Literature DB >> 31607756

Reducing RF-induced Heating near Implanted Leads through High-Dielectric Capacitive Bleeding of Current (CBLOC).

Laleh Golestanirad1, Leonardo M Angelone2, John Kirsch3, Sean Downs3, Boris Keil4, Giorgio Bonmassar3, Lawrence L Wald3.   

Abstract

Patients with implanted medical devices such as deep brain stimulation or spinal cord stimulation are often unable to receive magnetic resonance imaging (MRI). This is because once the device is within the radiofrequency (RF) field of the MRI scanner, electrically conductive leads act as antenna, amplifying the RF energy deposition in the tissue and causing possible excessive tissue heating. Here we propose a novel concept in lead design in which 40cm lead wires are coated with a ~1.2mm layer of high dielectric constant material (155 < ε r < 250) embedded in a weakly conductive insulation (σ = 20S/m). The technique called High-Dielectric Capacitive Bleeding of Current, or CBLOC, works by forming a distributed capacitance along the lengths of the lead, efficiently dissipating RF energy before it reaches the exposed tip. Measurements during RF exposure at 64 MHz and 123 MHz demonstrated that CBLOC leads generated 20-fold less heating at 1.5 T, and 40-fold less heating at 3 T compared to control leads. Numerical simulations of RF exposure at 297 MHz (7T) predicted a 15-fold reduction in specific absorption rate (SAR) of RF energy around the tip of CBLOC leads compared to control leads.

Entities:  

Keywords:  MR Conditional; RF heating; RF safety; electrode leads; finite element method; high dielectric material; high field; magnetic resonance imaging (MRI); medical implants; numerical simulations; specific absorption rate (SAR)

Year:  2019        PMID: 31607756      PMCID: PMC6788634          DOI: 10.1109/TMTT.2018.2885517

Source DB:  PubMed          Journal:  IEEE Trans Microw Theory Tech        ISSN: 0018-9480            Impact factor:   3.599


  42 in total

1.  Neurostimulation systems for deep brain stimulation: in vitro evaluation of magnetic resonance imaging-related heating at 1.5 tesla.

Authors:  Ali R Rezai; Daniel Finelli; John A Nyenhuis; Greg Hrdlicka; Jean Tkach; Ashwini Sharan; Paul Rugieri; Paul H Stypulkowski; Frank G Shellock
Journal:  J Magn Reson Imaging       Date:  2002-03       Impact factor: 4.813

2.  Temperature and SAR calculations for a human head within volume and surface coils at 64 and 300 MHz.

Authors:  Christopher M Collins; Wanzhan Liu; Jinghua Wang; Rolf Gruetter; J Thomas Vaughan; Kamil Ugurbil; Michael B Smith
Journal:  J Magn Reson Imaging       Date:  2004-05       Impact factor: 4.813

3.  In vitro investigation of pacemaker lead heating induced by magnetic resonance imaging: role of implant geometry.

Authors:  Giovanni Calcagnini; Michele Triventi; Federica Censi; Eugenio Mattei; Pietro Bartolini; Wolfgang Kainz; Howard I Bassen
Journal:  J Magn Reson Imaging       Date:  2008-10       Impact factor: 4.813

4.  Evaluation of cumulative effects of MR imaging on pacemaker systems at 1.5 Tesla.

Authors:  Claas P Naehle; Volkert Zeijlemaker; Daniel Thomas; Carsten Meyer; Katharina Strach; Rolf Fimmers; Hans Schild; Torsten Sommer
Journal:  Pacing Clin Electrophysiol       Date:  2009-09-30       Impact factor: 1.976

5.  Local SAR near deep brain stimulation (DBS) electrodes at 64 and 127 MHz: A simulation study of the effect of extracranial loops.

Authors:  Laleh Golestanirad; Leonardo M Angelone; Maria Ida Iacono; Husam Katnani; Lawrence L Wald; Giorgio Bonmassar
Journal:  Magn Reson Med       Date:  2016-10-31       Impact factor: 4.668

6.  Trends in permanent pacemaker implantation in the United States from 1993 to 2009: increasing complexity of patients and procedures.

Authors:  Arnold J Greenspon; Jasmine D Patel; Edmund Lau; Jorge A Ochoa; Daniel R Frisch; Reginald T Ho; Behzad B Pavri; Steven M Kurtz
Journal:  J Am Coll Cardiol       Date:  2012-09-19       Impact factor: 24.094

7.  Safe magnetic resonance imaging scanning of patients with cardiac rhythm devices: a role for computer modeling.

Authors:  Bruce L Wilkoff; Timothy Albert; Mariya Lazebnik; Sung-Min Park; Jonathan Edmonson; Ben Herberg; John Golnitz; Sandy Wixon; Joel Peltier; Hyun Yoon; Sarah Willey; Yair Safriel
Journal:  Heart Rhythm       Date:  2013-10-04       Impact factor: 6.343

8.  Improvement of Electromagnetic Field Distributions Using High Dielectric Constant (HDC) Materials for CTL-Spine MRI: Numerical Simulations and Experiments.

Authors:  Bu S Park; Brent McCright; Leonardo M Angelone; Amir Razjouyan; Sunder S Rajan
Journal:  IEEE Trans Electromagn Compat       Date:  2017-10       Impact factor: 2.006

9.  A novel brain stimulation technology provides compatibility with MRI.

Authors:  Peter Serano; Leonardo M Angelone; Husam Katnani; Emad Eskandar; Giorgio Bonmassar
Journal:  Sci Rep       Date:  2015-04-29       Impact factor: 4.379

10.  Complexity of MRI induced heating on metallic leads: experimental measurements of 374 configurations.

Authors:  Eugenio Mattei; Michele Triventi; Giovanni Calcagnini; Federica Censi; Wolfgang Kainz; Gonzalo Mendoza; Howard I Bassen; Pietro Bartolini
Journal:  Biomed Eng Online       Date:  2008-03-03       Impact factor: 2.819

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  7 in total

Review 1.  Improving Safety of MRI in Patients with Deep Brain Stimulation Devices.

Authors:  Alexandre Boutet; Clement T Chow; Keshav Narang; Gavin J B Elias; Clemens Neudorfer; Jürgen Germann; Manish Ranjan; Aaron Loh; Alastair J Martin; Walter Kucharczyk; Christopher J Steele; Ileana Hancu; Ali R Rezai; Andres M Lozano
Journal:  Radiology       Date:  2020-06-23       Impact factor: 11.105

2.  Reconfigurable MRI technology for low-SAR imaging of deep brain stimulation at 3T: Application in bilateral leads, fully-implanted systems, and surgically modified lead trajectories.

Authors:  Ehsan Kazemivalipour; Boris Keil; Alireza Vali; Sunder Rajan; Behzad Elahi; Ergin Atalar; Lawrence L Wald; Joshua Rosenow; Julie Pilitsis; Laleh Golestanirad
Journal:  Neuroimage       Date:  2019-05-13       Impact factor: 6.556

3.  The effect of simulation strategies on prediction of power deposition in the tissue around electronic implants during magnetic resonance imaging.

Authors:  Bach T Nguyen; Julie Pilitsis; Laleh Golestanirad
Journal:  Phys Med Biol       Date:  2020-09-16       Impact factor: 3.609

4.  Machine learning-based prediction of MRI-induced power absorption in the tissue in patients with simplified deep brain stimulation lead models.

Authors:  Jasmine Vu; Bach T Nguyen; Bhumi Bhusal; Justin Baraboo; Joshua Rosenow; Ulas Bagci; Molly G Bright; Laleh Golestanirad
Journal:  IEEE Trans Electromagn Compat       Date:  2021-09-30       Impact factor: 2.036

5.  RF heating of deep brain stimulation implants in open-bore vertical MRI systems: A simulation study with realistic device configurations.

Authors:  Laleh Golestanirad; Ehsan Kazemivalipour; David Lampman; Hideta Habara; Ergin Atalar; Joshua Rosenow; Julie Pilitsis; John Kirsch
Journal:  Magn Reson Med       Date:  2019-11-02       Impact factor: 4.668

6.  Patient's body composition can significantly affect RF power deposition in the tissue around DBS implants: ramifications for lead management strategies and MRI field-shaping techniques.

Authors:  Bhumi Bhusal; Boris Keil; Joshua Rosenow; Ehsan Kazemivalipour; Laleh Golestanirad
Journal:  Phys Med Biol       Date:  2021-01-14       Impact factor: 3.609

7.  Vertical open-bore MRI scanners generate significantly less radiofrequency heating around implanted leads: A study of deep brain stimulation implants in 1.2T OASIS scanners versus 1.5T horizontal systems.

Authors:  Ehsan Kazemivalipour; Bhumi Bhusal; Jasmine Vu; Stella Lin; Bach Thanh Nguyen; John Kirsch; Elizabeth Nowac; Julie Pilitsis; Joshua Rosenow; Ergin Atalar; Laleh Golestanirad
Journal:  Magn Reson Med       Date:  2021-05-07       Impact factor: 3.737

  7 in total

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