Evaluation of airflow limitation using a new modality of lung sound analysis in asthmatic children

A machine learning approach to the development and prospective evaluation of a pediatric lung sound classification model

Auscultation, a cost-effective and non-invasive part of physical examination, is essential to diagnose pediatric respiratory disorders. Electronic stethoscopes allow transmission, storage, and analysis of lung sounds. We aimed to develop a machine learning model to classify pediatric respiratory sounds. Lung sounds were digitally recorded during routine physical examinations at a pediatric pulmonology outpatient clinic from July to November 2019 and labeled as normal, crackles, or wheezing. Ensemble support vector machine models were trained and evaluated for four classification tasks (normal vs. abnormal, crackles vs. wheezing, normal vs. crackles, and normal vs. wheezing) using K-fold cross-validation (K = 10). Model performance on a prospective validation set (June to July 2021) was compared with those of pediatricians and non-pediatricians. Total 680 clips were used for training and internal validation. The model accuracies during internal validation for normal vs. abnormal, crackles vs. wheezing, normal vs. crackles, and normal vs. wheezing were 83.68%, 83.67%, 80.94%, and 90.42%, respectively. The prospective validation (n = 90) accuracies were 82.22%, 67.74%, 67.80%, and 81.36%, respectively, which were comparable to pediatrician and non-pediatrician performance. An automated classification model of pediatric lung sounds is feasible and maybe utilized as a screening tool for respiratory disorders in this pandemic era.

Wheezing Characteristics and Predicting Reactivity to Inhaled β2-Agonist in Children for Home Medical Care

Background: Given that wheezing is treated with inhaled β2-agonists, their effect should be reviewed before the condition becomes severe; however, few methods can currently predict reactivity to inhaled β2-agonists. We investigated whether preinhalation wheezing characteristics identified by lung sound analysis can predict reactivity to inhaled β2-agonists. Methods: In 202 children aged 10-153 months, wheezing was identified by auscultation. Lung sounds were recorded for 30 s in the chest region on the chest wall during tidal breathing. We analyzed the wheezing before and after β2-agonist inhalation. Wheezing was displayed as horizontal bars of intensity defined as a wheeze power band, and the wheezing characteristics (number, frequency, and maximum intensity frequency) were evaluated by lung sound analysis. The participants were divided into two groups: non-disappears (wheezing did not disappear after inhalation) and disappears (wheezing disappeared after inhalation). Wheezing characteristics before β2-agonist inhalation were compared between the two groups. The characteristics of wheezing were not affected by body size. The number of wheeze power bands of the non-responder group was significantly higher than those of the responder group (P < 0.001). The number of wheeze power bands was a predictor of reactivity to inhaled β2-agonists, with a cutoff of 11.1. The 95% confidence intervals of sensitivity, specificity, and positive and negative predictive values were 88.8, 42, 44, and 81.1% (P < 0.001), respectively. Conclusions: The number of preinhalation wheeze power bands shown by lung sound analysis was a useful indicator before treatment. This indicator could be a beneficial index for managing wheezing in young children.

Treatment evaluation using lung sound analysis in asthmatic children

BACKGROUND AND OBJECTIVE

Non-invasive assessment of treatment and prediction of attacks in asthmatic children do not yet exist. Lung sound analysis can non-invasively evaluate airway obstruction. We used a recently developed technology for analysing lung sounds using ic700 (index of the chest wall at 700 Hz, sound intensity at 700 Hz) to evaluate response to inhaled corticosteroid (ICS) in asthmatic children.

METHOD

Seventy asthmatic children, including infants, underwent lung sound recording in the asymptomatic state prior to and 1, 2, 4, 6 and 8 weeks after ICS treatment, and asthma control was assessed at 10 weeks. The ic700 scores at 4, 6 and 8 weeks were compared with the presence of attack during the following 2 weeks. Subjects were divided into uncontrolled and well-controlled groups.

RESULTS

The mean ic700 scores of all subjects significantly reduced after 8 weeks of treatment. The mean scores of the uncontrolled group were significantly higher than those of the well-controlled group at 4, 6 and 8 weeks after starting treatment. The ic700 cut-off value for predicting asthma attacks within 2 weeks following the evaluation was set at 0.0. After 6 weeks of treatment, the area under the curve was 0.92 ± 0.04; the sensitivity, specificity and positive and negative predictive values were 83%, 88% and 88% and 84%, respectively. Similar results were observed at 4 and 8 weeks.

CONCLUSION

The ic700 score is useful in assessing the effects of ICS treatment, predicting attack symptoms and identifying asymptomatic asthmatic children at a high risk for asthma attack.

Lung sound analysis helps localize airway inflammation in patients with bronchial asthma

Purpose

Airway inflammation can be detected by lung sound analysis (LSA) at a single point in the posterior lower lung field. We performed LSA at 7 points to examine whether the technique could identify the location of airway inflammation in patients with asthma.

Patients and methods

Breath sounds were recorded at 7 points on the body surface of 22 asthmatic subjects. Inspiration sound pressure level (I_SPL), expiration sound pressure level (E_SPL), and the expiration-to-inspiration sound pressure ratio (E/I) were calculated in 6 frequency bands. The data were analyzed for potential correlation with spirometry, airway hyperresponsiveness (PC₂₀), and fractional exhaled nitric oxide (FeNO).

Results

The E/I data in the frequency range of 100–400 Hz (E/I low frequency [LF], E/I mid frequency [MF]) were better correlated with the spirometry, PC₂₀, and FeNO values than were the I_SPL or E_SPL data. The left anterior chest and left posterior lower recording positions were associated with the best correlations (forced expiratory volume in 1 second/forced vital capacity: r=−0.55 and r=−0.58; logPC₂₀: r=−0.46 and r=−0.45; and FeNO: r=0.42 and r=0.46, respectively). The majority of asthmatic subjects with FeNO ≥70 ppb exhibited high E/I MF levels in all lung fields (excluding the trachea) and V₅₀%pred <80%, suggesting inflammation throughout the airway. Asthmatic subjects with FeNO <70 ppb showed high or low E/I MF levels depending on the recording position, indicating uneven airway inflammation.

Conclusion

E/I LF and E/I MF are more useful LSA parameters for evaluating airway inflammation in bronchial asthma; 7-point lung sound recordings could be used to identify sites of local airway inflammation.

A clinical method for detecting bronchial reversibility using a breath sound spectrum analysis in infants

BACKGROUND

Using a breath sound analyzer, we investigated clinical parameters for detecting bronchial reversibility in infants.

METHODS

A total of 59 infants (4-39 months, mean age 7.8 months) were included. In Study 1, the intra- and inter-observer variability was measured in 23 of 59 infants. Breath sound parameters, the frequency at 99% of the maximum frequency (F₉₉), frequency at 25%, 50%, and 75% of the power spectrum (Q₂₅, Q₅₀, and Q₇₅), and highest frequency of inspiratory breath sounds (HFI), and parameters obtained using the ratio of parameters, i.e. spectrum curve indices, the ratio of the third and fourth area to total area (A₃/A_T and B₄/A_T, respectively) and ratio of power and frequency at F₇₅ and F₅₀ (RPF₇₅ and RPF₅₀), were calculated. In Study 2, the relationship between parameters of breath sounds and age and stature were studied. In Study 3, breath sounds were studied before and after β₂ agonist inhalation.

RESULTS

In Study 1, the data showed statistical intra- and inter-observer reliability in A₃/A_T (p=0.042 and 0.034, respectively) and RPF₅₀ (p=0.001 and 0.001, respectively). In Study 2, there were no significant relationships between age, height, weight, and BMI. In Study 3, A₃/A_T and RPF₅₀ significantly changed after β₂ agonist inhalation (p=0.001 and p<0.001, respectively).

CONCLUSIONS

Breath sound analysis can be performed in infants, as in older children, and the spectrum curve indices are not significantly affected by age-related factors. These sound parameters may play a role in the assessment of bronchial reversibility in infants.

Changes in lung sounds during asthma progression in a guinea pig model

BACKGROUND

Lung sound analysis is useful for objectively evaluating airways even in children with asymptomatic asthma. However, the relationship between lung sounds and morphological changes in the airways has not been elucidated. We examined the relationship between lung sounds and chronic morphological changes in the airways during the progression of asthma from onset in guinea pigs.

METHODS

Eleven male guinea pigs were examined; of these, seven were used as asthma models and four as controls. The asthma models were sensitized and repeatedly challenged by inhaling albumin chicken egg. We measured lung sounds and lung function twice a week for 21 weeks. After the final antigen challenge, the lungs were excised for histological examination. We measured the ratio of airway wall thickness to the total airway area and the ratio of the internal area to the total airway area in the trachea, third bronchi, and terminal bronchioles.

RESULTS

Among the lungs sounds, the difference between the two groups was greatest with respect to inspiratory sound intensity. The ratio of airway wall thickness to the total airway area of the terminal bronchioles was greater in the asthma models than in the controls, and it correlated best with the changes in inspiratory sound intensity in the 501-1000-Hz range (r = 0.76, p < 0.003).

CONCLUSIONS

Lung sound intensity in the middle frequency range from 501 to 1000 Hz correlated with peripheral airway wall thickness. Inspiratory sound intensity appeared to be an indicator of morphological changes in small airways in asthma.