Sensory Airway Stent for Wireless Chip-free Sensing in the Airway

Introduction: : An airway stent is a medical device designed to provide support inside the human airway, ensuring its patency in case of airway narrowing or obstruction, such as tracheobronchomalacia and cancer. Monitoring stent patency and disease progression is crucial for effective treatment of airway diseases. However, existing airway stents are passive and lack the ability to sense stent status and biomarkers. To address this challenge, here we propose a chip-free sensory ring integrated to an airway stent to monitor stent patency and the airway tissue stiffness as a biomarker (Fig. 1A). The sensory ring allows tissue stiffness and airway pressure sensing enabled by a readout coil and analyzed using a Vector Network Analyzer (VNA) (Fig. 1B). The sensory ring consists of a capacitive tissue stiffness sensor, a capacitive magnetic sensor, a magnetic switch, and an inductor (Fig. 1C, D). An LC circuit is formed by the capacitive sensor and inductor, enabling resonant frequency capture by the VNA (Fig. 1E). The magnetic switch allows switching functions by connecting to various sensors (Fig. 1F). The readout signal in Fig. 1G shows a peak in the S11-frequency curve that correlates with the resonant frequency, used for deriving the sensor reading. Figure 1H depicts the experimental setup with a pickup coil above the sensor inductor. The sensory ring alone and integrated to an airway stent are shown in Fig. 1I and J. The proposed device is promising for long-term, and wireless sensing of airway conditions and airway stent patency in airway diseases.

Materials and

Methods: : First, the tissue stiffness sensor is composed of a conductive layer and a magnetic layer. The conductive layer is fabricated from a flexible copper film (Pyralux) and is patterned using an LPKF U4 machine. A layer of magnetic composite, is affixed to the non-conductive side of the copper film to enhance stiffness and mitigate undesired bending. Four permanent magnets, each measuring 1 mm in height and 1 mm in diameter, are glued onto the magnetic composite. A cylindrical resin probe is attached to the free end of the sensor.

Second, the fabrication process for the magnetic sensor mirrors that of the tissue stiffness sensor, but does not incorporate permanent magnets or the probe. Both sensors are affixed to a flexible circuit made from Pyralux. The copper pads that connect to the sensors are spin-coated with PDMS to ensure electrical insulation. Liquid dielectrics are introduced into the gap between the capacitive layer of the sensor and the pads of the circuit.

Third, the inductor for wireless communication is also made of Pyralux and patterned by the LPKF U4. A VNA machine is employed to communicate with the sensor wirelessly. A readout coil is positioned above the sensor inductor at about 2.5 cm for transmitting and receiving signals.

Lastly, to validate the stiffness sensing capabilities, testing samples of varying stiffness levels are prepared. These samples are made from Ecoflex 00-30 and Slacker in different weight ratios, with Slacker used to soften the polymer for a lower stiffness.

Results, Conclusions, and Discussions:: Result: The tissue stiffness sensor is shown in Fig. 2A and B. First, this probing process can be modeled using the Hertzian contact theory (Fig. 2C). The equivalent elastic modulus, assuming a small deflection, can be simplified as follows: E* = Bk/d, where B represents the applied magnetic field strength in the z-direction, d is the deflection, and k is a constant related to the probe's geometry and magnetization. As the distance between the two plates of the capacitor, d depends on the sensor’s capacitance (C), leading to a correlation between the sensor’s capacitance and tissue stiffness.

Second, the sensor is calibrated in terms of C and d (Fig. 2D) and subsequently tested on samples of varying stiffness under a given magnetic field (Fig. 2E). With the calibrated model in Fig. 2D, d is computed from the capacitance in Fig. 2F. These data serve as the ground truth to calibrate the unknown constant k by averaging across each set (Fig. 2G). Figure 2H shows that the predicted stiffness values align closely with the actual measurements.

Lastly, to validate the wireless sensing capability, a readout coil is positioned 2.5 cm above the sensor inductor. The collected S11 values within a varying magnetic field are displayed in Fig. 2J. The resonant frequency responses clearly show that the frequency-B curve for a softer sample decreases more rapidly than on a stiffer one. Furthermore, these resonant frequencies can be mapped back to sensor capacitance for estimating tissue stiffness.

Conclusion and discussion: We have reported a chip-free wireless sensing mechanism to monitor the conditions of airway tissue and the airway stents. This approach proves effective by demonstrating a consistent trend when the sensor is tested on samples of various elastic moduli. The sensor shows significant promise for miniaturized and resilient implantable devices due to its chip-free design. To facilitate practical applications of the device, signal transmission disturbance will be investigated, and the detection distance could be further improved by optimizing the on-board inductor coil. Future work will also focus on validating the biocompatibility, safety, and lifespan of the proposed sensory ring in animal models.

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