21.11.2024

Researchers led by Xiaoguang Dong, assistant professor of mechanical engineering at Vanderbilt University, have developed artificial cilia to monitor mucus conditions in human airways.

This system provides critical insights into the severity of diseases such as Cystic Fibrosis (CF), Chronic Obstructive Pulmonary Disease (COPD), and lung cancer by detecting biomarkers like mucus viscosity and layer thickness.

Image: Robotic sensory cilia to monitor internal biomarkers up close; Copyright: Vanderbilt University

A system of artificial cilia capable of monitoring mucus conditions in human airways to better detect infection, airway obstruction, or the severity of diseases like Cystic Fibrosis (CF), Chronic Obstructive Pulmonary Diseases (COPD) and lung cancer.

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Challenges in airway disease monitoring

Effective management of airway diseases often requires continuous monitoring of mucus properties, as these serve as key indicators of inflammation and disease progression. Current methods, such as CT imaging and bronchoscopy, are limited by radiation exposure and lack real-time monitoring capabilities outside hospital settings.

According to the research, the new system addresses these limitations. Mucus conditions offer important biomarkers for indicating inflammation and stent patency but remain challenging to monitor.

How the artificial cilia work

Inspired by biological cilia, the artificial system integrates innovative sensing mechanisms:

Mucus viscosity monitoring: Magnetic artificial cilia are actuated by external magnetic fields, and their shape is measured using a flexible strain gauge.

Layer thickness measurement: A capacitance-based sensor detects mucus layer thickness with self-calibration and adjustable sensitivity, also using magnetic actuation.

The system uses a wearable magnetic actuation device to generate the necessary external fields. Sensor data is wirelessly transmitted to a smartphone or cloud platform for real-time analysis, enabling early detection of airway disease and alerts for airway stent blockage.

Testing and applications

The team tested the sensors both independently and in conjunction with airway stents in artificial tracheas and sheep tracheas. The results demonstrated the technology’s ability to provide actionable data for disease diagnosis and stent maintenance.

“The proposed sensing mechanisms and devices pave the way for real-time monitoring of mucus conditions, facilitating early disease detection and providing stent patency alerts, thereby allowing timely interventions and personalized care,” the study states. These capabilities enable timely medical interventions and personalized care for patients with airway diseases.

Broader impact and future directions

The system’s potential extends beyond disease monitoring to improving the management of airway stents, a critical component in treating central airway obstructions caused by lung cancer and other diseases. By integrating wireless data transfer and continuous monitoring, the technology represents a step toward minimally invasive and proactive care.

Dong’s team collaborated with experts from Vanderbilt University Medical Center, including Fabien Maldonado, professor of medicine and thoracic surgery, and Caitlin Demarest, assistant professor of thoracic surgery. The study’s first author, Yusheng Wang, is a Ph.D. student in mechanical engineering at Vanderbilt.

MEDICA-tradefair.com; Source: Vanderbilt University

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