University of Hertfordshire

  • Nicola Pavese
  • Yen F Tai
  • Nada Yousif
  • Dipankar Nandi
  • Peter G Bain
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Original languageEnglish
JournalWorld neurosurgery
Journal publication date27 Sep 2019
Early online date27 Sep 2019
Publication statusE-pub ahead of print - 27 Sep 2019


BACKGROUND: Programming Deep Brain Stimulation (DBS) settings in patients with Parkinson's disease (PD) is challenging and time consuming due to the vast number of possible parameter combinations. This results in long sessions that can be exhausting for the patients and the physicians. GUIDETM (Boston Scientific) is a 3D-neuroantomical visual software that precisely visualises the location of the DBS electrode in the subthalamic nucleus (STN).OBJECTIVE: To compared the duration and clinical effects of traditional trial-and-error versus GUIDETM-assisted DBS programming in ten PD patients treated with STN DBS.METHODS: For each patient, neurostimulation parameters were selected with GUIDETM to create a stimulation field encompassing the dorsal part of the STN. On programming day, each patient was assessed with both traditional and GUIDETM approaches using a cross-over design. For GUIDETM-assisted session, the patients were programmed directly with the DBS settings obtained with the stimulated field model and, if necessary, parameters were adjusted to achieve optimal clinical response. Clinical improvement was assessed with UPDRS scores for limb bradykinesia, tremor, and rigidity.RESULTS: In seven patients, DBS settings obtained with GUIDETM led to a suboptimal clinical improvement and mild adjustments were required. After these adjustments, the magnitude of clinical improvement with the two approaches was comparable (p= 0.8219). Programming time with GUIDETM was significantly shorter than that traditional programming approach (p< 0.0001).CONCLUSIONS: Visualization of stimulation fields with GUIDETM provides useful information to achieve a clinical improvement comparable to that obtained with the traditional trial-and-error approach, but with shorter and more efficient programming sessions.


Copyright © 2019. Published by Elsevier Inc.

ID: 17450363