Every year pneumonia is the cause of death for over a million people worldwide, with most of these deaths occurring in areas that do not have access to advanced medical infrastructure. The current clinical gold standard for detecting pneumonia is a chest x-ray, which, while effective for diagnosis, is often unavailable to patients in resource limited settings due to inhibitive financial costs. For these populations, physical examinations provide an accessible, convenient, and low-cost alternative---thus, all doctors are trained to perform the physical exam. The physical exam technique of percussion is performed by tapping specific areas of the back and assessing whether the resulting sound corresponds to healthy or diseased tissue. Unfortunately, differences in physician technique lead to inconsistent findings and dismissal of the percussion method when x-ray machines are available. The goal of our device is to quantify these findings to eliminate interobserver error and harness the diagnostic power of percussion to provide a low-cost, quantitative physical examination tool for the diagnosis of pneumonia in patient populations with limited access to chest radiography. We have developed a prototype device that provides acoustic stimulation to the chest; sound is recorded from the back using an electronic stethoscope and this recording is used to estimate the chest cavity's acoustic transfer function. The transfer function characterizes the strength of response of a system to different frequencies and can be used to distinguish between different systems.
Our specific aims focus on developing a method to study the effects on the acoustic transfer function due to structural changes in the lungs during pneumonia (Aim 1) and to explore the generalizability of this approach to pneumothorax specifically as well as other lung pathologies (Aim 2).
In Aim 1, we hypothesize that the accumulation of exudate (fluid) in a lobe of the lungs in pneumonia will lead to better sound transmission of higher frequencies compared to healthy lung. First, we will use a sponge with similar density to human lung tissue as an imaging phantom to improve our device's signal-to-noise ratio and streamline data analysis. Second, we will perform our experiments in patients comparing the healthy side of their lungs to the side with lobar pneumonia. Finally, we will develop a classifier that can take additional variables such as age and gender into consideration to improve performance of our test and return a severity score of pneumonia based on acoustic findings.
For Aim 2, our hypothesis is that the accumulation of air in pleural spaces will reduce transmission of sound, especially at higher frequencies. We will first perform an experiment with an air-filled cavity (stomach) compared to solid tissue (knee) to determine the effect of air accumulation on the transfer function. Next, as in Aim 1, we will perform tests on patients comparing the side with the pneumothorax to the healthy side. Finally, we will develop a classifier to provide a severity score of pneumothorax. We anticipate that the findings from our studies will provide novel insight into the feasibility of acoustic diagnosis of pneumonia and pneumothorax.

Public Health Relevance

Every year, millions of adults and children die of pneumonia -- most in areas without access to chest x-rays. The goal of this proposal is to detect pneumonia using acoustic technology in a portable hardware platform providing care to regions without access to advanced medical infrastructure. While the current focus is on reliable diagnosis of pneumonia and pneumothorax, this work may provide insight into diagnosis of other pulmonary pathologies such as COPD, and atelectasis.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
5F30HL140906-03
Application #
9875473
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Kalantari, Roya
Project Start
2018-02-01
Project End
2022-01-31
Budget Start
2020-02-01
Budget End
2021-01-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Rao, Adam; Ruiz, Jorge; Bao, Chen et al. (2018) Tabla: A Proof-of-Concept Auscultatory Percussion Device for Low-Cost Pneumonia Detection. Sensors (Basel) 18:
Rao, Adam; Huynh, Emily; Royston, Thomas et al. (2018) Acoustic Methods for Pulmonary Diagnosis. IEEE Rev Biomed Eng :
Rao, Adam; Chu, Simon; Batlivala, Neil et al. (2018) Improved Detection of Lung Fluid With Standardized Acoustic Stimulation of the Chest. IEEE J Transl Eng Health Med 6:3200107