Thompson John A, Hirt Lisa, David-Gerecht Pamela, Fasano Alfonso, Kramer Daniel R, Ojemann Steven G, Kern Drew S
Department of Neurology University of Colorado School of Medicine Aurora Colorado USA.
Department of Neurosurgery University of Colorado School of Medicine Aurora Colorado USA.
Mov Disord Clin Pract. 2023 May 5;10(6):987-991. doi: 10.1002/mdc3.13750. eCollection 2023 Jun.
Technological advancements in deep brain stimulation (DBS) require methodological changes in programming. Fractionalization poses significant practical challenges for the most common approach for assessing DBS efficacy, monopolar review (MR).
Two DBS programming methods: MR and fixed parameter vertical and horizontal fractionalization (FPF) were compared.
A two-phase process of vertical and horizontal FPF was performed. MR was conducted thereafter. After a short wash-out period, both optimal configurations determined by MR and FPF were tested in a double-blind randomized manner.
Seven PD patients were enrolled, providing 11 hemispheres to compare the two conditions. In all subjects, the blinded examiner selected a directional or fractionalization configuration. There was no significant difference in clinical benefits between MR and FPF. FPF was the preferred method for initial programming as selected by subject and clinician.
FPF programming is a viable and efficient methodology that may be incorporated into clinical practice.
深部脑刺激（DBS）技术的进步要求在编程方法上做出改变。分数化给评估DBS疗效的最常用方法——单极回顾（MR）带来了重大实际挑战。
比较两种DBS编程方法：MR和固定参数垂直和水平分数化（FPF）。
进行了垂直和水平FPF的两阶段过程。此后进行了MR。在短暂的洗脱期后，以双盲随机方式测试了由MR和FPF确定的两种最佳配置。
招募了7名帕金森病患者，提供了11个半球来比较两种情况。在所有受试者中，盲法检查者选择了定向或分数化配置。MR和FPF在临床益处方面没有显著差异。FPF是受试者和临床医生选择的初始编程首选方法。
FPF编程是一种可行且有效的方法，可纳入临床实践。
