Skip to main content

Towards Autonomous Robotic Procedure for Ultrasound-Guided Percutaneous Cardiac Interventions for Mitral Valve Repair

  • Conference paper
  • First Online:
European Robotics Forum 2024 (ERF 2024)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 33))

Included in the following conference series:

  • 44 Accesses

Abstract

The paper outlines the early stages of a robotic platform designed to improve safety and repeatability of Transcatheter Edge-to-Edge Repair (TEER) procedures. The platform integrates artificial intelligence (AI) software for image interpretation, sensor-equipped catheters for virtual monitoring, robotic actuators for manipulation, and a mixed-reality interface for real-time monitoring. The AI software can automatically identify Mitral Valve (MV) anatomical features from ultrasound images. The platform also includes a path planning module and an inverse kinematic controller for safe navigation. The use of novel sensors and automatic actuation allows for precise control. Real-time simulation of the catheter’s interactions provides accurate analysis of anatomical deformations. These developments represent significant progress in percutaneous intracardiac procedures, with the potential to make TEER procedures safer and more accessible.

A. Peloso, R. Munafò, E. De Momi and E. Votta—These authors contributed in the same way.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Munafò, R., et al.: A deep learning-based fully automated pipeline for regurgitant mitral valve anatomy analysis from 3D echocardiography. IEEE Access (2024)

    Google Scholar 

  2. Kerfoot, E., Clough, J., Oksuz, I., Lee, J., King, A., Schnabel, J.: Left-ventricle quantification using residual U-Net. Statistical Atlases and Computational Models of the Heart (2019)

    Google Scholar 

  3. Ho, J., Ermon, S.: Generative adversarial imitation learning. In: Advances in Neural Information Processing Systems (2016)

    Google Scholar 

  4. Zhang, X., et al.: Robotic actuation and control of a catheter for structural intervention cardiology. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE (2022)

    Google Scholar 

  5. Ha, X.T., et al.: Robust catheter tracking by fusing electromagnetic tracking, fiber Bragg grating and sparse fluoroscopic images. IEEE Sens. J. (2021). https://doi.org/10.1109/JSEN.2021.3107036

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Angela Peloso .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Peloso, A. et al. (2024). Towards Autonomous Robotic Procedure for Ultrasound-Guided Percutaneous Cardiac Interventions for Mitral Valve Repair. In: Secchi, C., Marconi, L. (eds) European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-031-76428-8_72

Download citation

Publish with us

Policies and ethics