Development and validation of novel tests in the DCT drawing analysis platform for the detection of Alzheimer’s Disease-related early cognitive
Development and validation of novel tests in the DCT drawing analysis platform for the detection of Alzheimer’s Disease-related early cognitive
批准号:
10221367
负责人:
Sean Michael Tobyne
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
项目状态:
已结题
起止时间:
2020-05-02 至 2022-02-28
中文摘要
项目总结/文摘
英文摘要
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.
期刊论文(0)
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科研奖励(0)
会议论文
Predicting Whole Brain Multi-Sensory Cognitive Control Networks: Relationship with Neuropsychological Test Performance and Repetitive Head Impact
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批准号:9395139
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项目类别:
-
资助金额:$3.23万
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财政年份:2017
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负责人:Sean Michael Tobyne
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依托单位:
海外基金