Dynamic Visualization of Breath Sound Distribution in Suspected Foreign Body Aspiration: A Pediatric Case Series

Vibration response imaging in healthy Japanese subjects

BACKGROUND

Vibration response imaging (VRI) records the intensity and distribution of lung sounds during the respiration cycle. Our objective was to analyze VRI findings in healthy Japanese adults.

METHODS

VRI images of 106 healthy subjects (33.7±9.6 years, 52 male and 54 female), including 67 nonsmokers and 39 asymptomatic smokers, were recorded. The regional intensity of vibrations was assessed using quantitative lung data (QLD), and VRI dynamic images by rater assessment, left and right lung asynchrony (gap index), and regional lung asynchrony (asynchrony score).

RESULTS

A dominance of total left lung QLD was observed in all subjects, and this phenomenon was more prominent in female subjects. However, there was no significant difference between the total left and total right lung QLD in smokers. Rater assessments showed that 81.1% of all subjects had a normal final assessment. Male subjects had a significantly higher percentage of good or normal assessments for all image scores, except dynamic image scoring. The asynchrony score was significantly higher in female subjects. There were no significant differences in these qualitative assessments between non-smokers and smokers.

CONCLUSIONS

Although our QLD results were similar to those of a previous report, there were discrepancies between sexes for the qualitative assessments. A significantly higher number of female subjects had abnormal images as assessed by the raters. Furthermore, significantly higher asynchrony scores were observed in female subjects. The VRI variability in sex may be considered normal among the Japanese population. This study is registered with UMIN-CTR under registration number UMIN000002355.

Computerised lung sound monitoring to assess effectiveness of chest physiotherapy and secretion removal: a feasibility study

OBJECTIVES

To explore the feasibility of computerised lung sound monitoring to evaluate secretion removal in intubated and mechanically ventilated adult patients.

DESIGN

Before and after observational investigation.

SETTING

Intensive care unit.

PARTICIPANTS

Fifteen intubated and mechanically ventilated adult patients receiving chest physiotherapy.

INTERVENTIONS

Chest physiotherapy included combinations of standard closed airway suctioning, saline lavage, postural drainage, chest wall vibrations, manual-assisted cough and/or lung hyperinflation, dependent upon clinical indications.

MAIN OUTCOME MEASURES

Lung sound amplitude at peak inspiration was assessed using computerised lung sound monitoring. Measurements were performed immediately before and after chest physiotherapy. Data are reported as mean [standard deviation (SD)], mean difference and 95% confidence intervals (CI). Significance testing was not performed due to the small sample size and the exploratory nature of the study.

RESULTS

Fifteen patients were included in the study [11 males, four females, mean age 65 (SD 14) years]. The mean total lung sound amplitude at peak inspiration decreased two-fold from 38 (SD 59) units before treatment to 17 (SD 19) units after treatment (mean difference 22, 95% CI of difference -3 to 46). The mean total lung sound amplitude from the lungs of patients with a large amount of secretions (n=9) was over four times 'louder' than the lungs of patients with a moderate or small amount of secretions (n=6) [56 (SD 72) units vs 12 (13) units, respectively; mean difference -44, 95% CI of difference -100 to 11]. The mean total lung sound amplitude decreased in the group of 'loud' right and left lungs (n=15) from 37 (SD 36) units before treatment to 15 (SD 13) units after treatment (mean difference 22, 95% CI of difference 6 to 38).

CONCLUSION

Computerised lung sound monitoring in this small group of patients demonstrated a two-fold decrease in lung sound amplitude following chest physiotherapy. Subgroup analysis also demonstrated decreasing trends in lung sound amplitude in the group of 'loud' lungs following chest physiotherapy. Due to the small sample size and large SDs with high variability in the lung sound amplitude measurements, significance testing was not reported. Further investigation is needed in a larger sample of patients with more accurate measurement of sputum wet weight in order to distinguish between secretion-related effects and changes due to other factors such as airflow rate and pattern.

Accuracy of gray-scale coding in lung sound mapping

Stethoscope evaluation of the lungs is widely accepted and practiced; however, there are some widely recognized, major limitations with its use. A safe device that helped solve these limitations by translating sound into objective, quantifiable images would have clinical utility. Translating lung sounds into quantifiable images in which regional differences or asymmetry in intensities of breath sounds are presented as gradients in gray-scale is not a trivial process. Healthy lungs and lung pathology are characterized by different patterns of regional breath sound distribution and, therefore, the accuracy of mapping gray-scale images must be ensured in a controlled systematic fashion prior to clinical use of such a technique. Vibration response imaging (VRI) maps lung sounds from 40 sensors to a two-dimensional gray-scale image. To assess mapping accuracy, a simulated lung sound map with uniform signals was compared to modified maps where sound signals were reduced (1-3db) at one sensor. Also, 8 readers evaluated the gray-scale images. The computer algorithm accurately displayed gray-scale coding changes in correct locations in 97% of images. There was 95+/-4% accuracy rate by readers to correctly identify gray-scale changes. In addition, quantitative data at different stages of signal processing were investigated in a LSM of a subject with asthma. Signal processing was 97% accurate overall in that the gray-scale values from which the image was derived corresponded with intensity values from recorded signals. These results suggest VRI accurately maps acoustic signals to a gray-scale image and that trained readers can detect small changes.

Evaluation of obstructive lung disease with vibration response imaging

As optimal treatment and prognosis differ between asthma and COPD, a new diagnostic approach to differentiating between the two disorders would be clinically desirable. We evaluated the utility of vibration response imaging in differentiating between asthma and COPD. Sixty-six subjects with asthma or COPD were recorded, before and after the administration of a short-acting bronchodilator, using a computerized lung sound analysis device. Gray-scale images of breath sound distribution in the lungs, quantitative data in breath sound graphs (timing, amplitude) and automatic crackle and wheeze detection programs were used to differentiate between asthma and COPD subjects. Imaging data were compared with the clinical diagnosis, made by the standard methods (medical history, physical examination, and spirometric indices). Blinded evaluation of images demonstrated a significantly higher rate of improvement in image dynamics, shape and overall improvement following bronchodilator in subjects with asthma compared with those with COPD. Quantitative data showed distinct patterns in timing and amplitude for these two pathologies. Combined analyses based on qualitative image evaluation and quantitative data demonstrated an overall 85% accuracy (84% for asthma, 86% for COPD) in differentiating between asthma and COPD. Combined qualitative and quantitative evaluations of lung sounds are quite sensitive in distinguishing between lung sound recordings of COPD and asthma individuals. Lung sound features of synchronization in timing and intensity provide objective data that may further differentiate these two airway disorders.

Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects

Computerized lung-sound analysis is a sensitive and quantitative method to identify wheezing by its typical pattern on spectral analysis. We evaluated the accuracy of the VRI, a multi-sensor, computer-based device with an automated technique of wheeze detection. The method was validated in 100 sound files from seven subjects with asthma or chronic obstructive pulmonary disease and seven healthy subjects by comparison of auscultation findings, examination of audio files, and computer detection of wheezes. Three blinded physicians identified 40 sound files with wheezes and 60 sound files without wheezes. Sensitivity and specificity were 83% and 85%, respectively. Negative predictive value and positive predictive value were 89% and 79%, respectively. Overall inter-rater agreement was 84%. False positive cases were found to contain sounds that simulate wheezes, such as background noises with high frequencies or strong noises from the throat that could be heard and identified without a stethoscope. The present findings demonstrate that the wheeze detection algorithm has good accuracy, sensitivity, specificity, negative predictive value and positive predictive value for wheeze detection in regional analyses with a single sensor and multiple sensors. Results are similar to those reported in the literature. The device is user-friendly, requires minimal patient effort, and, distinct from other devices, it provides a dynamic image of breath sound distribution with wheeze detection output in less than 1 minute.

Assessment of asymmetric lung disease in intensive care unit patients using vibration response imaging

BACKGROUND

Vibration response imaging (VRI) is a computer-based technology that creates a visual dynamic two-dimensional image of distribution of vibration within the lung during the respiratory process. The acoustic signals, recorded from 36 posteriorly positioned surface skin sensors, are transferred to a hardware board where several stages of filtering are applied to select a specific frequency band. The filtered output signal frequencies are presented as a gray-scale coded dynamic image, consisting of a series of 0.17 s frames, and as a table featuring the percentage contribution of each lung to the total vibration signal.

METHODS

We describe the VRI technology in detail and examine images obtained from consecutive intensive care unit (ICU) patients with one diseased lung on chest radiograph. ICU patients with normal chest radiographs are presented as controls. Analysis of the image was performed by comparing the weighted pixel count analysis from both lungs. In this method, the pixels in the image were assigned values based on their grayscale color with the darker pixels assigned higher values.

RESULTS

In patients with normal chest radiographs, the right and left lungs developed similarly in dynamic VRI images, and the percent lung vibrations from both sides were comparable (53%+/-12% and 47%+/-12%, respectively). In ICU patients with asymmetric lung disease, however, the percent lung vibrations from the diseased and nondiseased lungs were 27%+/-23% and 73%+/-23%, respectively (P<0.001). In patients with asymmetric lung disease (one lung has moderate to severe disease and the other appears normal or close to normal as per chest radiograph), the diseased lung usually appeared in VRI as irregular, smaller, and lighter in color (reduced vibration signal) when compared to the nonaffected lung. The weighted pixel count from diseased and nondiseased lungs were 33%+/-21% and 67%+/-21%, respectively (P < 0.003).

CONCLUSION

The VRI technology may provide a radiation-free method for identifying and tracking of asymmetric lung parenchymal processes.

Case report: vibration response imaging findings following inadvertent esophageal intubation

PURPOSE

We describe the effect that inadvertent esophageal intubation has on the images and on the vibration distribution of vibration response imaging (VRI).

CLINICAL FEATURES

Vibration response imaging (VRI) is a novel, non-invasive, computer-based technology that measures vibration energy of lung sounds during respiration and displays regional intensity, in both visual and graphic format. Vibration response images, obtained prior to tracheal intubation (spontaneous breathing) and during endotracheal ventilation using a controlled mode, resulted in evenly distributed vibrations throughout the patient's lungs. During inadvertent esophageal ventilation, however, the majority of vibrations were detected in the upper regions of the image, compared to those of the lower (60% vs 8%, respectively). During spontaneous breathing and endotracheal ventilation, the midclavicular column of sensors, located over the centre of each lung, detected more vibrations compared to either the medial or the axillary column of sensors. During inadvertent esophageal ventilation, more vibrations were detected by the medial column of sensors (nearest to the midline/esophagus); and fewer were detected by the sensors that were positioned more laterally.

CONCLUSION

This report illustrates the potential for a visual image of distribution of lung vibration energy to differentiate endotracheal intubation from inadvertent esophageal intubation.