New Ultrasound Technology to Revolutionize Respiratory Disease Diagnoses

The thorax, situated between the neck and abdomen, serves as a critical zone for assessing respiratory health. Doctors rely on the analysis of sound vibrations created by airflow within the lungs and bronchial tree during regular breathing and sounds from the larynx during speech to spot possible issues within the respiratory system. However, traditional methods for assessing respiratory health can be subjective and depend heavily on the quality of the examination. While modern electronic stethoscopes have improved the detection of abnormalities during breathing, there's still a lack of technology for effectively analyzing the surface vibrations caused by vocalizations.

A team of researchers led by Austral Diagnostics (Paris, France) has now demonstrated the efficacy of a new ultrasound technology in detecting the subtle movements caused by vocalizations at the chest's surface. They also demonstrated the ability to map these vibrations during short durations to illustrate their evolution using "airborne ultrasound surface motion camera" (AUSMC). This innovative imaging tool captures the thorax surface vibrations at high speeds, around 1,000 frames per second, without direct contact with the skin. This approach shares the physical principle of conventional ultrasound Doppler imaging but does not require the application of a probe on the skin.

Image: The revolutionary ultrasound technology could transform the diagnostic of cardiac and pulmonary pathologies (Photo courtesy of Mathieu Couade)

In their study involving 77 healthy volunteers, the team used the AUSMC to visualize chest surface vibrations from natural vocalizations with the aim of reproducing the “vocal fremitus” – vocalization-induced vibrations on the surface of the body – that are usually analyzed during physical examination of the thorax. They observed that these induced surface vibrations were detectable in all participants. Interestingly, the spatial distribution of vibrational energy was uneven, skewing more to the right side of the chest and varying in frequency across the anteroposterior axis. Notably, the frequency distribution of vocalizations differed between men and women, with higher frequencies observed in women. Current clinical trials are employing the AUSMC to identify lung pathologies. Researchers are optimistic that integrating this technology with AI algorithms could revolutionize thorax examinations, allowing for a more detailed understanding of respiratory health and improving the diagnosis of respiratory conditions.

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