脑灌注动力学失调与阿尔茨海默病有关。

IF 4.4 Q1 CLINICAL NEUROLOGY
Vasilis Marmarelis, Sandy Billinger, Elizabeth Joe, Dae Shin, Suhaib Hashem, Jasmin Rizko, Emily Hazen, Danilo Cardim, Jeff Burns, Rong Zhang, Helena C Chui
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引用次数: 0

摘要

一项由美国国立卫生研究院(NIH)资助的多中心研究开发并评估了一种名为“脑血管动力学指数”(CDI)的新型生理标志物,用于改善轻度认知障碍(MCI)及其向阿尔茨海默病(AD)过渡的诊断。方法:CDI利用相关时间序列数据,通过预测动态建模,量化脑灌注和氧合(随时间自主调节血流量和氧输送)的调节动力学。结果:横断面结果显示,CDI对90例MCI/AD患者与77例对照患者的鉴别诊断表现出色(曲线下面积(AUC) = 0.96),超过了常用的淀粉样蛋白正电子放射断层扫描-标准化摄取值比(PET-SUVR) (AUC = 0.78)或迷你精神状态检查(MMSE)和蒙特利尔认知评估(MoCA)的认知筛查测试(AUC分别= 0.91和0.92)。CDI也可以用于疾病分期,因为它从34名轻度AD参与者中区分了56名MCI (AUC = 0.98)。结论:这些发现为MCI和AD的高性能诊断生理标志物提供了希望,可以在临床环境中以舒适,快速和自动化的方式获得。重点:脑血管动力学指数(CDI)是一种量化脑灌注调节动态的新型生理标志物。与现有标志物相比,CDI可改善轻度认知障碍/阿尔茨海默病(MCI/AD)的诊断(曲线下面积[AUC] >0.95)。CDI无创、客观、快速、廉价。CDI表现支持脑血管功能障碍在AD中的关键作用。CDI是通过血流动力学/氧合时间序列数据的动态建模获得的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Dysregulation of cerebral perfusion dynamics is associated with Alzheimer's disease.

Dysregulation of cerebral perfusion dynamics is associated with Alzheimer's disease.

Dysregulation of cerebral perfusion dynamics is associated with Alzheimer's disease.

Introduction: A novel physio-marker, termed "cerebrovascular dynamics index" (CDI), was developed and evaluated in a multi-center National Institutes of Health (NIH)-funded study for improved diagnosis of mild cognitive impairment (MCI) and its transition to Alzheimer's disease (AD).

Methods: The CDI quantifies the regulation dynamics of cerebral perfusion and oxygenation (which adjust autonomously blood flow and oxygen delivery over time) through predictive dynamic modeling using relevant time-series data.

Results: Cross-sectional results demonstrated excellent diagnostic performance of CDI in differentiating 90 MCI/AD patients from 77 controls (area under the curve (AUC) =  0.96), which surpassed the commonly used biomarker of amyloid positron emission tomography-standardized uptake value ratio (PET-SUVR) (AUC = 0.78) or cognitive screening tests of Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) (AUC = 0.91 and 0.92, respectively). The CDI can also be used for disease staging because it differentiated 56 MCI from 34 mild AD participants (AUC = 0.98).

Conclusion: These findings offer the promise of a high-performance diagnostic physio-marker for MCI and AD, which can be obtained in a comfortable, rapid, and automated manner in clinical settings.

Highlights: Novel physio-marker (cerebrovascular dynamics index [CDI]) quantifies the regulation dynamics of cerebral perfusion.The CDI was shown to improve mild cognitive impairment/Alzheimer's disease (MCI/AD) diagnosis (area under the curve [AUC] >0.95) relative to existing markers.The CDI is obtained non-invasively, objectively, rapidly, and inexpensively.The CDI performance supports the key role of cerebrovascular dysfunction in AD.The CDI is obtained via dynamic modeling of hemodynamic/oxygenation time-series data.

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来源期刊
CiteScore
7.80
自引率
7.50%
发文量
101
审稿时长
8 weeks
期刊介绍: Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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