Enhancing Physical Therapy: Noninvasive Brain Stimulation System for Treating Carpal Tunnel Syndrome

腕管综合征(CTS)影响高达4%的美国人口，其中在工作场所的患病率更高 人口[1，2]。慢性疼痛(CP)是CTS最常见和最难治疗的并发症之一[2-6]。 目前的治疗方法[2-11]没有直接解决痛感是在大脑中处理的事实[5，12-14] 尽管CTS患者也有中枢性疼痛，但大多数都发生在神经病变部位(即外周) 5、6、12-15[5、6、12-15]。CTS症状学与CP诱导的脑内变化相关 活动和/或结构[14-24]。非侵入性脑刺激(NIBS)已成功地应用于 CP在某些疾病状态下的治疗，其中治疗导致脑活动逆转适应不良 可塑性与CP的知觉/感觉相关[25-28]。然而，最常见的NIBS方法， 例如经颅直流电刺激，在治疗神经病理性疼痛方面显示出有限的疗效[13， 29-33]。据推测，传统NIBS技术的焦点、穿透性和 靶向控制限制了它们的治疗效果[34-38]。电声刺激(ESSTim™)是一种改进的 NIBS模式，通过结合独立控制来克服其他技术的限制 电磁场和超声场通过可调谐的机电来聚焦和增强刺激电流 神经组织中的偶联[39]。这项提案的重点是评估我们的非侵入性ESSTim系统 无论是单独治疗还是与物理疗法(PT)相结合，都能有效地治疗CTS中的CP。在……里面 第一阶段，评估拟议工作的可行性，并具体测试ESSTim改进CTS的能力 疼痛，我们将跟踪20名CTS患者在连续5天给予固定剂量的ESSTim，20分钟/天(10 假ESSTim，10 ESSTim)。我们将实施一系列安全、疼痛、定量感觉测试(QST)， 运动功能，以及至少在治疗期间进行的全球自我评估(例如，生活质量) 在最后一次治疗后的六周。在第二阶段，我们将评估ESSTim是否导致疼痛 减少治疗可以配合物理治疗(PT)来改善CTS的治疗。我们将关注60个CTS 患者(ESStim30例，Sham组30例)在两周内给予固定剂量的刺激10天，每天20分钟， 但现在与PT一起提供。我们将通过一系列评估对这些患者进行评估 在第一阶段验证，并比较测试的干预措施在至少八周内的效果 最后一次治疗。我们假设ESSTim可以与PT协同提供，因为两者都可以 鼓励可塑性依赖的改变，这可以最大限度地改善CTS患者的无痛活动能力。在……里面 在CTS处理的同时，我们将建立多元线性和广义线性回归模型，以 预测与疼痛、身体功能和心理社会评估相关的CTS患者结局 基线疾病特征的作用。计算工作将用于开发优化的CTS ESSTim给药模型。总体而言，我们假设我们将能够开发用于CTS治疗的ESSTim™。

Carpal Tunnel Syndrome (CTS) affects up to 4% of the US population, with higher prevalence in the working population [1, 2]. Chronic pain (CP) is one of the most common and difficult to treat complications of CTS [2-6]. Current therapies [2-11] do not directly address the fact that pain sensation is processed in the brain [5, 12-14] and most act at the neuropathy site (i.e., in the periphery), although CTS patients also have a central pain component due to their injury [5, 6, 12-15]. CTS symptomatology correlates with CP-induced changes in brain activity and/or structure [14-24]. Non-Invasive Brain Stimulation (NIBS) has been successfully applied for the treatment of CP in some disease states, where treatment induced changes in brain activity revert maladaptive plasticity associated with the perception/sensation of CP [25-28]. However, the most common NIBS methods, e.g., transcranial direct current stimulation, have shown limited, if any, efficacy in treating neuropathic pain [13, 29-33]. It has been postulated that limitations in conventional NIBS techniques’ focality, penetration, and targeting control limit their therapeutic efficacy [34-38]. Electrosonic Stimulation (ESStim™) is an improved NIBS modality that overcomes the limitations of other technologies by combining independently controlled electromagnetic and ultrasonic fields to focus and boost stimulation currents via tuned electromechanical coupling in neural tissue [39]. This proposal is focused on evaluating whether our noninvasive ESStim system can effectively treat CP in CTS, both as a lone treatment and in conjunction with physical therapy (PT). In Phase I, to assess the feasibility of the proposed work, and specifically test ESStim’s ability to improve CTS pain, we will follow 20 CTS patients after giving a fixed dose of ESStim for 5 consecutive days, 20 min/day (10 SHAM ESStim, 10 ESStim). We will administer a battery of safety, pain, quantitative sensory testing (QST), motor function, and global self-assessments (e.g., QOL) evaluated over the treatment period and for at least six weeks following the last treatment session. Next in Phase II, we will assess whether ESStim induced pain reductions can be coupled with physical therapy (PT) to improve CTS treatment. We will follow 60 CTS patients (30 ESStim, 30 SHAM) after giving a fixed dose of stimulation for 10 days over two weeks, 20 min/day, but now provided in conjunction with PT. We will evaluate these patients with the battery of assessments validated in Phase I, and compare the efficacy of the tested interventions for at least eight weeks following the last treatment session. We hypothesize ESStim can be provided synergistically with PT, as both can encourage plasticity-dependent changes which could maximally improve a CTS patient’s pain free mobility. In parallel with the CTS treatments, we will build multivariate linear and generalized linear regression models to predict the CTS patient outcomes related to pain, physical function, and psychosocial assessments as a function of baseline disease characteristics. The computational work will be used to develop an optimized CTS ESStim dosing model. Overall, we hypothesize that we will be able to develop ESStim™ for CTS treatment.