Dystonia Coalition- CRP 3

摘要 口吃困难是一种慢性的、使人衰弱的疾病。没有治愈方法，目前可用的 治疗只针对症状，只取得了部分成功。开发新疗法的努力取决于 关于衡量症状严重程度的能力。传统上，严重程度是用人工评分来衡量的 被称为临床评分表的工具。然而，由于这些评级标准具有内在的主观性， 它们表现出从一个评级到下一个评级的变异性--即使是对于相同的评分者。这限制了他们的能力 准确捕获严重性并检测随着时间推移严重性的变化。视频处理软件的进展 提供使用部分自动化的量化手段来补充临床评分标准的可能性 客观的症状。我们对肌张力障碍患者的计算机化、基于视频的系统的初步测试 视频显示，他们可以量化最常见类型的肌张力障碍的几个临床重要特征。 我们的长期目标是最大限度地利用这些方法来帮助监控进度、评估 治疗反应，优化肌张力障碍的治疗。 在这个项目中，我们将开发和验证这种方法来客观地测量运动症状 三种常见的肌张力障碍形式：颈部肌张力障碍(CD)、眼睑痉挛(BSP)和喉肌张力障碍 (Ld)。对于CD和BSP，系统使用了被称为计算机表情识别的高级软件 工具箱(CERT)，用于从患者面部的视频记录中测量各种异常运动。证书 已在神经学正常人群中广泛使用，并且对高度可变的视频具有很强的鲁棒性 录制条件。虽然这种类型的方法以前从未被应用于LD，但我们将开发一个 类似的系统，用于测量在检查过程中拍摄到的声带异常活动 喉咙。对于三种形式的肌张力障碍，我们的目标是：a)测试系统捕获特定类型的 肌张力障碍的特征，b)评估这些特征的组合如何与全球临床评估相关 严重程度，c)比较系统对严重程度的评估与患者报告的质量评估 生命，以及d)确定系统是否可以检测与肉毒毒素相关的严重程度的变化 注射，是这些形式的局灶性肌张力障碍最常见的治疗方法。 完成后，我们将开发和验证新的方法来衡量MOST的严重性 常见的口吃困难。该方法对肌张力障碍的基础研究和临床研究都有一定的参考价值。基本信息 例如，遗传学、蛋白质组学和脑成像方面的研究依赖于严重性评估来分配 将患者分配到不同的组和/或确定患者的神经生物学方面如何与症状相关 严肃性。肌张力障碍自然发展的临床研究及其对新治疗的反应 依赖于严重程度评估。因此，该项目将有助于扩大基础研究和临床研究的影响。 并有助于加速开发治疗肌张力障碍的新疗法。

Abstract The dystonias are chronic, debilitating disorders. There are no cures, and the currently available treatments target only the symptoms and are only partly successful. Efforts to develop new treatments depend on the ability to measure the severity of the symptoms. Traditionally, severity is measured with human-scored instruments known as clinical rating scales. However, because these rating scales are inherently subjective, they exhibit variability from one rating to the next – even for the same rater. This limits their ability to accurately capture severity and detect changes in severity over time. Advances in video processing software offer the possibility to supplement clinical rating scales with a partially automated means of quantifying symptoms objectively. Our preliminary tests of computerized, video-based systems with dystonia patient videos suggest they can quantify several clinically important features of the most common types of dystonia. Our long-term goal is to maximize how these approaches can aid in monitoring progression, assessing treatment response, and optimizing treatment for dystonia. In this project, we will develop and validate this approach to objectively measure the motor symptoms of three common forms of dystonia: cervical dystonia (CD), blepharospasm (BSP), and laryngeal dystonia (LD). For CD and BSP, the system uses advanced software known as the Computer Expression Recognition Toolbox (CERT) to measure various abnormal movements from video recordings of the patient’s face. CERT has been used extensively in neurologically normal populations and it is robust to highly variable video recording conditions. Although this type of approach has never before been applied to LD, we will develop a similar system to measure abnormal activity in the vocal cords captured on video during examination of the larynx. For each of the three forms of dystonia, our aims are to: a) test how well the system captures specific features of the dystonia, b) evaluate how combinations of those features relate to global clinical assessments of severity, c) compare the system’s assessment of severity with patient-reported assessments of quality of life, and d) determine whether the system can detect changes in severity associated with botulinum toxin injections, the most common treatment for these forms of focal dystonia. Upon completion, we will have developed and validated new methods to measure severity of the most common dystonias. The methods will be useful for both basic and clinical research in dystonia. Basic research in genetics, proteomics, and brain imaging, for example, relies on severity assessments for assigning patients to different groups and/or determining how aspects of the patient’s neurobiology relate to symptom severity. Clinical research on the natural progression of dystonia and its response to new treatments also relies on severity assessments. Thus this project will help amplify the impact of both basic and clinical research and help accelerate the development of new treatments for dystonia.