Literature DB >> 31096058

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.

Ehsan Kazemivalipour1, Boris Keil2, Alireza Vali3, Sunder Rajan4, Behzad Elahi5, Ergin Atalar6, Lawrence L Wald7, Joshua Rosenow8, Julie Pilitsis9, Laleh Golestanirad10.   

Abstract

Patients with deep brain stimulation devices highly benefit from postoperative MRI exams, however MRI is not readily accessible to these patients due to safety risks associated with RF heating of the implants. Recently we introduced a patient-adjustable reconfigurable coil technology that substantially reduced local SAR at tips of single isolated DBS leads during MRI at 1.5 T in 9 realistic patient models. This contribution extends our work to higher fields by demonstrating the feasibility of scaling the technology to 3T and assessing its performance in patients with bilateral leads as well as fully implanted systems. We developed patient-derived models of bilateral DBS leads and fully implanted DBS systems from postoperative CT images of 13 patients and performed finite element simulations to calculate SAR amplification at electrode contacts during MRI with a reconfigurable rotating coil at 3T. Compared to a conventional quadrature body coil, the reconfigurable coil system reduced the SAR on average by 83% for unilateral leads and by 59% for bilateral leads. A simple surgical modification in trajectory of implanted leads was demonstrated to increase the SAR reduction efficiency of the rotating coil to >90% in a patient with a fully implanted bilateral DBS system. Thermal analysis of temperature-rise around electrode contacts during typical brain exams showed a 15-fold heating reduction using the rotating coil, generating <1°C temperature rise during ∼4-min imaging with high-SAR sequences where a conventional CP coil generated >10°C temperature rise in the tissue for the same flip angle.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Deep brain stimulation (DBS); Finite element; In-silico medicine; Individualized medicine; MRI coils; MRI safety; Magnetic resonance imaging (MRI); Medical implants; Neuromodulation; Neurostimulation; Reconfigurable MRI; Simulations; Specific absorption rate (SAR)

Mesh:

Year:  2019        PMID: 31096058      PMCID: PMC7266624          DOI: 10.1016/j.neuroimage.2019.05.015

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  58 in total

1.  Measuring RF-induced currents inside implants: Impact of device configuration on MRI safety of cardiac pacemaker leads.

Authors:  Peter Nordbeck; Ingo Weiss; Philipp Ehses; Oliver Ritter; Marcus Warmuth; Florian Fidler; Volker Herold; Peter M Jakob; Mark E Ladd; Harald H Quick; Wolfgang R Bauer
Journal:  Magn Reson Med       Date:  2009-03       Impact factor: 4.668

2.  Parallel radiofrequency transmission at 3 tesla to improve safety in bilateral implanted wires in a heterogeneous model.

Authors:  Clare E McElcheran; Benson Yang; Kevan J T Anderson; Laleh Golestanirad; Simon J Graham
Journal:  Magn Reson Med       Date:  2017-02-28       Impact factor: 4.668

3.  Heating effects of metallic implants by MRI examinations.

Authors:  R Buchli; P Boesiger; D Meier
Journal:  Magn Reson Med       Date:  1988-07       Impact factor: 4.668

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

Authors:  Laleh Golestanirad; Leonardo M Angelone; John Kirsch; Sean Downs; Boris Keil; Giorgio Bonmassar; Lawrence L Wald
Journal:  IEEE Trans Microw Theory Tech       Date:  2019-01-01       Impact factor: 3.599

5.  A closer look at unilateral versus bilateral deep brain stimulation: results of the National Institutes of Health COMPARE cohort.

Authors:  Houtan A Taba; Samuel S Wu; Kelly D Foote; Chris J Hass; Hubert H Fernandez; Irene A Malaty; Ramon L Rodriguez; Yunfeng Dai; Pamela R Zeilman; Charles E Jacobson; Michael S Okun
Journal:  J Neurosurg       Date:  2010-09-17       Impact factor: 5.115

6.  Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions.

Authors:  Ashutosh Chaturvedi; Christopher R Butson; Scott F Lempka; Scott E Cooper; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2010-04       Impact factor: 8.955

7.  Neurostimulation system used for deep brain stimulation (DBS): MR safety issues and implications of failing to follow safety recommendations.

Authors:  Ali R Rezai; Michael Phillips; Kenneth B Baker; Ashwini D Sharan; John Nyenhuis; Jean Tkach; Jaimie Henderson; Frank G Shellock
Journal:  Invest Radiol       Date:  2004-05       Impact factor: 6.016

8.  Deep brain stimulation for essential tremor.

Authors:  J P Hubble; K L Busenbark; S Wilkinson; R D Penn; K Lyons; W C Koller
Journal:  Neurology       Date:  1996-04       Impact factor: 9.910

9.  STN-stimulation in Parkinson's disease restores striatal inhibition of thalamocortical projection.

Authors:  Jacob Geday; Karen Østergaard; Erik Johnsen; Albert Gjedde
Journal:  Hum Brain Mapp       Date:  2009-01       Impact factor: 5.038

10.  RF-induced heating in tissue near bilateral DBS implants during MRI at 1.5 T and 3T: The role of surgical lead management.

Authors:  Laleh Golestanirad; John Kirsch; Giorgio Bonmassar; Sean Downs; Behzad Elahi; Alastair Martin; Maria-Ida Iacono; Leonardo M Angelone; Boris Keil; Lawrence L Wald; Julie Pilitsis
Journal:  Neuroimage       Date:  2018-09-19       Impact factor: 6.556

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  8 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.  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

3.  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

4.  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

5.  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

6.  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.  A Preliminary Study for Reference RF Coil at 11.7 T MRI: Based on Electromagnetic Field Simulation of Hybrid-BC RF Coil According to Diameter and Length at 3.0, 7.0 and 11.7 T.

Authors:  Jeung-Hoon Seo; Jun-Young Chung
Journal:  Sensors (Basel)       Date:  2022-02-15       Impact factor: 3.576

8.  A workflow for predicting temperature increase at the electrical contacts of deep brain stimulation electrodes undergoing MRI.

Authors:  Alireza Sadeghi-Tarakameh; Nur Izzati Huda Zulkarnain; Xiaoxuan He; Ergin Atalar; Noam Harel; Yigitcan Eryaman
Journal:  Magn Reson Med       Date:  2022-07-04       Impact factor: 3.737

  8 in total

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