arrow
返回

Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm

delete2023-02-01
delete20
delete
OA
AI
J
Jan Roediger
T
Till A. Dembek
J
Johannes Achtzehn
J
Johannes L. Busch
A
Anna-Pauline Krämer
K
Katharina Faust
G
Gerd‐Helge Schneider
P
Patricia Krause
A
Andreas Horn
A
Andrea A. Kühn *
DOI:10.1016/S2589-7500(22)00214-Xdelete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Background Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data. Methods This double-blind, randomised, crossover, non-inferiority trial was carried out at Charite - Universitatsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoCprogrammed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete.Findings Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47 & BULL;3 (SD 17 & BULL;1) at OFF-stimulation baseline to 24 & BULL;7 (SD 12 & BULL;4) and 26 & BULL;3 (SD 12 & BULL;4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1 & BULL;6 (SD 7 & BULL;1; 95% CI -4 & BULL;0 to 0 & BULL;9; superiority test psuperiority=0 & BULL;20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test pnon-inferiority=0 & BULL;0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared.Interpretation Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters.
Keyword:
PARKINSONS-DISEASE
SUBTHALAMIC NUCLEUS
DOUBLE-BLIND
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Lancet Digital Health 封面图
Lancet Digital Health
IF:
24.1
论文数:
1.2K
被引数:
8.5K

机构

B
Berlin Institute of Health
学者数:
3.9W
论文数: 3.0W
被引数: 6.6K
C
Charite Universitatsmedizin Berlin
学者数:
1.6W
论文数: 1.3W
被引数: 29
H
Humboldt University of Berlin
学者数:
3.2W
论文数: 2.7W
被引数: 47
学者 查看更多机构
引用论文

引用论文

How do parkinsonian signs return after discontinuation of subthalamic DBS?
err2003-01-14
err365
PREAI
errTemperli, P; Ghika, J; Villemure, JG; Burkhard, PR; Bogousslavsky, J; Vingerhoets, FJG
err分享
err收藏
Multi-objective data-driven optimization for improving deep brain stimulation in Parkinson's disease多目标数据驱动优化改善帕金森病脑深部电刺激
err2021-05-05
err19
errOAAI
errConnolly, Mark J.; Cole, Eric R.; Isbaine, Faical; de Hemptinne, Coralie; Starr, Phillip A.; Willie, Jon T.; Gross, Robert E.; Miocinovic, Svjetlana
err分享
err收藏
Probabilistic mapping of the antidystonic effect of pallidal neurostimulation: a multicentre imaging study
errBRAIN
IF11.7
err2019-03-08
err97
errOAAI
errReich, Martin M.; Horn, Andreas; Lange, Florian; Roothans, Jonas; Paschen, Steffen; Runge, Joachim; Wodarg, Fritz; Pozzi, Nicolo G.; Witt, Karsten; Nickl, Robert C.; Soussand, Louis; Ewert, Siobhan; Maltese, Virgina; Wittstock, Matthias; Schneider, Gerd-Helge; Coenen, Volker; Mahlknecht, Philipp; Poewe, Werner; Eisner, Wilhelm; Helmers, Ann-Kristin; Matthies, Cordula; Sturm, Volker; Isaias, Ioannis U.; Krauss, Joachim K.; Kuehn, Andrea A.; Deuschl, Guenther; Volkmann, Jens
err分享
err收藏
Imaging-based programming of subthalamic nucleus deep brain stimulation in Parkinson's disease帕金森病丘脑底核深部脑刺激的基于成像的编程
err2021-09-01
err25
errOAAI
errWaldthaler, Josefine; Bopp, Miriam; Kuehn, Nele; Bacara, Bugrahan; Keuler, Merle; Gjorgjevski, Marko; Carl, Barbara; Timmermann, Lars; Nimsky, Christopher; Pedrosa, David J.
err分享
err收藏
Anodic stimulation misunderstood: preferential activation of fiber orientations with anodic waveforms in deep brain stimulation
err2019-01-14
err72
errOAAI
errAnderson, Daria Nesterovich; Duffley, Gordon; Vorwerk, Johannes; Dorval, Alan D.; Butson, Christopher R.
err分享
err收藏
Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease连通性预测帕金森病的深部脑刺激结果
err2017-07-25
err509
errOAAI
errHorn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Huebsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kuehn, Andrea A.; Fox, Michael D.
err分享
err收藏
CLOVER-DBS: Algorithm-Guided Deep Brain Stimulation-Programming Based on External Sensor Feedback Evaluated in a Prospective, Randomized, Crossover, Double-Blind, Two-Center Study
err2021-10-12
err15
PREAI
errWenzel, Gregor R.; Roediger, Jan; Bruecke, Christof; Marcelino, Ana Luisa de A.; Guelke, Eileen; Poetter-Nerger, Monika; Scholtes, Heleen; Wynants, Kenny; Paz, Leon M. Juarez; Kuehn, Andrea A.
err分享
err收藏
StimVision v2: Examples and Applications in Subthalamic Deep Brain Stimulation for Parkinson's Disease
err2021-02-01
err33
errOAAI
errNoecker, Angela M.; Frankemolle-Gilbert, Anneke M.; Howell, Bryan; Petersen, Mikkel V.; Beylergil, Sinem Balta; Shaikh, Aasef G.; McIntyre, Cameron C.
err分享
err收藏
StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming
err2021-11-27
err25
errOAAI
errRoediger, Jan; Dembek, Till A.; Wenzel, Gregor; Butenko, Konstantin; Kuehn, Andrea A.; Horn, Andreas
err分享
err收藏
学者 查看更多内容