Literature DB >> 31832907

Development of a robot-assisted ultrasound-guided radiation therapy (USgRT).

Peter Karl Seitz1,2, Beatrice Baumann3, Wibke Johnen4, Cord Lissek3, Johanna Seidel3, Rolf Bendl4,3.   

Abstract

PURPOSE: Radiation treatment is improved by the use of image-guided workflows. This work pursues the approach of using ultrasound (US) as a real-time imaging modality. The primary focus of this study is to develop and test a breathing and motion control for a robotic-guided US transducer. All control functions of the robot and the US image processing were then integrated into one software platform enabling US-guided radiation therapy.
METHODS: The robot (KUKA LBR iiwa 7 R800) and the US image processing workflows were integrated into the Medical Interaction Toolkit (MITK) (Nolden et al. in Int J Comput Assist Radiol Surg 8(4):607-620, 2013). The positions of the US probe were tracked with an optical tracking system. As a main function of robot positioning control, a highly sensitive breathing and motion compensation method was developed using KUKA's robotic application programming interface. The resulting autonomous robot motions were tested by the use of defined breathing patterns with two volunteers. Furthermore, a filter pipeline for 3D US image processing with MITK was developed. Thus, image registration of US images and previously acquired planning image data was enabled.
RESULTS: The implemented breathing and motion compensation feature was successful with the addition of the remote rotating, translating capability of the US probe. Desired force applied to the US probe, and thus to the patient, is stable and enables a continuous US imaging. The developed filter pipeline for image processing facilitates registration and display of planning data and US image data in one graphical user interface.
CONCLUSION: A stable and robust method for motion compensation for robot-assisted US imaging was developed and tested successfully. This is a first step toward the safe use of autonomous robot motions in interaction with patients. Furthermore, main software components were integrated into a single platform and used with the purpose of ultrasound-guided radiation therapy.

Entities:  

Keywords:  Combining modalities; Image-guided radiation therapy (IGRT); Robotic; Ultrasound

Mesh:

Year:  2019        PMID: 31832907     DOI: 10.1007/s11548-019-02104-y

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  1 in total

Review 1.  Ultrasound Imaging in Radiation Therapy: From Interfractional to Intrafractional Guidance.

Authors:  Craig Western; Dimitre Hristov; Jeffrey Schlosser
Journal:  Cureus       Date:  2015-06-20
  1 in total
  6 in total

1.  Automatic ultrasound scanning robotic system with optical waveguide-based force measurement.

Authors:  Shihang Chen; Zhaojun Li; Yanping Lin; Fang Wang; Qixin Cao
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-05-03       Impact factor: 2.924

2.  Landmark tracking in 4D ultrasound using generalized representation learning.

Authors:  Daniel Wulff; Jannis Hagenah; Floris Ernst
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-10-15       Impact factor: 3.421

3.  The Essential Role of Open Data and Software for the Future of Ultrasound-Based Neuronavigation.

Authors:  Ingerid Reinertsen; D Louis Collins; Simon Drouin
Journal:  Front Oncol       Date:  2021-02-02       Impact factor: 6.244

4.  Risk Assessment-Oriented Design of a Needle Insertion Robotic System for Non-Resectable Liver Tumors.

Authors:  Bogdan Gherman; Nadim Al Hajjar; Paul Tucan; Corina Radu; Calin Vaida; Emil Mois; Alin Burz; Doina Pisla
Journal:  Healthcare (Basel)       Date:  2022-02-18

5.  Systematic analysis of volumetric ultrasound parameters for markerless 4D motion tracking.

Authors:  Johanna Sprenger; Marcel Bengs; Stefan Gerlach; Maximilian Neidhardt; Alexander Schlaefer
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-05-21       Impact factor: 3.421

Review 6.  Robot-Assisted Image-Guided Interventions.

Authors:  Michael Unger; Johann Berger; Andreas Melzer
Journal:  Front Robot AI       Date:  2021-07-12
  6 in total

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