Speech-based biomarkers of CNS dysfunction associated with early Alzheimers disea

描述(由申请人提供)：在临床实践和研究中需要更有效的方法来筛查和监测老年患者，但去诊所看医生的费用很高 而且许多老年患者受到行动能力或交通工具的限制。阿尔茨海默病合作研究(ADCS)正在评估几种在家远程监控患者状态的技术平台。Mary Sano博士领导了这项基于家庭的评估(HBA)研究，该研究在几年前完成了患者招募，现在正在完成最后的参与者随访。所有参与者都在研究基线时由医疗专业人员在诊断性访谈中进行了全面评估，并在研究结束时(或怀疑临床状态发生变化时)完成了类似的评估。穆特博士的研究团队开发了一种使用交互式语音应答(IVR)技术的语音计算机自动电话系统，这是HBA研究的一个组成部分。有几项IVR评估记录了用于语言分析的语音样本，没有分析语音模式的声学特征，用于分析的资源也不包括在HBA研究预算中。最近的研究表明，分析语音中的声学特征可以为与抑郁症相关的中枢神经系统功能提供可靠的、基于生理的生物标志物。多年来，临床抑郁症和早期阿尔茨海默病之间的症状相似之处已经被注意到，但重叠的程度和紧急症状的时间顺序仍然没有解决。目的：中枢神经系统功能障碍的生理学生物标志物可能为阿尔茨海默病的诊断和治疗提供新的见解。建议的研究是为了支持潜在筛查措施的开发和验证，这些措施可用于临床实践中的鉴别诊断，如 并为患有多种慢性病的老年人提供创新评估和管理办法的基础。该应用程序建议将来自全国HBA调查站点的不可识别的临床结果衡量标准和医疗诊断与由CPC开发的IVR系统记录的语音样本的音频文件合并。麻省理工学院林肯实验室的信号处理工程师将对语音样本进行分析，以寻找反映与阿尔茨海默氏症、帕金森氏症和抑郁症等中枢神经系统疾病相关的生理学生物标记物的声学特性。通过ADCS数据库获得的临床和诊断信息将用于开发和验证多变量统计模型，以改进诊断筛查、对疾病进展的非侵入性监测和/或疾病之间的鉴别诊断。 与公共卫生的相关性：老年患者的活动受限限制了研究的参与和与治疗提供者的接触，因此认知能力下降往往在必要的更长时间内未被发现。使用自动电话系统在家中远程监控患者的有效方法可以改进评估程序，减少访问障碍，促进跨文化非英语互动，并增强患者保留率 以最低的成本。ADCS家庭评估研究招募了具有全国代表性的214名老年人样本，并对他们进行了4年的纵向监测，以观察遗忘性MCI的出现和MCI向轻度痴呆的转变。自动电话系统用于记录研究参与者的语音样本，为识别和开发反映在语音记录的声学特征中的中枢神经系统功能障碍的新的、客观可量化的生物标记物提供了独特的机会。这样的生物标记物将有可能进行基于人群的认知筛查，以及对正在接受记忆障碍障碍治疗的患者进行远程纵向监测。

DESCRIPTION (provided by applicant): More efficient methods to screen and monitor elderly patients in clinical practice and research are needed, but visits to clinical offices are expensive and many older patient are restricted by mobility or transportation access. The Alzheimer's Disease Cooperative Study (ADCS) is evaluating several technology platforms for remotely monitoring patient status at home. Dr. Mary Sano leads this Home-Based Assessment (HBA) study, which completed patient recruitment several years ago and is now completing the final participant follow-up visits. All participants were comprehensively evaluated in diagnostic interviews by medical professionals at study baseline, and are completing similar evaluations at the end of the study (or when a change in clinical status is suspected). A speech-enabled, computer-automated telephone system using interactive voice response (IVR) technology, developed by Dr. Mundt's research team, is one component of the HBA study. Several of the IVR assessments record speech samples for linguistic analysis, acoustic characteristics of the speech patterns are not being analyzed and resources to do so are not included in the HBA study budget. Recent studies have demonstrated that analysis of vocal acoustic characteristics in speech can provide reliable, physiologically-based biomarkers of CNS functioning associated with major depression. Symptomatic similarities between clinical depression and early Alzheimer's disease have been noted for many years, but the extent of overlap and temporal sequencing of emergent symptoms remains unresolved. Objective, physiologically-based biomarkers of CNS dysfunction may provide new insights for diagnosing and managing Alzheimer's patients. The research proposed is to support the development and validation of potential screening measures that could be used for differential diagnosis in clinical practice, as well as provide a foundation for innovative assessment and management approaches for older persons with multiple chronic conditions. This application proposes to merge non-identifiable clinical outcomes measures and medical diagnoses obtained from HBA investigative sites across the nation with audio files of speech samples recorded by the IVR system developed by CPC. The speech samples will be analyzed by signal processing engineers at MIT's Lincoln Laboratory for acoustic properties reflecting physiologically-based biomarkers associated with CNS disorders such as Alzheimer's, Parkinson's, and depression. The clinical and diagnostic information available through the ADCS database will be used to develop and validate multivariate statistical models to improve diagnostic screening, noninvasive monitoring of disease progression, and/or differential diagnoses between conditions. PUBLIC HEALTH RELEVANCE: Restricted mobility of older patients limits research participation and access to treatment providers, so cognitive decline often goes undetected for longer periods than necessary. Efficient methods to remotely monitoring patients from home using automated telephone systems can improve assessment procedures, reduce access barriers, facilitate multicultural non-English speaking interactions, and enhance patient retention at minimal cost. The ADCS Home-Based Assessment Study has recruited a nationally-representative sample of 214 seniors and is monitoring them longitudinally for 4 years to observe emergence of amnestic MCI and conversion of MCI to mild dementia. An automated telephone system is used to record speech samples from study participants, providing a unique opportunity to identify and develop new, objectively- quantifiable biomarkers of CNS dysfunction reflected in the acoustic characteristic of the speech recordings. Such biomarkers would have the potential for population-based cognitive screening as well as remote longitudinal monitoring of patients being treated for memory impairment disorders.