Acoustic biomarkers of Chronic Obstructive Lung Disease

We used a multichannel lung sound analyzer that provides acoustic data from multiple sites on the chest wall to study 90 patients diagnosed by their physicians as having COPD. Their findings were compared to 90 age matched controls who presented themselves to an internist for their annual physical examination. We calculated over 100 parameters for each subject. Eleven parameters of these parameters were statistically different between COPD and control patients: Inspiratory and expiratory crackle rate as well as inspiratory and expiratory wheeze/rhonchi rate was greater in COPD. Ratio of the duration of inspiration to the duration of expiration was smaller in COPD. Ratio of peak inspiratory amplitude to peak expiratory amplitude was smaller in COPD. Ratio of low frequency inspiratory energy to ‡ §


New information
We used a multichannel lung sound analyzer that provides acoustic data from multiple sites on the chest wall to study 90 patients diagnosed by their physicians as having COPD.Their findings were compared to 90 age matched controls who presented themselves to an internist for their annual physical examination.We calculated over 100 parameters for each subject.Eleven parameters of these parameters were statistically different between COPD and control patients: Inspiratory and expiratory crackle rate as well as inspiratory and expiratory wheeze/rhonchi rate was greater in COPD.Ratio of the duration of inspiration to the duration of expiration was smaller in COPD.Ratio of peak inspiratory amplitude to peak expiratory amplitude was smaller in COPD.Ratio of low frequency inspiratory energy to

Introduction
The goal of this study was to determine lung sounds-derived biomarkers that distinguished Chronic Obstructive Pulmonary Disease patients from age-matched controls.We quantified time and frequency based acoustic parameters using multiple microphones placed on the chest surface.

Methods
We used a multichannel lung sound analyzer to study 90 patients diagnosed by their physicians as having Chronic Obstructive Pulmonary Disease.The acoustic findings in these patients were compared to those in 90 age matched controls who presented to an internist for an annual physical examination.We calculated over 100 parameters for each subject.Eleven parameters were statistically different between COPD and control patients: 1.
Ratio of the duration of inspiration to the duration of expiration (%) 2.
Lead -the difference in timing between the start of inspiration at the trachea and the start of inspiration at each chest wall site (% of inspiration duration) 3.
Lag -the difference in timing between the end of inspiration at the trachea and the end of inspiration at each chest wall site (% of inspiration duration) 4.
Maximum ratio of low frequency energy (between 10Hz and 80Hz) to high frequency energy (80Hz to 500Hz) among chest microphones 7.
Ratio of peak inspiratory amplitude to peak expiratory amplitude The eleven parameters are further explained in Fig. 1 Biomarkers 2 and 3: Lead and Lag

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In patients with regional variations in resistance and elastance gas moves at the beginning of inspiration out of some alveoli into others.

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Gas moves in the opposite direction at the end of inspiration.

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This phenomenon, referred to as pendelluft, was described over five decades ago.

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Lung sounds express the phenomenon of pendelluft as increased sound amplitude at the beginning (Lead) and at the end of inspiration (Lag).• See detailed discussion of these two parameters in Vyshedskiy and Murphy (2012).

Biomarkers 4 and 5: Lead and Lag time-integrated amplitude
• Sound amplitude is proportional to gas flow over the region of recording.• Time integrated amplitude is proportional to gas volume.

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Lead time integrated amplitude should be proportional to the regional gas volume movement at the start of inspiration.

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Lag time integrated amplitude should be proportional to the regional gas volume movement at the end of inspiration.

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It is another way to measure the degree of pendelluft in COPD patients.
Biomarker 6: Ratio of low frequency to high freq.energy

• Low frequency energy (light green area) is divided by high frequency energy (light blue). •
The ratio is increased when there is a peak at low frequency.

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The mechanism of the increased low frequency vibrations in COPD is unknown.Poster as it was presented at the conference.Please see text for details.
• A possible explanation is that it may be due to the relatively increased size of the air spaces in the lung of COPD patients as we have noted a similar increase in low frequency peaks in patients with pneumothorax and pneumonectomy as well in a patient with a giant bulla.

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Increased low frequency vibrations in COPD might also be explained by increased activity of the skeletal muscles of the thorax.

Results and discussion
Eleven parameters were statistically different between COPD and control patients (Table 1).

Table 1 .
Summary of the Automated Acoustical Data Analysis