Real-time color flow mapping of ultrasound microrobots.

Journal: Science advances
Published Date: Jul 18, 2025

Abstract

Visualization and tracking of microrobots in real time pose key challenges for surgical microrobotic systems, as existing imaging modalities like magnetic resonance imaging, computed tomography, and x-ray are unable to monitor microscale items with real-time resolution. Ultrasound imaging-guided drug administration represents a remarkable advancement in this respect, offering real-time visual feedback on invasive medical procedures. However, ultrasound imaging still faces substantial inherent limitations in spatial resolution and signal attenuation, which hinder extending this method to microrobot visualization. Here, we introduce an approach for visualizing individual microrobots in real time with color flow mapping ultrasound imaging based on acoustically induced structural oscillations of the microrobot generating a pseudo-Doppler signal. This approach enables the simultaneous localization and activation of bubble-based microrobots using two ultrasound sources operating at distinct frequency bandwidths. Our successful capture of microrobots measuring 60 to 80 micrometers in diameter reveals the potential of real-time ultrasonic imaging at the microscale.

Authors

  • Cornel Dillinger
    Acoustic Robotics Systems Lab, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.
  • Ahilan Rasaiah
    Acoustic Robotics Systems Lab, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.
  • Abigail Vogel
    Acoustic Robotics Systems Lab, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.
  • Chaimae Bahou
    Functional Urology Research Group, Department for Biomedical Research, University of Bern, Bern, Switzerland.
  • Katia Monastyrskaya
    Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, 3008 Bern, Switzerland.
  • Ali Hashemi Gheinani
    Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, 3008 Bern, Switzerland.
  • Daniel Ahmed
    Acoustic Robotics Systems Lab, Institute or Robotics and Intelligent Systems, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland. dahmed@ethz.ch.

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