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

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.

Bronchiectasis Assessment in Primary Ciliary Dyskinesia: A Non-Invasive Approach Using Forced Oscillation Technique

Primary ciliary dyskinesia (PCD) is an autosomal recessive disorder that results from the dysfunction of motile cilia, which can cause chronic upper and lower respiratory infections leading to bronchiectasis. However, there is a need for additional tools to monitor the progression of bronchiectasis in PCD. The forced oscillation technique (FOT) is an effort-independent lung function test that can be used to evaluate respiratory mechanics. In this retrospective study, we aimed to describe the radiographic findings associated with respiratory impedance (resistance (Rrs) and reactance (Xrs)) measured by FOT in six adult PCD patients and one pediatric with the (RSPH4A (c.921+3_921+6delAAGT (intronic)) founder mutation. We compared the radiographic findings on a high-resolution chest computed tomography (CT) scan with the FOT results. Our findings suggest that respiratory impedance measured by FOT may be a valuable tool for detecting and monitoring the progression of bronchiectasis in PCD patients with the (RSPH4A (c.921+3_921+6delAAGT (intronic)) founder mutation. However, further research is necessary to validate these results and determine the sensitivity and specificity of bronchiectasis monitoring in PCD patients with other genetic mutations.

Lung Function Reference Equations for Indian Ethnic Groups Based on a Handheld Forced Oscillation Device for Age 9-19 Years

OBJECTIVE

To develop regression equations to predict forced oscillation technique (FOT) parameters in Indian children and adolescents.

METHODS

Lung function was assessed in a multigeographic cohort of residential school children using a portable FOT-based device (PulmoScan) and spirometry. FOT measurements were performed in 1497 study participants, aged 9-19 y, from 8 Indian districts. Bland-Altman analysis was performed for additional 32 adult subjects to compare the results of PulmoScan to a standard IOS device in an outpatient setting. Reference equations were developed for R_rs and X_rs from the data of healthy subjects with normal spirometry using multivariate regression model for Indo-European, Dravidian, and mixed ethnic groups.

RESULTS

X5 (bias = 0.02) showed a better agreement than resistance parameters (R5 bias = 0.75, R20 bias =  -0.22) in IOS/PulmoScan comparison. Anthropometric variables (age, height, and weight) were positively correlated with reactance (X5) and negatively with resistance parameters (R5, R10, R15, and R20), with most associations being stronger in boys. Final regression model considered ethnicity as a key determinant along with anthropometry.

CONCLUSION

Multiethnic reference equations were developed for Indian children aged 9-19 y based on a novel handheld FOT device.

Lung function measurements in preclinical research: What has been done and where is it headed?

Due to the close interaction of lung morphology and functions, repeatable measurements of pulmonary function during longitudinal studies on lung pathophysiology and treatment efficacy have been a great area of interest for lung researchers. Spirometry, as a simple and quick procedure that depends on the maximal inspiration of the patient, is the most common lung function test in clinics that measures lung volumes against time. Similarly, in the preclinical area, plethysmography techniques offer lung functional parameters related to lung volumes. In the past few decades, many innovative techniques have been introduced for in vivo lung function measurements, while each one of these techniques has their own advantages and disadvantages. Before each experiment, depending on the sensitivity of the required pulmonary functional parameters, it should be decided whether an invasive or non-invasive approach is desired. On one hand, invasive techniques offer sensitive and specific readouts related to lung mechanics in anesthetized and tracheotomized animals at endpoints. On the other hand, non-invasive techniques allow repeatable lung function measurements in conscious, free-breathing animals with readouts related to the lung volumes. The biggest disadvantage of these standard techniques for lung function measurements is considering the lung as a single unit and providing only global readouts. However, recent advances in lung imaging modalities such as x-ray computed tomography and magnetic resonance imaging opened new doors toward obtaining both anatomical and functional information from the same scan session, without the requirement for any extra pulmonary functional measurements, in more regional and non-invasive manners. Consequently, a new field of study called pulmonary functional imaging was born which focuses on introducing new techniques for regional quantification of lung function non-invasively using imaging-based techniques. This narrative review provides first an overview of both invasive and non-invasive conventional methods for lung function measurements, mostly focused on small animals for preclinical research, including discussions about their advantages and disadvantages. Then, we focus on those newly developed, non-invasive, imaging-based techniques that can provide either global or regional lung functional readouts at multiple time-points.

Explainable machine learning methods and respiratory oscillometry for the diagnosis of respiratory abnormalities in sarcoidosis

BACKGROUND

In this work, we developed many machine learning classifiers to assist in diagnosing respiratory changes associated with sarcoidosis, based on results from the Forced Oscillation Technique (FOT), a non-invasive method used to assess pulmonary mechanics. In addition to accurate results, there is a particular interest in their interpretability and explainability, so we used Genetic Programming since the classification is made with intelligible expressions and we also evaluate the feature importance in different experiments to find the more discriminative features.

METHODOLOGY/PRINCIPAL FINDINGS

We used genetic programming in its traditional tree form and a grammar-based form. To check if interpretable results are competitive, we compared their performance to K-Nearest Neighbors, Support Vector Machine, AdaBoost, Random Forest, LightGBM, XGBoost, Decision Trees and Logistic Regressor. We also performed experiments with fuzzy features and tested a feature selection technique to bring even more interpretability. The data used to feed the classifiers come from the FOT exams in 72 individuals, of which 25 were healthy, and 47 were diagnosed with sarcoidosis. Among the latter, 24 showed normal conditions by spirometry, and 23 showed respiratory changes. The results achieved high accuracy (AUC > 0.90) in two analyses performed (controls vs. individuals with sarcoidosis and normal spirometry and controls vs. individuals with sarcoidosis and altered spirometry). Genetic Programming and Grammatical Evolution were particularly beneficial because they provide intelligible expressions to make the classification. The observation of which features were selected most frequently also brought explainability to the study of sarcoidosis.

CONCLUSIONS

The proposed system may provide decision support for clinicians when they are struggling to give a confirmed clinical diagnosis. Clinicians may reference the prediction results and make better decisions, improving the productivity of pulmonary function services by AI-assisted workflow.

Respiratory Oscillometry in Chronic Obstructive Pulmonary Disease: Association with Functional Capacity as Evaluated by Adl Glittre Test and Hand Grip Strength Test

Purpose

Respiratory oscillometry has emerged as a powerful method for detecting respiratory abnormalities in COPD. However, this method has not been widely introduced into clinical practice. This limitation arises, at least in part, because the clinical meaning of the oscillometric parameters is not clear. In this paper, we evaluated the association of oscillometry with functional capacity and its ability to predict abnormal functional capacity in COPD.

Patients and Methods

This cross-sectional study investigated a control group formed by 30 healthy subjects and 30 outpatients with COPD. The subjects were classified by the Glittre‑ADL test and handgrip strength according to the functional capacity.

Results

This study has shown initially that subjects with abnormal functional capacity had a higher value for resistance (p < 0.05), reactance area (Ax, p < 0.01), impedance modulus (Z4, p < 0.05), and reduced dynamic compliance (Cdyn, p < 0.05) when compared with subjects with normal functional capacity. This resulted in significant and consistent correlations among resistive oscillometric parameters (R=−0.43), Cdyn (R=−0.40), Ax (R = 0.42), and Z4 (R = 0.41) with exercise performance. Additionally, the effects of exercise limitation in COPD were adequately predicted, as evaluated by the area under the curve (AUC) obtained by receiver operating characteristic analysis. The best parameters for this task were R4-R20 (AUC = 0.779) and Ax (AUC = 0.752).

Conclusion

Respiratory oscillometry provides information related to functional capacity in COPD. This method is also able to predict low exercise tolerance in these patients. These findings elucidate the physiological and clinical meaning of the oscillometric parameters, improving the interpretation of these parameters in COPD patients.

Clinical significance and applications of oscillometry

Recently, “Technical standards for respiratory oscillometry” was published, which reviewed the physiological basis of oscillometric measures and detailed the technical factors related to equipment and test performance, quality assurance and reporting of results. Here we present a review of the clinical significance and applications of oscillometry. We briefly review the physiological principles of oscillometry and the basics of oscillometry interpretation, and then describe what is currently known about oscillometry in its role as a sensitive measure of airway resistance, bronchodilator responsiveness and bronchial challenge testing, and response to medical therapy, particularly in asthma and COPD. The technique may have unique advantages in situations where spirometry and other lung function tests are not suitable, such as in infants, neuromuscular disease, sleep apnoea and critical care. Other potential applications include detection of bronchiolitis obliterans, vocal cord dysfunction and the effects of environmental exposures. However, despite great promise as a useful clinical tool, we identify a number of areas in which more evidence of clinical utility is needed before oscillometry becomes routinely used for diagnosing or monitoring respiratory disease.

This paper provides a current review of the interpretation, clinical significance and application of oscillometry in respiratory medicine, with special emphasis on limitations of evidence and suggestions for future research.https://bit.ly/3GQPViA

Early Diagnosis and Real-Time Monitoring of Regional Lung Function Changes to Prevent Chronic Obstructive Pulmonary Disease Progression to Severe Emphysema

First- and second-hand exposure to smoke or air pollutants is the primary cause of chronic obstructive pulmonary disease (COPD) pathogenesis, where genetic and age-related factors predispose the subject to the initiation and progression of obstructive lung disease. Briefly, airway inflammation, specifically bronchitis, initiates the lung disease, leading to difficulty in breathing (dyspnea) and coughing as initial symptoms, followed by air trapping and inhibition of the flow of air into the lungs due to damage to the alveoli (emphysema). In addition, mucus obstruction and impaired lung clearance mechanisms lead to recurring acute exacerbations causing progressive decline in lung function, eventually requiring lung transplant and other lifesaving interventions to prevent mortality. It is noteworthy that COPD is much more common in the population than currently diagnosed, as only 16 million adult Americans were reported to be diagnosed with COPD as of 2018, although an additional 14 million American adults were estimated to be suffering from COPD but undiagnosed by the current standard of care (SOC) diagnostic, namely the spirometry-based pulmonary function test (PFT). Thus, the main issue driving the adverse disease outcome and significant mortality for COPD is lack of timely diagnosis in the early stages of the disease. The current treatment regime for COPD emphysema is most effective when implemented early, on COPD onset, where alleviating symptoms and exacerbations with timely intervention(s) can prevent steep lung function decline(s) and disease progression to severe emphysema. Therefore, the key to efficiently combatting COPD relies on early detection. Thus, it is important to detect early regional pulmonary function and structural changes to monitor modest disease progression for implementing timely interventions and effectively eliminating emphysema progression. Currently, COPD diagnosis involves using techniques such as COPD screening questionnaires, PFT, arterial blood gas analysis, and/or lung imaging, but these modalities are limited in their capability for early diagnosis and real-time disease monitoring of regional lung function changes. Hence, promising emerging techniques, such as X-ray phase contrast, photoacoustic tomography, ultrasound computed tomography, electrical impedance tomography, the forced oscillation technique, and the impulse oscillometry system powered by robust artificial intelligence and machine learning analysis capability are emerging as novel solutions for early detection and real time monitoring of COPD progression for timely intervention. We discuss here the scope, risks, and limitations of current SOC and emerging COPD diagnostics, with perspective on novel diagnostics providing real time regional lung function monitoring, and predicting exacerbation and/or disease onset for prognosis-based timely intervention(s) to limit COPD–emphysema progression.

Lung cancer dynamics using fractional order impedance modeling on a mimicked lung tumor setup

Introduction

As pulmonary dysfunctions are prospective factors for developing cancer, efforts are needed to solve the limitations regarding applications in lung cancer. Fractional order respiratory impedance models can be indicative of lung cancer dynamics and tissue heterogeneity.

Objective

The purpose of this study is to investigate how the existence of a tumorous tissue in the lung modifies the parameters of the proposed models. The first use of a prototype forced oscillations technique (FOT) device in a mimicked lung tumor setup is investigated by comparing and interpreting the experimental findings.

Methods

The fractional order model parameters are determined for the mechanical properties of the healthy and tumorous lung. Two protocols have been performed for a mimicked lung tumor setup in a laboratory environment. A low frequency evaluation of respiratory impedance model and nonlinearity index were assessed using the forced oscillations technique.

Results

The viscoelastic properties of the lung tissue change, results being mirrored in the respiratory impedance assessment via FOT. The results demonstrate significant differences among the mimicked healthy and tumor measurements, (p-values < 0.05) for impedance values and also for heterogeneity index. However, there was no significant difference in lung function before and after immersing the mimicked lung in water or saline solution, denoting no structural changes.

Conclusion

Simulation tests comparing the changes in impedance support the research hypothesis. The impedance frequency response is effective in non-invasive identification of respiratory tissue abnormalities in tumorous lung, analyzed with appropriate fractional models.

Combined forced oscillation and fractional-order modeling in patients with work-related asthma: a case-control study analyzing respiratory biomechanics and diagnostic accuracy

BACKGROUND

Fractional-order (FrOr) models have a high potential to improve pulmonary science. These models could be useful for biomechanical studies and diagnostic purposes, offering accurate models with an improved ability to describe nature. This paper evaluates the performance of the Forced Oscillation (FO) associated with integer (InOr) and FrOr models in the analysis of respiratory alterations in work-related asthma (WRA).

METHODS

Sixty-two individuals were evaluated: 31 healthy and 31 with WRA with mild obstruction. Patients were analyzed pre- and post-bronchodilation. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). To evaluate how well do the studied models correspond to observed data, we analyzed the mean square root of the sum (MSEt) and the relative distance (Rd) of the estimated model values to the measured resistance and reactance measured values.

RESULTS AND DISCUSSION

Initially, the use of InOr and FrOr models increased our understanding of the WRA physiopathology, showing increased peripheral resistance, damping, and hysteresivity. The FrOr model (AUC = 0.970) outperformed standard FO (AUC = 0.929), as well as InOr modeling (AUC = 0.838) in the diagnosis of respiratory changes, achieving high accuracy. FrOr improved the curve fitting (MSEt = 0.156 ± 0.340; Rd = 3.026 ± 1.072) in comparison with the InOr model (MSEt = 0.367 ± 0.991; Rd = 3.363 ± 1.098). Finally, we demonstrated that bronchodilator use increased dynamic compliance, as well as reduced damping and peripheral resistance.

CONCLUSIONS

Taken together, these results show clear evidence of the utility of FO associated with fractional-order modeling in patients with WRA, improving our knowledge of the biomechanical abnormalities and the diagnostic accuracy in this disease.

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.

Airway Oscillometry Detects Spirometric-Silent Episodes of Acute Cellular Rejection

Rationale: Acute cellular rejection (ACR) is common during the initial 3 months after lung transplant. Patients are monitored with spirometry and routine surveillance transbronchial biopsies. However, many centers monitor patients with spirometry only because of the risks and insensitivity of transbronchial biopsy for detecting ACR. Airway oscillometry is a lung function test that detects peripheral airway inhomogeneity with greater sensitivity than spirometry. Little is known about the role of oscillometry in patient monitoring after a transplant.Objectives: To characterize oscillometry measurements in biopsy-proven clinically significant (grade ≥2 ACR) in the first 3 months after a transplant.Methods: We enrolled 156 of the 209 double lung transplant recipients between December 2017 and March 2019. Weekly outpatient oscillometry and spirometry and surveillance biopsies at Weeks 6 and 12 were conducted at our center.Measurements and Main Results: Of the 138 patients followed for 3 or more months, 15 patients had 16 episodes of grade 2 ACR (AR2) and 44 patients had 64 episodes of grade 0 ACR (AR0) rejection associated with stable and/or improving spirometry. In 15/16 episodes of AR2, spirometry was stable or improving in the weeks leading to transbronchial biopsy. However, oscillometry was markedly abnormal and significantly different from AR0 (P < 0.05), particularly in integrated area of reactance and the resistance between 5 and 19 Hz, the indices of peripheral airway obstruction. By 2 weeks after biopsy, after treatment for AR2, oscillometry in the AR2 group improved and was similar to the AR0 group.Conclusions: Oscillometry identified physiological changes associated with AR2 that were not discernible by spirometry and is useful for graft monitoring after a lung transplant.

Clinical Application of Forced Oscillation Technique (FOT) in Early Detection of Airway Changes in Smokers

The forced oscillation technique (FOT) is a non-invasive method to assess airway function by emitting oscillatory signals into the respiratory tract during tidal ventilation. This opinion piece discusses the current use, trialled modification and future directions in utilizing FOT as a novel diagnostic tool for early detection of small airway changes in smokers. The published evidence to date has shown that FOT parameters could be a sensitive diagnostic tool to detect early respiratory changes in smokers. Multiple frequencies and the frequency dependence of resistance and reactance can provide the most valuable and early information regarding smoking induced changes in airways. Considering its non-invasiveness, lower level of discomfort to patients than spirometry, feasibility, and cost effectiveness, it could be the first-choice diagnostic technique for detection of early respiratory changes in smokers. The finding of FOT could further be supported and correlated with inflammatory markers.

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.

Respiratory resistance and reactance in adults with sickle cell anemia: Part 2-Fractional-order modeling and a clinical decision support system for the diagnosis of respiratory disorders

BACKGROUND

A better understanding of sickle cell anemia (SCA) and improvements in drug therapy and health policy have contributed to the emergence of a large population of adults living with this disease. The mechanisms by which SCA produces adverse effects on the respiratory system of these patients are largely unknown. Fractional-order (FrOr) models have a high potential to improve pulmonary clinical science and could be useful for diagnostic purposes, offering accurate models with an improved ability to mimic nature. Part 2 of this two-part study examines the changes in respiratory mechanics in patients with SCA using the new perspective of the FrOr models. These results are compared with those obtained in traditional forced oscillation (FOT) parameters, investigated in Part 1 of the present study, complementing this first analysis.

METHODOLOGY/PRINCIPAL FINDINGS

The data consisted of three categories of subjects: controls (n = 23), patients with a normal spirometric exam (n = 21) and those presenting restriction (n = 24). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Initially, it was observed that biomechanical changes in SCA included increased values of fractional inertance, as well as damping and hysteresivity (p<0.001). The correlation analysis showed that FrOr parameters are associated with functional exercise capacity (R = -0.57), pulmonary diffusion (R = -0.71), respiratory muscle performance (R = 0.50), pulmonary flows (R = -0.62) and airway obstruction (R = 0.60). Fractional-order modeling showed high diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.93), outperforming spirometry (p<0.03) and standard FOT analysis (p<0.01) used in Part 1 of this study. A combination of machine learning methods with fractional-order modeling further improved diagnostic accuracy (AUC = 0.97).

CONCLUSIONS

FrOr modeling improved our knowledge about the biomechanical abnormalities in adults with SCA. Changes in FrOr parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FrOr modeling outperformed spirometric and traditional forced oscillation analyses, showing a high diagnostic accuracy in the diagnosis of early respiratory abnormalities that was further improved by an automatic clinical decision support system. This finding suggested the potential utility of this combination to help identify early respiratory changes in patients with SCA.