Researchers develop robotic sensory cilia that monitor internal biomarkers to detect and assess airway diseases

Xiaoguang Dong, assistant professor of mechanical engineering, is leading a team of researchers that has developed 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.

The research was published in the November 4 issue of PNAS in the article, "Sensory Artificial Cilia for In Situ Monitoring of Airway Physiological Properties."

In their paper, the researchers noted that continuously monitoring human airway conditions is crucial for timely interventions, especially when airway stents are implanted to alleviate central airway obstruction in lung cancer and other diseases. In particular, mucus conditions offer important biomarkers for indicating inflammation and stent patency but remain challenging to monitor. Current methods-reliant on computational tomography imaging and bronchoscope inspection-pose risks due to radiation and lack the ability to provide continuous real-time feedback outside of hospitals.

Mimicking the sensing ability of biological cilia, Dong and his team developed novel technology for detecting mucus conditions, including viscosity and layer thickness, which are crucial biomarkers for disease severity.

"The sensing mechanism for mucus viscosity leverages external magnetic fields to actuate a magnetic artificial cilium and sense its shape using a flexible strain-gauge," the researchers wrote. "Additionally, we report an artificial cilium with capacitance sensing for mucus layer thickness, offering unique self-calibration, adjustable sensitivity, and range, all enabled by external magnetic fields generated by a wearable magnetic actuation system."

The researchers tested the method by deploying the sensors independently or in conjunction with an airway stent within an artificial trachea and sheep trachea. Sensing signals are transferred wirelessly to a smart phone or the cloud for further data analysis and disease diagnosis.

"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," according to the study.

This work was done in collaboration with Vanderbilt University Medical Center faculty members Fabien Maldonado, professor of medicine and thoracic surgery; Caitlin Demarest, assistant professor Thoracic Surgery; and Caglar Oskay, chair of the Department of Civil and Environmental Engineering and Cornelius Vanderbilt Professor of Engineering. Yusheng Wang, the study's first author, is a third-year Ph.D. student in the Department of Mechanical Engineering.

Earlier this year, Dong was awarded an R21 Trailblazer Award by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health (NIH) to pursue a project about "Wirelessly Actuated Ciliary Stent for Minimally Invasive Treatment of Cilia Dysfunction."

The Trailblazer R21 Award supports new and early-stage investigators pursuing research programs that are of high interest to NIBIB, at the interface of life sciences with engineering and the physical sciences.