Development and validation of novel tests in the DCT drawing analysis platform for the detection of Alzheimer’s Disease-related early cognitive impairment

在 DCT 绘图分析平台中开发和验证新测试，用于检测阿尔茨海默病相关的早期认知障碍

• 批准号: 9909246
• 负责人: William Souillard-Mandar
• 金额: $ 12.92万
• 依托单位: DIGITAL COGNITION TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2020-05-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9909246
• 关键词: Algorithms; Alzheimer disease detection; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; Amyloid; Artificial Intelligence; Behavior; Behavioral; Biological Markers; Caring; Clinical Trials; Cognition; Cognitive; Collection; Computer software; Data; Data Analyses; Data Collection; Data Reporting; Data Set; Dementia; Development; Early Diagnosis; Ensure; Environment; Foundations; Future; Genetic Risk; Goals; Health Insurance Portability and Accountability Act; Home environment; Impaired cognition; Impairment; Individual; Infrastructure; Intuition; Machine Learning; Measurement; Measures; Monitor; Motion; Neuropsychological Tests; Neuropsychology; Paper; Participant; Patient Care; Patients; Performance; Phase; Receiver Operating Characteristics; Research; Research Personnel; Risk; Sensitivity and Specificity; Small Business Innovation Research Grant; Structure; System; Tablets; Technology; Testing; Therapeutic Agents; Time; Training; Validation; Visit; Visual; Work; base; care providers; cloud based; cognitive change; cognitive testing; cost effective; demented; digital; improved; information processing; input device; memory process; novel; novel therapeutics; pre-clinical; processing speed; recruit; signal processing; stability testing; tau Proteins; web portal

Project Summary/Abstract Early detection of AD and AD-related dementias is critical for the development of novel therapeutic agents and for effective patient treatment and care. DCT has created a platform able to detect subtle changes in behavior indicative of early cognitive impairment by using a digital pen to record drawing motions and automatically analyzing that data using a combination of artificial intelligence and neuropsychological analysis. DCT has successfully launched its first test on the platform, DCTclockTM, which has been demonstrated to detect subtle cognitive change in early Alzheimer’s Disease (AD) and AD-related dementias earlier than standard cognitive tests, correlate with known AD biomarkers such as amyloid and tau in preclinical-AD subjects, and detect known APOE genetic risk in cognitively healthy participants. The test is FDA-cleared to market for general cognitive assessment and is currently used in multinational clinical trials, research initiatives, and by practicing clinicians for patient care. DCT is now conducting a study involving 400 participants ranging from cognitively healthy to demented to validate a tablet as input device for the drawing data, and to collect data on a set of novel tablet-based drawing tasks including: a symbol task, a visual retention task, a trail making task, a path- finding task, and a visuoconstructional task. We aim to analyze task data collected in the study to produce a set of easily-deployable, rapid, cost-effective, and sensitive tests to be used as cognitive digital biomarkers in clinical trials for AD and AD-related dementias. The first aim is to develop novel cognitive measures from these additional tests and obtain preliminary validation. Existing data will be split into training and testing sets. The training set will be analyzed to develop metrics, following an interpretable hierarchical analysis structure with low-level drawing measurements combined in a set of composite scales tied to a cognitive concept (i.e., information processing), and then further combined to obtain a simple 0-100 score for performance on the test. The testing set will be used to conduct preliminary validation consisting of a Receiver Operating Characteristic curve analysis, correlation measures to existing neuropsychological tests, and test-retest reliability measurements to ensure repeat testing stability. The second aim is to implement the developed metrics in the commercial DCT platform. Robust software will be created for the measurement, storage, and display of the novel metrics, setting a foundation to enable usage of the metrics by research and commercial partners.

项目总结/摘要 AD和AD相关痴呆的早期检测对于开发新的治疗剂和治疗方法至关重要。 进行有效的病人治疗和护理。DCT创建了一个能够检测行为细微变化的平台 通过使用数字笔记录绘画动作并自动地 结合人工智能和神经心理学分析来分析这些数据。DCT具有 成功推出了其在平台上的第一个测试，DCTclockTM，已被证明可以检测微妙的 早期阿尔茨海默病（AD）和AD相关痴呆的认知变化早于标准认知变化。 测试，与临床前AD受试者中已知的AD生物标志物如淀粉样蛋白和tau相关，并检测 认知健康参与者中已知的APOE遗传风险。该测试是FDA批准上市的一般 认知评估，目前用于多国临床试验，研究计划，并通过实践 临床医生对病人的护理。DCT目前正在进行一项涉及400名参与者的研究， 健康到精神错乱，以验证平板电脑作为绘图数据的输入设备，并收集一组 新颖的基于平板电脑的绘图任务，包括：符号任务、视觉保持任务、轨迹制作任务、路径 寻找任务和视觉建构任务。 我们的目标是分析在研究中收集的任务数据，以产生一套易于部署，快速，成本效益， 和敏感性测试，用作AD和AD相关痴呆临床试验中的认知数字生物标志物。 第一个目标是从这些额外的测试中开发新的认知测量方法，并获得初步的 验证。现有数据将被分为训练集和测试集。将对训练集进行分析， 指标，遵循可解释的分层分析结构，具有低级绘图测量 结合在与认知概念相关的一组复合量表中（即，信息处理），然后 进一步组合以获得测试表现的简单0 - 100分。测试集将用于 进行初步验证，包括受试者工作特征曲线分析、相关性 现有的神经心理学测试的措施，以及重测信度测量，以确保重复 测试稳定性。第二个目标是在商业DCT平台上实现所开发的度量。 将为新指标的测量、存储和显示创建强大的软件， 基金会，使研究和商业合作伙伴能够使用这些指标。