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Neurosurgery
Original research
Intraoperative physiology augments atlas-based data in awake deep brain stimulation
  1. Danika L Paulo1,
  2. Graham W Johnson2,3,
  3. Derek J Doss2,3,
  4. Jackson H Allen3,
  5. Hernán F J González2,3,4,
  6. Robert Shults1,
  7. Rui Li5,
  8. Tyler J Ball1,
  9. Sarah K Bick1,
  10. Travis J Hassell6,
  11. Pierre-François D’Haese7,
  12. Peter E Konrad8,
  13. Benoit M Dawant2,
  14. Saramati Narasimhan1,
  15. Dario J Englot1
  1. 1 Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
  2. 2 Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
  3. 3 Vanderbilt University School of Medicine, Nashville, Tennessee, USA
  4. 4 Neurosurgery, UCSD, La Jolla, California, USA
  5. 5 Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
  6. 6 Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
  7. 7 Neuroradiology, West Virginia University Rockefeller Neuroscience Institute, Morgantown, West Virginia, USA
  8. 8 Neurosurgery, West Virginia University Rockefeller Neuroscience Institute, Morgantown, West Virginia, USA
  1. Correspondence to Dr Danika L Paulo, Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA; danika.l.paulo{at}vumc.org

Abstract

Background Deep brain stimulation (DBS) is commonly performed with patients awake to perform intraoperative microelectrode recordings and/or macrostimulation testing to guide final electrode placement. Supplemental information from atlas-based databases derived from prior patient data and visualised as efficacy heat maps transformed and overlaid onto preoperative MRIs can be used to guide preoperative target planning and intraoperative final positioning. Our quantitative analysis of intraoperative testing and corresponding changes made to final electrode positioning aims to highlight the value of intraoperative neurophysiological testing paired with image-based data to optimise final electrode positioning in a large patient cohort.

Methods Data from 451 patients with movement disorders treated with 822 individual DBS leads at a single institution from 2011 to 2021 were included. Atlas-based data was used to guide surgical targeting. Intraoperative testing data and coordinate data were retrospectively obtained from a large patient database. Medical records were reviewed to obtain active contact usage and neurologist-defined outcomes at 1 year.

Results Microelectrode recording firing profiles differ per track, per target and inform the locations where macrostimulation testing is performed. Macrostimulation performance correlates with the final electrode track chosen. Centroids of atlas-based efficacy heat maps per target were close in proximity to and may predict active contact usage at 1 year. Overall, patient outcomes at 1 year were improved for patients with better macrostimulation response.

Conclusions Atlas-based imaging data is beneficial for target planning and intraoperative guidance, and in conjunction with intraoperative neurophysiological testing during awake DBS can be used to individualize and optimise final electrode positioning, resulting in favourable outcomes.

  • MOVEMENT DISORDERS
  • NEUROPHYSIOLOGY
  • NEUROSURGERY
  • PARKINSON'S DISEASE
  • TREMOR

Data availability statement

Data are available upon reasonable request.

https://doi.org/10.1136/jnnp-2023-331248

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    Data availability statement

    Data are available upon reasonable request.

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    Footnotes

    • DLP and GWJ are joint first authors.

    • Twitter @PeterKonrad12

    • Correction notice Since this article first published, a joint first authorship statement has been included along with a declaration of funding.

    • Contributors Study design/concept: DLP, DJE, SN, GWJ

      Data collection: DLP, RL, RS, JA, HG, PD, PEK, TJB, SKB, TH, BMD, SN, DJE, Data analysis: DLP, SN, GWJ, DD, HG, DJE Writing manuscript: DLP, GWJ, SN, DJE,Reviewing manuscript: All. All authors critically reviewed the paper and DJE is the guarantor.

    • Funding BMD has received grant funding to support this project: NIH R01NS095291.

    • Competing interests Some of the technology described in this article has been licensed by Vanderbilt University to FHC, Inc. which distributes it under the name WayPoint Navigator. BD receives royalties for this license. PK has a fiduciary relationship with NeuroTargeting, LLC, but has not received financial compensation in the 5 years prior to this article.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.