Literature DB >> 31568905

Traditional Trial and Error versus Neuroanatomic 3-Dimensional Image Software-Assisted Deep Brain Stimulation Programming in Patients with Parkinson Disease.

Nicola Pavese1, Yen F Tai2, Nada Yousif3, Dipankar Nandi2, Peter G Bain2.   

Abstract

BACKGROUND: Programming deep brain stimulation (DBS) settings in patients with Parkinson disease (PD) is challenging and time consuming because of the vast number of possible parameter combinations. This results in long sessions that can be exhausting for the patients and physicians. GUIDE (Boston Scientific) is a 3-dimensional neuroanatomic visual software that precisely visualizes the location of the DBS electrode in the subthalamic nucleus (STN). The objective of this paper is to compare the duration and clinical effects of traditional trial and error versus GUIDE-assisted DBS programming in 10 patients with PD treated with STN DBS.
METHODS: For each patient, neurostimulation parameters were selected with GUIDE to create a stimulation field encompassing the dorsal part of the STN. On programming day, each patient was assessed with both traditional and GUIDE approaches using a crossover design. For GUIDE-assisted sessions, 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 Unified Parkinson's Disease Rating Scale scores for limb bradykinesia, tremor, and rigidity.
RESULTS: In 7 patients, DBS settings obtained with GUIDE led to suboptimal clinical improvement and mild adjustments were required. After these adjustments, the magnitude of clinical improvement with the 2 approaches was comparable (P = 0.8219). Programming time with GUIDE was significantly shorter than with the traditional programming approach (P < 0.0001).
CONCLUSIONS: Visualization of stimulation fields with GUIDE provides useful information to achieve a clinical improvement comparable with that obtained with the traditional trial and error approach, but with shorter and more efficient programming sessions.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Deep brain stimulation; Parkinson disease; Subthalamic; Visual software

Mesh:

Year:  2019        PMID: 31568905     DOI: 10.1016/j.wneu.2019.09.106

Source DB:  PubMed          Journal:  World Neurosurg        ISSN: 1878-8750            Impact factor:   2.104


  3 in total

1.  A New Application of Functional Zonal Image Reconstruction in Programming for Parkinson's Disease Treated Using Subthalamic Nucleus-Deep Brain Stimulation.

Authors:  Jiaming Mei; Bowen Chang; Chi Xiong; Manli Jiang; Chaoshi Niu
Journal:  Front Neurol       Date:  2022-06-10       Impact factor: 4.086

2.  Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Authors:  Alexandre Boutet; Radhika Madhavan; Gavin J B Elias; Suresh E Joel; Robert Gramer; Manish Ranjan; Vijayashankar Paramanandam; David Xu; Jurgen Germann; Aaron Loh; Suneil K Kalia; Mojgan Hodaie; Bryan Li; Sreeram Prasad; Ailish Coblentz; Renato P Munhoz; Jeffrey Ashe; Walter Kucharczyk; Alfonso Fasano; Andres M Lozano
Journal:  Nat Commun       Date:  2021-05-24       Impact factor: 14.919

3.  In silico Accuracy and Energy Efficiency of Two Steering Paradigms in Directional Deep Brain Stimulation.

Authors:  León Mauricio Juárez-Paz
Journal:  Front Neurol       Date:  2020-10-30       Impact factor: 4.003

  3 in total

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