Wireless mobile technology to improve workflow and feasibility of MR-guided percutaneous interventions

  • Martin A. Rube
  • Andrew B. Holbrook
  • Benjamin F. Cox
  • Razvan Buciuc
  • Andreas Melzer
Original Article

Abstract

Purpose

   A wireless interactive display and control device combined with a platform-independent web-based user interface (UI) was developed to improve the workflow for interventional magnetic resonance imaging (iMRI).

Methods

   The iMRI-UI enables image acquisition of up to three independent slices using various pulse sequences with different contrast weighting. Pulse sequence, scan geometry and related parameters can be changed on the fly via the iMRI-UI using a tablet computer for improved lesion detection and interventional device targeting. The iMRI-UI was validated for core biopsies with a liver phantom (\(n\) \(=\) 40) and Thiel soft-embalmed human cadavers (\(n\) \(=\) 24) in a clinical 1.5T MRI scanner.

Results

   The iMRI-UI components and setup were tested and found conditionally MRI-safe to use according to current ASTM standards. Despite minor temporary touch screen interference at a close distance to the bore (\(<\)20 cm), no other issues regarding quality or imaging artefacts were observed. The 3D root-mean-square distance error was \(2.8\pm 1.0\) (phantom)/\(2.9 \pm 0.8\) mm (cadaver), and overall procedure times ranged between 12 and 22 (phantom)/20 and 55 min (cadaver).

Conclusion

   The wireless iMRI-UI control setup enabled fast and accurate interventional biopsy needle placements along complex trajectories and improved the workflow for percutaneous interventions under MRI guidance in a preclinical trial.

Keywords

Magnetic resonance imaging (MRI) Abdomen Image-guided liver intervention MR remote control Mobile web technology MRI-guided interventions 

Notes

Acknowledgments

The authors thank Joelle Barral, William Overall and Juan Santos (HeartVista, Inc., Palo Alto, CA, USA) for technical support and Fabiola Fernandez-Gutierrez for her support in statistical analysis. Special thanks also to John Ferut (GE Healthcare, Waukesha, WI), Tom Breslin and Gabor Mizsei (MR Instruments Inc., Minnetonka, MN, USA) for valuable input and kind support. The authors are thankful for financial assistance provided by the FUSIMO (“Patient specific modelling and simulation of focused ultrasound in moving organs”) project funded under the European Community’s Seventh Framework Programme (FP7/2007–2013) for Research and Technological Development under Grant Agreement No. 270186. The Marie Curie Initial Training Network -Integrated Interventional Imaging Operating System (IIIOS) funded the authors Martin A. Rube, Benjamin F. Cox, Andrew B. Holbrook and R. Buciuc and supported this work. The IIIOS project has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 238802. The authors also acknowledge the funding sources NIH R01-CA121163 and P01-CA159992.

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Copyright information

© CARS 2014

Authors and Affiliations

  • Martin A. Rube
    • 1
  • Andrew B. Holbrook
    • 2
  • Benjamin F. Cox
    • 1
  • Razvan Buciuc
    • 3
  • Andreas Melzer
    • 1
  1. 1.Division of Imaging and Technology, Institute for Medical Science and TechnologyUniversity of DundeeDundeeUK
  2. 2.Department of RadiologyStanford UniversityStanfordUSA
  3. 3.Department of RadiologyMaimonides Medical CenterBrooklynUSA

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