic accuracy in more advanced stages of the disease.

Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis

INTRODUCTION

The use of machine learning (ML) methods would improve the diagnosis of respiratory changes in systemic sclerosis (SSc). This paper evaluates the performance of several ML algorithms associated with the respiratory oscillometry analysis to aid in the diagnostic of respiratory changes in SSc. We also find out the best configuration for this task.

METHODS

Oscillometric and spirometric exams were performed in 82 individuals, including controls (n = 30) and patients with systemic sclerosis with normal (n = 22) and abnormal (n = 30) spirometry. Multiple instance classifiers and different supervised machine learning techniques were investigated, including k-Nearest Neighbors (KNN), Random Forests (RF), AdaBoost with decision trees (ADAB), and Extreme Gradient Boosting (XGB).

RESULTS AND DISCUSSION

The first experiment of this study showed that the best oscillometric parameter (BOP) was dynamic compliance, which provided moderate accuracy (AUC = 0.77) in the scenario control group versus patients with sclerosis and normal spirometry (CGvsPSNS). In the scenario control group versus patients with sclerosis and altered spirometry (CGvsPSAS), the BOP obtained high accuracy (AUC = 0.94). In the second experiment, the ML techniques were used. In CGvsPSNS, KNN achieved the best result (AUC = 0.90), significantly improving the accuracy in comparison with the BOP (p < 0.01), while in CGvsPSAS, RF obtained the best results (AUC = 0.97), also significantly improving the diagnostic accuracy (p < 0.05). In the third, fourth, fifth, and sixth experiments, different feature selection techniques allowed us to spot the best oscillometric parameters. They resulted in a small increase in diagnostic accuracy in CGvsPSNS (respectively, 0.87, 0.86, 0.82, and 0.84), while in the CGvsPSAS, the best classifier's performance remained the same (AUC = 0.97).

CONCLUSIONS

Oscillometric principles combined with machine learning algorithms provide a new method for diagnosing respiratory changes in patients with systemic sclerosis. The present study's findings provide evidence that this combination may help in the early diagnosis of respiratory changes in these patients.

Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity

Purpose

This research examines the emerging role of respiratory oscillometry associated with integer (InOr) and fractional order (FrOr) respiratory models in the context of groups of patients with increasing severity. The contributions to our understanding of the respiratory abnormalities along the course of increasing COPD severity and the diagnostic use of this method were also evaluated.

Patients and Methods

Forty-five individuals with no history of smoking or pulmonary diseases (control group) and 141 individuals with diagnoses of COPD were studied, being classified into 45 mild, 42 moderate, 36 severe and 18 very severe cases.

Results

This study has shown initially that the course of increasing COPD severity was adequately described by the model parameters. This resulted in significant and consistent correlations among these parameters and spirometric indexes. Additionally, this evaluation enhanced our understanding of the respiratory abnormalities in different COPD stages. The diagnostic accuracy analyses provided evidence that hysteresivity, obtained from FrOr modeling, allowed a highly accurate identification in patients with mild changes [area under the receiver operator characteristic curve (AUC)= 0.902]. Similar analyses in groups of moderate and severe patients showed that peripheral resistance, derived from InOr modeling, provided the most accurate parameter (AUC=0.898 and 0.998, respectively), while in very severe patients, traditional, InOr and FrOr parameters were able to reach high diagnostic accuracy (AUC>0.9).

Conclusion

InOr and FrOr modeling improved our knowledge of the respiratory abnormalities along the course of increasing COPD severity. In addition, the present study provides evidence that these models may contribute in the diagnosis of COPD. Respiratory oscillometry exams require only tidal breathing and are easy to perform. Taken together, these practical considerations and the results of the present study suggest that respiratory oscillometry associated with InOr and FrOr models may help to improve lung function tests in COPD.

Differential diagnosis of asthma and restrictive respiratory diseases by combining forced oscillation measurements, machine learning and neuro-fuzzy classifiers

To design machine learning classifiers to facilitate the clinical use and increase the accuracy of the forced oscillation technique (FOT) in the differential diagnosis of patients with asthma and restrictive respiratory diseases. FOT and spirometric exams were performed in 97 individuals, including controls (n = 20), asthmatic patients (n = 38), and restrictive (n = 39) patients. The first experiment of this study showed that the best FOT parameter was the resonance frequency, providing moderate accuracy (AUC = 0.87). In the second experiment, a neuro-fuzzy classifier and different supervised machine learning techniques were investigated, including k-nearest neighbors, random forests, AdaBoost with decision trees, and support vector machines with a radial basis kernel. All classifiers achieved high accuracy (AUC ≥ 0.9) in the differentiation between patient groups. In the third and fourth experiments, the use of different feature selection techniques allowed us to achieve high accuracy with only three FOT parameters. In addition, the neuro-fuzzy classifier also provided rules to explain the classification. Neuro-fuzzy and machine learning classifiers can aid in the differential diagnosis of patients with asthma and restrictive respiratory diseases. They can assist clinicians as a support system providing accurate diagnostic options.

Increased prevalence of small airways dysfunction in patients with systemic sclerosis as determined by impulse oscillometry

OBJECTIVES

The prevalence and clinical implications of small airways involvement in SSc are still to be fully elucidated. The goal of the present work is to assess the prevalence of small airways dysfunction by impulse oscillometry and to determine whether it correlates with selected disease-related features and respiratory-related quality of life.

METHODS

Ninety-four SSc patients and 93 healthy controls were studied by impulse oscillometry measurements. Small airways dysfunction was defined as the difference between resistance at low frequency, i.e. 5 Hz, and resistance at high frequency, i.e. 20 Hz, termed 'R5-R20', ⩾0.07 kPa/l/s. The St George's Respiratory Questionnaire was used to measure health impairment in SSc patients. Radiological features of small airways disease and parenchymal abnormalities on high resolution CT chest scans were jointly assessed by two thoracic radiologists.

RESULTS

Small airways dysfunction was present in 21.5% of the SSc patient cohort, with a prevalence almost 5-fold higher compared with controls, and it was significantly associated with worse respiratory-related quality of life. Radiological features consistent with small airways abnormalities were detected in 25% of SSc patients, mostly in the absence of interstitial lung changes. Combining functional and radiological evaluations, one-third of the SSc cohort showed at least one feature of small airways involvement, which was associated with the lcSSc phenotype and with longer disease duration.

CONCLUSION

The current study strengthens the hypothesis that small airway dysfunction might be a feature of SSc-related lung involvement, providing the first data on its significant impact on respiratory-related quality of life. A full assessment of lung function in SSc patients should include impulse oscillometry as a complementary technique, due to potential clinical and therapeutic implications.

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 oscillation technique for early detection of the effects of smoking and COPD: contribution of fractional-order modeling

Purpose

The aim of the present study was to evaluate the performance of the forced oscillation technique (FOT) for the early diagnosis of the effects of smoking and COPD. The contributions of the integer-order (InOr) and fractional-order (FrOr) models were also evaluated.

Patients and methods

In total, 120 subjects were analyzed: 40 controls, 40 smokers (20.3±9.3 pack-years) and 40 patients with mild COPD.

Results

Initially, it was observed that traditional FOT parameters and the InOr and FrOr models provided a consistent description of the COPD pathophysiology. Mild COPD introduced significant increases in the FrOr inertance, damping factor and hysteresivity (P<0.0001). These parameters were significantly correlated with the spirometric parameters of central and small airway obstruction (P<0.0001). The diagnostic accuracy analyses indicated that FOT parameters and InOr modeling may adequately identify these changes (area under the receiver operating characteristic curve – AUC >0.8). The use of FrOr modeling significantly improved this process (P<0.05), allowing the early diagnosis of smokers and patients with mild COPD with high accuracy (AUC >0.9).

Conclusion

FrOr modeling improves our knowledge of modifications that occur in the early stages of COPD. Additionally, the findings of the present study provide evidence that these models may play an important role in the early diagnosis of COPD, which is crucial for improving the clinical management of the disease.

Computed tomography trachea volumetry in patients with scleroderma: Association with clinical and functional findings

BACKGROUND

In scleroderma, excessive collagen production can alter tracheal geometry, and computed tomography (CT) volumetry of this structure may aid in detecting possible abnormalities. The objectives of this study were to quantify the morphological abnormalities in the tracheas of ​​patients with scleroderma and to correlate these findings with data on clinical and pulmonary function.

METHODS

This was a cross-sectional study in which 28 adults with scleroderma and 27 controls matched by age, gender and body mass index underwent chest CT with posterior segmentation and skeletonization of the images. In addition, all participants underwent pulmonary function tests and clinical evaluation, including the modified Rodnan skin score (mRSS).

RESULTS

Most patients (71.4%) had interstitial lung disease on CT. Compared to controls, patients with scleroderma showed higher values ​​in the parameters measured by CT trachea volumetry, including area, eccentricity, major diameter, minor diameter, and tortuosity. The tracheal area and equivalent diameter were negatively correlated with the ratio between forced expiratory flow and forced inspiratory flow at 50% of forced vital capacity (FEF50%/FIF50%) (r = -0.44, p = 0.03 and r = -0.46, p = 0.02, respectively). The tracheal tortuosity was negatively correlated with peak expiratory flow (r = -0.51, p = 0.008). The mRSS showed a positive correlation with eccentricity (r = 0.62, p < 0.001) and tracheal tortuosity (r = 0.51, p = 0.007), while the presence of anti-topoisomerase I antibody (ATA) showed a positive correlation with tracheal tortuosity (r = 0.45, p = 0.03).

CONCLUSIONS

In a sample composed predominantly of scleroderma patients with associated interstitial lung disease, there were abnormalities in tracheal geometry, including greater eccentricity, diameter and tortuosity. In these patients, abnormalities in the geometry of the trachea were associated with functional markers of obstruction. In addition, tracheal tortuosity was correlated with cutaneous involvement and the presence of ATA.

Respiratory resistance and reactance in adults with sickle cell anemia: Correlation with functional exercise capacity and diagnostic use

BACKGROUND

The improvement in sickle cell anemia (SCA) care resulted in the emergence of a large population of adults living with this disease. The mechanisms of lung injury in this new population are largely unknown. The forced oscillation technique (FOT) represents the current state-of-the-art in the assessment of lung function. The present work uses the FOT to improve our knowledge about the respiratory abnormalities in SCA, evaluates the associations of FOT with the functional exercise capacity and investigates the early detection of respiratory abnormalities.

METHODOLOGY/PRINCIPAL FINDINGS

Spirometric classification of restrictive abnormalities resulted in three categories: controls (n = 23), patients with a normal exam (n = 21) and presenting pulmonary restriction (n = 24). FOT analysis showed that, besides restrictive changes (reduced compliance; p<0.001), there is also an increase in respiratory resistance (p<0.001) and ventilation heterogeneity (p<0.01). FOT parameters are associated with functional exercise capacity (R = -0.38), pulmonary diffusion (R = 0.66), respiratory muscle performance (R = 0.41), pulmonary volumes (R = 0.56) and airway obstruction (R = 0.54). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). A combination of FOT and machine learning (ML) classifiers showed adequate diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.82).

CONCLUSIONS

In this study, the use of FOT showed that adults with SCA develop a mixed pattern of respiratory disease. Changes in FOT parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FOT associated with ML methods accurately diagnosed early respiratory abnormalities. This suggested the potential utility of the FOT and ML clinical decision support systems in the identification of respiratory abnormalities in patients with SCA.

High-accuracy detection of airway obstruction in asthma using machine learning algorithms and forced oscillation measurements

BACKGROUND AND OBJECTIVES

The main pathologic feature of asthma is episodic airway obstruction. This is usually detected by spirometry and body plethysmography. These tests, however, require a high degree of collaboration and maximal effort on the part of the patient. There is agreement in the literature that there is a demand of research into new technologies to improve non-invasive testing of lung function. The purpose of this study was to develop automatic classifiers to simplify the clinical use and to increase the accuracy of the forced oscillation technique (FOT) in the diagnosis of airway obstruction in patients with asthma.

METHODS

The data consisted of FOT parameters obtained from 75 volunteers (39 with obstruction and 36 without). Different supervised machine learning (ML) techniques were investigated, including k-nearest neighbors (KNN), random forest (RF), AdaBoost with decision trees (ADAB) and feature-based dissimilarity space classifier (FDSC).

RESULTS

The first part of this study showed that the best FOT parameter was the resonance frequency (AUC = 0.81), which indicates moderate accuracy (0.70-0.90). In the second part of this study, the use of the cited ML techniques was investigated. All the classifiers improved the diagnostic accuracy. Notably, ADAB and KNN were very close to achieving high accuracy (AUC = 0.88 and 0.89, respectively). Experiments including the cross products of the FOT parameters showed that all the classifiers improved the diagnosis accuracy and KNN was able to reach a higher accuracy range (AUC = 0.91).

CONCLUSIONS

Machine learning classifiers can help in the diagnosis of airway obstruction in asthma patients, and they can assist clinicians in airway obstruction identification.

Ventilation distribution and small airway function in patients with systemic sclerosis

BACKGROUND

Despite the importance of traditional pulmonary function tests (PFTs) in managing systemic sclerosis (SSc), many patients with pulmonary disease diagnosed by computed tomography (CT) present with normal PFTs.

OBJECTIVE

To evaluate the efficacy of the nitrogen single-breath washout (N₂SBW) test in diagnosing SSc and to correlate N₂SBW parameters with the PFT indexes used in the follow-up of these patients, clinical data, and CT findings.

METHODS

Cross-sectional study in which 52 consecutive SSc patients were subjected to spirometry, body plethysmography, analysis of the diffusing capacity for carbon monoxide (DLCO), analysis of respiratory muscle strength, N₂SBW testing, and CT analysis.

RESULTS

Twenty-eight patients had a forced vital capacity (FVC) that was <70% of the predicted value. In the N₂SBW test, 44 patients had a phase III slope (Phase III slope_N2SBW) that was >120% of the predicted value, while 15 patients had a closing volume/vital capacity (CV/VC) that was >120% of the predicted value. A significant difference in Phase III slope_N2SBW was observed when the patients with predominant traction bronchiectasis and honeycombing were compared to the patients with other CT patterns (p<0.0001). The Phase III slope_N2SBW was correlated with FVC (r_s=-0.845, p<0.0001) and DLCO (r_s=-0.600, p<0.0001), and the CV/VC was correlated with FVC (r_s=-0.460, p=0.0006) and residual volume/total lung capacity (r_s=0.328, p=0.017).

CONCLUSION

Ventilation heterogeneity is a frequent finding in SSc patients that is associated with restrictive damage, changes in pulmonary diffusion, and CT patterns. In addition, approximately one-third of the patients presented with findings that were compatible with small airway disease.

Early Diagnosis of Respiratory Abnormalities in Asbestos-Exposed Workers by the Forced Oscillation Technique

BACKGROUND

The current reference test for the detection of respiratory abnormalities in asbestos-exposed workers is spirometry. However, spirometry has several shortcomings that greatly affect the efficacy of current asbestos control programs. The forced oscillation technique (FOT) represents the current state-of-the-art technique in the assessment of lung function. This method provides a detailed analysis of respiratory resistance and reactance at different oscillatory frequencies during tidal breathing. Here, we evaluate the FOT as an alternative method to standard spirometry for the early detection and quantification of respiratory abnormalities in asbestos-exposed workers.

METHODOLOGY/PRINCIPAL FINDINGS

Seventy-two subjects were analyzed. The control group was composed of 33 subjects with a normal spirometric exam who had no history of smoking or pulmonary disease. Thirty-nine subjects exposed to asbestos were also studied, including 32 volunteers in radiological category 0/0 and 7 volunteers with radiological categories of 0/1 or 1/1. FOT data were interpreted using classical parameters as well as integer (InOr) and fractional-order (FrOr) modeling. The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Exposed workers presented increased obstruction (resistance p<0.001) and a reduced compliance (p<0.001), with a predominance of obstructive changes. The FOT parameter changes were correlated with the standard pulmonary function analysis methods (R = -0.52, p<0.001). Early respiratory abnormalities were identified with a high diagnostic accuracy (AUC = 0.987) using parameters obtained from the FrOr modeling. This accuracy was significantly better than those obtained with classical (p<0.001) and InOr (p<0.001) model parameters.

CONCLUSIONS

The FOT improved our knowledge about the biomechanical abnormalities in workers exposed to asbestos. Additionally, a high diagnostic accuracy in the diagnosis of early respiratory abnormalities in asbestos-exposed workers was obtained. This makes the FOT particularly useful as a screening tool in the context of asbestos control and elimination. Moreover, it can facilitate epidemiological research and the longitudinal follow-up of asbestos exposure and asbestos-related diseases.

Forced oscillation, integer and fractional-order modeling in asthma

The purpose of this study was to evaluate the use of fractional-order (FrOr) modeling in asthma. To this end, three FrOr models were compared with traditional parameters and an integer-order model (InOr). We investigated which model would best fit the data, the correlation with traditional lung function tests and the contribution to the diagnostic of airway obstruction. The data consisted of forced oscillation (FO) measurements obtained from healthy (n=22) and asthmatic volunteers with mild (n=22), moderate (n=19) and severe (n=19) obstructions. The first part of this study showed that a FrOr was the model that best fit the data (relative distance: FrOr=4.3±2.4; InOr=5.1±2.6%). The correlation analysis resulted in reasonable (R=0.36) to very good (R=0.77) associations between FrOr parameters and spirometry. The closest associations were observed between parameters related to peripheral airway obstruction, showing a clear relationship between the FrOr models and lung mechanics. Receiver-operator analysis showed that FrOr parameters presented a high potential to contribute to the detection of the mild obstruction in a clinical setting. The accuracy [area under the Receiver Operating Characteristic curve (AUC)] observed in these parameters (AUC=0.954) was higher than that observed in traditional FO parameters (AUC=0.732) and that obtained from the InOr model (AUC=0.861). Patients with moderate and severe obstruction were identified with high accuracy (AUC=0.972 and 0.977, respectively). In conclusion, the results obtained are in close agreement with asthma pathology, and provide evidence that FO measurement associated with FrOr models is a non-invasive, simple and radiation-free method for the detection of biomechanical abnormalities in asthma.

Respiratory mechanics measured by forced oscillation technique in rheumatoid arthritis-related pulmonary abnormalities: frequency-dependence, heterogeneity and effects of smoking

Rheumatoid arthritis (RA)-related pulmonary disorders specifically airway abnormalities and interstitial pneumonia (IP) are important extra-articular manifestations. The forced oscillation technique (FOT) is a useful method to assess respiratory impedance, respiratory resistance (Rrs) and reactance (Xrs), at different oscillatory frequencies during tidal breathing. The aim of this study was to characterize the respiratory mechanics of patients with RA and to relate them to parameters of the pulmonary function test and findings of chest CT images. Respiratory impedance of RA patients (n = 69) was measured as a function of frequency from 4 to 36 Hz using the FOT device and compared with that of healthy subjects (n = 10). Data were retrospectively reviewed. Patients were female-dominant (60.9 %) and 95.7 % had abnormal CT findings including airway and parenchymal abnormalities. Thirty-seven of 69 patients (53.6 %) were smokers. Rrs was significantly frequency-dependent in RA patients but not in the healthy subjects. Xrs were significantly frequency-dependent in both RA and healthy groups. Rrs was significantly higher during an expiratory phase in both RA and healthy groups. Xrs was significantly lower (more negative) during an expiratory phase than that during an inspiratory phase in RA patients but not in healthy subjects. Xrs of the RA group was significantly more negative than that of the normal control. There was no difference in impedance parameters between the airway lesion dominant (n = 27) and IP dominant groups (n = 23) in the RA group. The impedance parameters of the RA group significantly correlated with most parameters of the pulmonary function test. In pulmonary function test results, % of the predicted value for forced expiratory flow from 25 to 75 % of forced vital capacity was significantly lower and % of the predicted value for diffusing capacity of the lung for carbon monoxide was higher in the airway lesion dominant group than those in the IP dominant group. Krebs von den Lungen-6, a serum indicator of IP, was significantly higher in the IP group than that in the airway lesion dominant group. Taken together, the impedance results reflect abnormalities in pulmonary functions and structures in patients with RA.

Airway resistance and reactance are affected in systemic sclerosis

Background

Interstitial lung disease often occurs as an early complication of systemic sclerosis (SSc). The aim was to investigate whether impulse oscillometry (IOS) could be used to evaluate lung impairment in SSc.

Methods

Seventy-eight SSc patients, of which 65 had limited cutaneous SSc (lcSSc) and 13 had diffuse cutaneous SSc (dcSSc), were subjected to high-resolution computed tomography (HRCT) and pulmonary function tests (spirometry, IOS, and single breath CO diffusion capacity test). Twenty-six healthy individuals served as controls.

Results

Patients with lcSSc had higher levels of peripheral airway resistance, that is, R5–R20 (difference between resistance at 5 Hz and resistance at 20 Hz) showed a median (and interquartile range) of 0.05 (0.02–0.09) in lcSSc, 0.01 (0.00–0.04) in dcSSc and 0.04 (0.01–0.06) in healthy controls. They also had higher levels of reactance: reactance area was 0.26 (0.15–0.56) in lcSSc, 0.20 (0.11–0.29) in dcSSc and 0.18 (0.08–0.30) in healthy controls, and resonant frequency was 10.9 (8.8–14.8) in lcSSc, 9.0 (8.3–11.6) in dcSSc and 9.1 (8.0–13.1) in healthy controls. Airway reactance correlated to fibrotic findings on HRCT, such as ground glass opacities and reticulations.

Discussion

This implies that IOS parameters to some extent are related to fibrosis in patients with SSc.

Correlations between forced oscillation technique parameters and pulmonary densitovolumetry values in patients with acromegaly

The aims of this study were to evaluate the forced oscillation technique (FOT) and pulmonary densitovolumetry in acromegalic patients and to examine the correlations between these findings. In this cross-sectional study, 29 non-smoking acromegalic patients and 17 paired controls were subjected to the FOT and quantification of lung volume using multidetector computed tomography (Q-MDCT). Compared with the controls, the acromegalic patients had a higher value for resonance frequency [15.3 (10.9-19.7) vs 11.4 (9.05-17.6) Hz, P=0.023] and a lower value for mean reactance [0.32 (0.21-0.64) vs 0.49 (0.34-0.96) cm H₂O/L/s², P=0.005]. In inspiratory Q-MDCT, the acromegalic patients had higher percentages of total lung volume (TLV) for nonaerated and poorly aerated areas [0.42% (0.30-0.51%) vs 0.25% (0.20-0.32%), P=0.039 and 3.25% (2.48-3.46%) vs 1.70% (1.45-2.15%), P=0.001, respectively]. Furthermore, the acromegalic patients had higher values for total lung mass in both inspiratory and expiratory Q-MDCT [821 (635-923) vs 696 (599-769) g, P=0.021 and 844 (650-945) vs 637 (536-736) g, P=0.009, respectively]. In inspiratory Q-MDCT, TLV showed significant correlations with all FOT parameters. The TLV of hyperaerated areas showed significant correlations with intercept resistance (r_s=−0.602, P<0.001) and mean resistance (r_s=−0.580, P<0.001). These data showed that acromegalic patients have increased amounts of lung tissue as well as nonaerated and poorly aerated areas. Functionally, there was a loss of homogeneity of the respiratory system. Moreover, there were correlations between the structural and functional findings of the respiratory system, consistent with the pathophysiology of the disease.

Within-breath respiratory impedance and airway obstruction in patients with chronic obstructive pulmonary disease

OBJECTIVE

Recent work has suggested that within-breath respiratory impedance measurements performed using the forced oscillation technique may help to noninvasively evaluate respiratory mechanics. We investigated the influence of airway obstruction on the within-breath forced oscillation technique in smokers and chronic obstructive pulmonary disease patients and evaluated the contribution of this analysis to the diagnosis of chronic obstructive pulmonary disease.

METHODS

Twenty healthy individuals and 20 smokers were assessed. The study also included 74 patients with stable chronic obstructive pulmonary disease. We evaluated the mean respiratory impedance (Zm) as well as values for the inspiration (Zi) and expiration cycles (Ze) at the beginning of inspiration (Zbi) and expiration (Zbe), respectively. The peak-to-peak impedance (Zpp=Zbe-Zbi) and the respiratory cycle dependence (ΔZrs=Ze-Zi) were also analyzed. The diagnostic utility was evaluated by investigating the sensitivity, the specificity and the area under the receiver operating characteristic curve. ClinicalTrials.gov: NCT01888705.

RESULTS

Airway obstruction increased the within-breath respiratory impedance parameters that were significantly correlated with the spirometric indices of airway obstruction (R=-0.65, p<0.0001). In contrast to the control subjects and the smokers, the chronic obstructive pulmonary disease patients presented significant expiratory-inspiratory differences (p<0.002). The adverse effects of moderate airway obstruction were detected based on the Zpp with an accuracy of 83%. Additionally, abnormal effects in severe and very severe patients were detected based on the Zm, Zi, Ze, Zbe, Zpp and ΔZrs with a high degree of accuracy (>90%).

CONCLUSIONS

We conclude the following: (1) chronic obstructive pulmonary disease introduces higher respiratory cycle dependence, (2) this increase is proportional to airway obstruction, and (3) the within-breath forced oscillation technique may provide novel parameters that facilitate the diagnosis of respiratory abnormalities in chronic obstructive pulmonary disease.

Relationships between the pulmonary densitometry values obtained by CT and the forced oscillation technique parameters in patients with silicosis

OBJECTIVE

To evaluate the correlations between pulmonary densitometry values and forced oscillation technique (FOT) parameters in patients with silicosis.

METHODS

This cross-sectional study comprised 36 non-smoker patients with silicosis and 20 matched control subjects who were submitted to FOT and multidetector CT (MDCT).

RESULTS

Compared with the control subjects, the MDCT evaluation demonstrated that patients with silicosis exhibited greater total lung mass. These patients also had larger non-aerated and poorly aerated compartments, which included nodules and scarring. Compared with the control subjects, FOT evaluation demonstrated that patients with silicosis exhibited changes in both reactive and resistive properties of the respiratory system. In these patients, there was a greater heterogeneity of the respiratory system and increased work of breathing. Significant correlations between non-aerated compartment size and FOT parameters that reflect the non-homogeneity of the respiratory system were observed. The dynamic compliance of the respiratory system was negatively correlated with non-aerated compartment size, while the impedance at 4 Hz was positively correlated with non-aerated compartment size.

CONCLUSION

Patients with silicosis have heavier lungs. In these patients, a larger non-aerated compartment is associated with a worsening of lung function. A more significant pulmonary involvement is associated with a loss of homogeneity and increased mechanical load of the respiratory system. Advances in knowledge The findings provided by both pulmonary densitometry and FOT may add valuable information to the subjective analysis of silicosis; however, more studies are necessary to evaluate the potential use of these methods for assessing disease progression.

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.

Machine learning algorithms and forced oscillation measurements to categorise the airway obstruction severity in chronic obstructive pulmonary disease

The purpose of this study was to develop automatic classifiers to simplify the clinical use and increase the accuracy of the forced oscillation technique (FOT) in the categorisation of airway obstruction level in patients with chronic obstructive pulmonary disease (COPD). The data consisted of FOT parameters obtained from 168 volunteers (42 healthy and 126 COPD subjects with four different levels of obstruction). The first part of this study showed that FOT parameters do not provide adequate accuracy in identifying COPD subjects in the first levels of obstruction, as well as in discriminating between close levels of obstruction. In the second part of this study, different supervised machine learning (ML) techniques were investigated, including k-nearest neighbour (KNN), random forest (RF) and support vector machines with linear (SVML) and radial basis function kernels (SVMR). These algorithms were applied only in situations where high categorisation accuracy [area under the Receiver Operating Characteristic curve (AUC)≥0.9] was not achieved with the FOT parameter alone. It was observed that KNN and RF classifiers improved categorisation accuracy. Notably, in four of the six cases studied, an AUC≥0.9 was achieved. Even in situations where an AUC≥0.9 was not achieved, there was a significant improvement in categorisation performance (AUC≥0.83). In conclusion, machine learning classifiers can help in the categorisation of COPD airway obstruction. They can assist clinicians in tracking disease progression, evaluating the risk of future disease exacerbations and guiding therapy.

Respiratory impedance and response to salbutamol in healthy individuals and patients with COPD

BACKGROUND

Recent studies suggested that the bronchodilator response depends on airway obstruction. The forced oscillation technique (FOT) may help improve our understanding of the changes in respiratory mechanics that occur after the application of a bronchodilator.

OBJECTIVES

We aimed to (1) assess the response to salbutamol and to compare the impedance changes in healthy individuals and COPD patients, (2) investigate the effects of airway obstruction on this response and (3) evaluate the utility of the FOT as a complementary measurement to assess the response to the bronchodilator.

METHODS

Twenty-five healthy individuals and 82 patients with COPD were assessed with the FOT followed by spirometry before and after the use of salbutamol.

RESULTS

The changes exhibited by the COPD subgroups were greater than in the healthy individuals (p < 0.05). Increased obstruction resulted in decreased reductions in mean resistance and increased improvements in mean reactance (p < 0.001). In addition, the bronchodilation reduced the ventilation heterogeneity and the impedance modulus in all COPD stages (p < 0.05). The correlation coefficients for the spirometric and FOT changes were low (0.21-0.38).

CONCLUSIONS

In the initial phases of COPD (stage I), the effects of bronchodilation are greater than in healthy volunteers. The bronchodilator use improved the oscillatory mechanics in all of the studied groups of COPD patients. These improvements are reduced in more advanced phases of airway obstruction (II, III and IV). The FOT provides information that complements the data supplied by spirometry, contributing to an improvement in the evaluation of the bronchodilator response in COPD.