A Soft Robot for Peripheral Lung Cancer Diagnosis and Therapy

Area of Science:

• Medical Robotics
• Biomedical Engineering
• Pulmonology

Background:

• Lung cancer diagnosis often relies on bronchoscopic biopsies, which struggle to reach peripheral lung regions.
• Current diagnostic tools have limited reachability in deep lung airways, potentially missing peripheral cancers.

Purpose of the Study:

• To design, model, fabricate, and test a novel soft robotic endoscope for enhanced lung cancer diagnosis.
• To enable navigation and intervention in deep lung periphery previously inaccessible to standard bronchoscopes.

Main Methods:

• Development of a one-degree-of-freedom soft robot (2.4mm diameter) with integrated diagnostics, intervention, and micro-camera vision sensing.
• Mechanical characterization (blocked force, bending angle, velocity, workspace) and in vitro/ex vivo performance assessment.
• Creation and validation of a computer vision algorithm for autonomous navigation, alignment, and lesion stabilization.

Main Results:

• The soft robotic endoscope demonstrated successful navigation in deep lung airways.
• Mechanical properties were characterized, and performance was validated in experimental settings.
• The computer vision algorithm enabled autonomous alignment and stabilization for diagnostic procedures.

Conclusions:

• The developed soft robotic endoscope offers improved reachability for diagnosing peripheral lung cancer.
• Integrated vision and autonomous control systems aid clinicians in navigating complex lung anatomy.
• This technology has the potential to improve early detection rates for lung cancer.