Literature DB >> 32756027

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

Bach T Nguyen1, Julie Pilitsis, Laleh Golestanirad.   

Abstract

Numerical simulations are increasingly employed in safety assessment of high-field magnetic resonance imaging (MRI) in patients with conductive medical implants such as those with deep brain stimulation (DBS) devices. Performing numerical simulations with realistic patient models and implant geometry is the preferred method as it provides the most accurate results; however, in many cases such an approach is infeasible due to limitation of computational resources. The difficulties in reconstructing realistic patient and device models and obtaining accurate electrical properties of tissue have compelled researchers to adopt compromises, either to exceedingly simplify implant structure and geometry, or the complexity of the body model. This study examines the effect of variations in anatomical details of the human body model and implant geometry on predicted values of specific absorption rate (SAR) values during MRI in a patient with a DBS implant. We used a patient-derived model of a fully implanted DBS implant and performed numerical simulations to calculate the maximum SAR during MRI at 1.5T (64 MHz) and 3T (127 MHz). We then assessed the effect of uncertainties in dielectric properties of tissue, complexity of body model, truncation of body/DBS model, and DBS lead geometry on SAR. Our results showed that 40% variation in the conductivity of individual tissues in a heterogeneous body model caused a peak of 7% variation in maximum SAR value at 64 MHz, and 10.6% variation in SAR at 127 MHz. SAR predictions from a homogeneous body model with a conductivity range of [Formula: see text] could cover the full range of SAR variations predicted by the heterogeneous body model. Truncation of body model below the implanted pulse generator changed the predicted SAR by 16% at 1.5T and 32% at 3T while saving 250% and 148% in computational time and memory allocation, respectively. In contrast, variation in DBS lead geometry significantly changed the SAR by up to 51% at 64 MHz and 67% at 127 MHz. These results suggest that the error introduced by simplifying the implant's geometry could negate the benefit of using a realistic body model, should such model be used at the expense of oversimplifying implant geometry.

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Year:  2020        PMID: 32756027      PMCID: PMC8713474          DOI: 10.1088/1361-6560/abac9f

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  48 in total

1.  MRI-based anatomical model of the human head for specific absorption rate mapping.

Authors:  Nikos Makris; Leonardo Angelone; Seann Tulloch; Scott Sorg; Jonathan Kaiser; David Kennedy; Giorgio Bonmassar
Journal:  Med Biol Eng Comput       Date:  2008-11-05       Impact factor: 2.602

2.  Magnetic resonance imaging of implanted deep brain stimulators: experience in a large series.

Authors:  Paul S Larson; R Mark Richardson; Philip A Starr; Alastair J Martin
Journal:  Stereotact Funct Neurosurg       Date:  2007-12-12       Impact factor: 1.875

3.  SAR simulations for high-field MRI: how much detail, effort, and accuracy is needed?

Authors:  S Wolf; D Diehl; M Gebhardt; J Mallow; O Speck
Journal:  Magn Reson Med       Date:  2012-05-18       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.  Designing passive MRI-safe implantable conducting leads with electrodes.

Authors:  Paul A Bottomley; Ananda Kumar; William A Edelstein; Justin M Allen; Parag V Karmarkar
Journal:  Med Phys       Date:  2010-07       Impact factor: 4.071

Review 6.  Current clinical issues for MRI scanning of pacemaker and defibrillator patients.

Authors:  Ron Kalin; Marshall S Stanton
Journal:  Pacing Clin Electrophysiol       Date:  2005-04       Impact factor: 1.976

7.  Realistic modeling of deep brain stimulation implants for electromagnetic MRI safety studies.

Authors:  Bastien Guerin; Peter Serano; Maria Ida Iacono; Todd M Herrington; Alik S Widge; Darin D Dougherty; Giorgio Bonmassar; Leonardo M Angelone; Lawrence L Wald
Journal:  Phys Med Biol       Date:  2018-05-04       Impact factor: 3.609

8.  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

Review 9.  Neuroimaging and deep brain stimulation.

Authors:  D Dormont; D Seidenwurm; D Galanaud; P Cornu; J Yelnik; E Bardinet
Journal:  AJNR Am J Neuroradiol       Date:  2009-09-12       Impact factor: 4.966

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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  4 in total

1.  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

2.  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

3.  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

4.  Safety of MRI in patients with retained cardiac leads.

Authors:  Bach T Nguyen; Bhumi Bhusal; Amir Ali Rahsepar; Kate Fawcett; Stella Lin; Daniel S Marks; Rod Passman; Donny Nieto; Richard Niemzcura; Laleh Golestanirad
Journal:  Magn Reson Med       Date:  2021-12-27       Impact factor: 3.737

  4 in total

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