Literature DB >> 27245875

The Rate of Magnetic Resonance Imaging in Patients with Deep Brain Stimulation.

Steven Falowski1, Yair Safriel, Michael P Ryan, Liesl Hargens.   

Abstract

BACKGROUND: For Parkinson's disease (PD), essential tremor (ET), and dystonia patients with deep brain stimulation (DBS) implants, magnetic resonance imaging (MRI) requires additional safety considerations due to potentially hazardous interactions.
OBJECTIVE: A propensity-matched cohort of DBS-implanted patients was analyzed to determine the likelihood of needing MRI.
METHODS: Patients with new DBS full-system implants (n = 576) were identified in the Truven Health MarketScan® Commercial Claims and Medicare Supplemental Databases (2009-2012). Patients diagnosed with PD, ET, or dystonia and no DBS implant were identified (DBS-indicated patients: n = 11,216). The DBS-indicated patients were continuously enrolled for 4 years and matched for age, gender, and propensity score based on comorbid conditions to DBS-implanted patients (n = 4,878 and 543, respectively). A Kaplan-Meier survival curve of time to first MRI was extrapolated to 10 years.
RESULTS: An estimated 56-57% of DBS-indicated patients need an MRI within 5 years and 66-75% within 10 years after implantation. While 92% of DBS-implanted patients' MRI after implantation was of the head, for DBS-indicated patients, 62% of MRIs were of the body, potentially unrelated to the primary diagnosis.
CONCLUSIONS: This analysis highlights the projected utilization of MRI in the DBS population for head and full-body images.
© 2016 The Author(s) Published by S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2016        PMID: 27245875     DOI: 10.1159/000444760

Source DB:  PubMed          Journal:  Stereotact Funct Neurosurg        ISSN: 1011-6125            Impact factor:   1.875


  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.  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

Review 3.  Deep brain stimulation and electromagnetic interference.

Authors:  Shervin Rahimpour; Musa Kiyani; Sarah E Hodges; Dennis A Turner
Journal:  Clin Neurol Neurosurg       Date:  2021-02-25       Impact factor: 1.876

4.  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

Review 5.  Deep Brain Stimulation Initiative: Toward Innovative Technology, New Disease Indications, and Approaches to Current and Future Clinical Challenges in Neuromodulation Therapy.

Authors:  Yanan Sui; Ye Tian; Wai Kin Daniel Ko; Zhiyan Wang; Fumin Jia; Andreas Horn; Dirk De Ridder; Ki Sueng Choi; Ausaf A Bari; Shouyan Wang; Clement Hamani; Kenneth B Baker; Andre G Machado; Tipu Z Aziz; Erich Talamoni Fonoff; Andrea A Kühn; Hagai Bergman; Terence Sanger; Hesheng Liu; Suzanne N Haber; Luming Li
Journal:  Front Neurol       Date:  2021-01-28       Impact factor: 4.003

6.  Hydrogel-Based Organic Subdural Electrode with High Conformability to Brain Surface.

Authors:  Shuntaro Oribe; Shotaro Yoshida; Shinya Kusama; Shin-Ichiro Osawa; Atsuhiro Nakagawa; Masaki Iwasaki; Teiji Tominaga; Matsuhiko Nishizawa
Journal:  Sci Rep       Date:  2019-09-16       Impact factor: 4.379

7.  Predicting in vivo MRI Gradient-Field Induced Voltage Levels on Implanted Deep Brain Stimulation Systems Using Neural Networks.

Authors:  M Arcan Erturk; Eric Panken; Mark J Conroy; Jonathan Edmonson; Jeff Kramer; Jacob Chatterton; S Riki Banerjee
Journal:  Front Hum Neurosci       Date:  2020-02-20       Impact factor: 3.169

  7 in total

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