Development and validation of novel tests in the DCT drawing analysis platform for the detection of Alzheimer’s Disease-related early cognitive
在 DCT 绘图分析平台中开发和验证新测试,用于检测与阿尔茨海默病相关的早期认知
基本信息
- 批准号:10221367
- 负责人:
- 金额:$ 23.78万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-05-02 至 2022-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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. Linus Health has acquired 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.
DCTclockTM, the first test on this platform, has been successfully launched and is able 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. Linus Health is now conducting a study involving ~200 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 Linus 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.
项目摘要/摘要
早期发现阿尔茨海默病和阿尔茨海默病相关痴呆对于开发新型治疗药物和
进行有效的病人治疗和护理。Linus Health收购了一个平台,能够检测到
使用数字笔记录绘画动作和早期认知障碍的行为
使用人工智能和神经心理学分析的组合来自动分析这些数据。
DCTclockTM是该平台上的第一个测试,已经成功启动,能够检测到细微的
早期阿尔茨海默病(AD)和AD相关痴呆的认知改变早于标准认知
测试,与已知的AD生物标志物,如临床前AD患者中的淀粉样蛋白和tau相关,并检测
认知健康参与者中已知的载脂蛋白E遗传风险。该测试获得了FDA批准上市的通用性
认知评估,目前用于跨国临床试验、研究计划和实践
临床医生为病人提供护理。Linus Health现在正在进行一项研究,涉及约200名参与者,范围从
将平板电脑作为图形数据的输入设备进行验证,并在以下方面收集数据:认知健康到精神错乱
一组新颖的基于平板的绘画任务,包括:符号任务、视觉保持任务、轨迹绘制任务、
寻路任务和视觉建构任务。
我们的目标是分析研究中收集的任务数据,以产生一套易于部署、快速、经济高效的
敏感测试将在AD和AD相关痴呆的临床试验中用作认知数字生物标记物。
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。现有数据将被分成训练集和测试集。将对训练集进行分析以开发
指标,遵循带有低级绘图测量的可解释的分层分析结构
组合成一组与认知概念(即信息处理)捆绑在一起的复合量表,然后
进一步结合在一起,得到了简单的0-100分的测试表现。测试集将用于
进行初步验证,包括接收器工作特性曲线分析、关联
对现有神经心理测试的措施,以及确保重复性的重测信度测量
测试稳定性。第二个目标是在商业Linus平台上实现开发的指标。
将为新指标的测量、存储和显示创建强大的软件,设置
基金会,使研究和商业合作伙伴能够使用这些指标。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Sean Michael Tobyne其他文献
Sean Michael Tobyne的其他文献
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{{ truncateString('Sean Michael Tobyne', 18)}}的其他基金
Predicting Whole Brain Multi-Sensory Cognitive Control Networks: Relationship with Neuropsychological Test Performance and Repetitive Head Impact
预测全脑多感官认知控制网络:与神经心理学测试表现和重复头部冲击的关系
- 批准号:
9395139 - 财政年份:2017
- 资助金额:
$ 23.78万 - 项目类别:
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