Improving an EEG-based neurodiagnostic software platform to detect Alzheimer's Disease in MCI patients
改进基于脑电图的神经诊断软件平台来检测 MCI 患者的阿尔茨海默病
基本信息
- 批准号:10546255
- 负责人:
- 金额:$ 29.98万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-15 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAddressAffectAlgorithmsAlzheimer disease screeningAlzheimer&aposs DiseaseAlzheimer&aposs disease careAlzheimer&aposs disease diagnosisAlzheimer’s disease biomarkerBehavioral SymptomsBiological MarkersClinicClinicalCognitiveCollaborationsComputer softwareCountryDataData PoolingDementiaDetectionDiagnosisDiseaseDisease ProgressionEarly DiagnosisElderlyElectroencephalographyEnsureFeedbackHealthHealth Care CostsHumanImpaired cognitionMachine LearningMeasuresMedicalMethodsMissionModelingNerve DegenerationNeurologicNeurologistOutcome MeasurePathologicPathway interactionsPatient CarePatientsPerformancePersonsPhasePhysiciansProcessPsyche structureReportingResearchScanningSensitivity and SpecificitySpecificityStandardizationSymptomsSystemTechniquesTechnologyTestingTimeTissuesTrainingUnited StatesWorkaging populationbaseclinical carecostcost effectivedata acquisitiondiagnostic toolexperiencehuman old age (65+)improvedinsightmild cognitive impairmentminimally invasivenovelnovel markerpreservationsatisfactionscreening programsuccesstoolusabilityuser-friendly
项目摘要
PROJECT SUMMARY
Alzheimer’s disease (AD) is a progressive, neurodegenerative condition and the most common cause of
dementia. In the United States, an estimated 6.2 million people over the age of 65 are living with AD, 72% of
whom are over 75 years old. Given the country’s aging population, this number is expected to more than triple
by 2050, costing the United States an annual $600 billion in associated healthcare costs. Early diagnosis is
crucial to AD treatment because it allows clinicians more time to find and initiate treatment pathways, which
decreases disease progression and preserves mental capacity. New research suggests that biomarkers can
help diagnose AD years before symptoms appear. Despite recent technological advancements, many tools and
technologies that measure biomarkers are invasive, expensive, and not sensitive or specific enough, particularly
when detecting the disease at earlier stages, limiting their usability.
When combined with advanced machine learning techniques, electroencephalography (EEG) has been shown
to address many of the existing issues related to AD biomarkers. At SPARK Neuro, we aim to unlock the full
potential of EEG through a novel software platform. Combining EEG with the capabilities of machine learning,
our model better assesses cognitive health and neurodegeneration, aiding the diagnosis of AD. SPARK’s
neuroanalytic platform will be a standardized, objective, non-invasive, cost-effective diagnostic tool capable of
highly sensitive and specific detection of cognitive impairment across the entire disease continuum. Our platform
would vastly expand AD screening initiatives and provide neurological insights to aid in the diagnosis and tracking
of disease progression.
During the proposed Phase I research, we will work in collaboration with Mayo Clinic to extend our current
algorithm to assess and differentiate patients in the earlier, mild cognitive impairment stage of the disease, and
provide highly useful and usable reports to clinicians. First, we will optimize the algorithm by incorporating EEG
data collected from Mayo Clinic patients. Next, we will focus on improving the user experience of both EEG data
acquisition and clinical reporting. We will enhance end-user satisfaction and optimize the technology to fit within
current clinical workflows. Participating Mayo Clinic EEG technicians will provide feedback. Once optimized,
SPARK’s approach will constitute the first in-office EEG-based neurodiagnostic tool specifically for diagnosing
and tracking AD. Our non-invasive solution has the potential to accelerate AD screening programs, detect
pathological AD at earlier stages, and provide individualized disease progression insights.
项目摘要
阿尔茨海默病(AD)是一种进行性神经退行性疾病,是阿尔茨海默病最常见的病因。
痴呆在美国,估计有620万65岁以上的人患有AD,72%的人患有AD。
年龄超过75岁。鉴于该国人口老龄化,这一数字预计将增加两倍以上
到2050年,美国每年将花费6000亿美元的相关医疗费用。早期诊断是
这对AD治疗至关重要,因为它使临床医生有更多的时间来寻找和启动治疗途径,
减少疾病进展并保持智力。新的研究表明,生物标志物可以
有助于在症状出现前几年诊断AD。尽管最近的技术进步,许多工具和
测量生物标志物的技术是侵入性的,昂贵的,不够敏感或特异,特别是
当在早期阶段检测疾病时,限制了它们的可用性。
当与先进的机器学习技术相结合时,脑电图(EEG)已被证明是
以解决与AD生物标志物相关的许多现有问题。在SPARK Neuro,我们的目标是解锁整个
通过一个新的软件平台的EEG的潜力。结合脑电图和机器学习的能力,
我们的模型更好地评估认知健康和神经退行性变,有助于AD的诊断。SPARK的
神经分析平台将是一种标准化、客观、非侵入性、具有成本效益的诊断工具,
高灵敏度和特异性检测整个疾病连续体中的认知障碍。我们的平台
将大大扩展AD筛查计划,并提供神经学见解,以帮助诊断和跟踪
疾病的发展。
在拟议的I期研究期间,我们将与马约诊所合作,
评估和区分疾病早期、轻度认知障碍阶段患者的算法,以及
为临床医生提供高度有用和可用的报告。首先,我们将优化算法,纳入脑电图
数据收集自马约诊所患者。接下来,我们将重点提升两种脑电数据的用户体验
采集和临床报告。我们将提高最终用户的满意度,并优化技术,
当前临床工作流程。参与的马约诊所EEG技术人员将提供反馈。一旦优化,
SPARK的方法将构成第一个基于办公室EEG的神经诊断工具,专门用于诊断
追踪AD我们的非侵入性解决方案有可能加速AD筛查计划,
病理性AD,并提供个性化的疾病进展的见解。
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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Richard J. Caselli其他文献
Color Fundus Photography and Deep Learning Applications in Alzheimer Disease
- DOI:
10.1016/j.mcpdig.2024.08.005 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Oana M. Dumitrascu;Xin Li;Wenhui Zhu;Bryan K. Woodruff;Simona Nikolova;Jacob Sobczak;Amal Youssef;Siddhant Saxena;Janine Andreev;Richard J. Caselli;John J. Chen;Yalin Wang - 通讯作者:
Yalin Wang
Deciphering distinct genetic risk factors for FTLD-TDP pathological subtypes via whole-genome sequencing
通过全基因组测序破译额颞叶痴呆-TDP 病理亚型的不同遗传危险因素
- DOI:
10.1038/s41467-025-59216-0 - 发表时间:
2025-04-25 - 期刊:
- 影响因子:15.700
- 作者:
Cyril Pottier;Fahri Küçükali;Matt Baker;Anthony Batzler;Gregory D. Jenkins;Marka van Blitterswijk;Cristina T. Vicente;Wouter De Coster;Sarah Wynants;Pieter Van de Walle;Owen A. Ross;Melissa E. Murray;Júlia Faura;Stephen J. Haggarty;Jeroen GJ. van Rooij;Merel O. Mol;Ging-Yuek R. Hsiung;Caroline Graff;Linn Öijerstedt;Manuela Neumann;Yan Asmann;Shannon K. McDonnell;Saurabh Baheti;Keith A. Josephs;Jennifer L. Whitwell;Kevin F. Bieniek;Leah Forsberg;Hilary Heuer;Argentina Lario Lago;Ethan G. Geier;Jennifer S. Yokoyama;Alexis P. Oddi;Margaret Flanagan;Qinwen Mao;John R. Hodges;John B. Kwok;Kimiko Domoto-Reilly;Matthis Synofzik;Carlo Wilke;Chiadi Onyike;Bradford C. Dickerson;Bret M. Evers;Brittany N. Dugger;David G. Munoz;Julia Keith;Lorne Zinman;Ekaterina Rogaeva;EunRan Suh;Tamar Gefen;Changiz Geula;Sandra Weintraub;Janine Diehl-Schmid;Martin R. Farlow;Dieter Edbauer;Bryan K. Woodruff;Richard J. Caselli;Laura L. Donker Kaat;Edward D. Huey;Eric M. Reiman;Simon Mead;Andrew King;Sigrun Roeber;Alissa L. Nana;Nilufer Ertekin-Taner;David S. Knopman;Ronald C. Petersen;Leonard Petrucelli;Ryan J. Uitti;Zbigniew K. Wszolek;Eliana Marisa Ramos;Lea T. Grinberg;Maria Luisa Gorno Tempini;Howard J. Rosen;Salvatore Spina;Olivier Piguet;Murray Grossman;John Q. Trojanowski;C. Dirk Keene;Lee-Way Jin;Johannes Prudlo;Daniel H. Geschwind;Robert A. Rissman;Carlos Cruchaga;Bernardino Ghetti;Glenda M. Halliday;Thomas G. Beach;Geidy E. Serrano;Thomas Arzberger;Jochen Herms;Adam L. Boxer;Lawrence S. Honig;Jean P. Vonsattel;Oscar L. Lopez;Julia Kofler;Charles L. White;Marla Gearing;Jonathan Glass;Jonathan D. Rohrer;David J. Irwin;Edward B. Lee;Vivianna Van Deerlin;Rudolph Castellani;Marsel M. Mesulam;Maria C. Tartaglia;Elizabeth C. Finger;Claire Troakes;Safa Al-Sarraj;Clifton L. Dalgard;Bruce L. Miller;Harro Seelaar;Neill R. Graff-Radford;Bradley F. Boeve;Ian RA. Mackenzie;John C. van Swieten;William W. Seeley;Kristel Sleegers;Dennis W. Dickson;Joanna M. Biernacka;Rosa Rademakers - 通讯作者:
Rosa Rademakers
Richard J. Caselli的其他文献
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{{ truncateString('Richard J. Caselli', 18)}}的其他基金
APOE in the Predisposition to, Protection from and Prevention of Alzheimer's Disease
APOE 在阿尔茨海默病的易感性、预防和预防中的作用
- 批准号:
10271403 - 财政年份:2020
- 资助金额:
$ 29.98万 - 项目类别:
APOE in the Predisposition to, Protection from and Prevention of Alzheimer's Disease
APOE 在阿尔茨海默病的易感性、预防和预防中的作用
- 批准号:
10600977 - 财政年份:2020
- 资助金额:
$ 29.98万 - 项目类别:
Brain Imaging, APOE & the Preclinical Course of Alzheimer's Disease
脑成像,APOE
- 批准号:
8696480 - 财政年份:2008
- 资助金额:
$ 29.98万 - 项目类别:
Brain Imaging, APOE & the Preclinical Course of Alzheimer's Disease
脑成像,APOE
- 批准号:
9086939 - 财政年份:2008
- 资助金额:
$ 29.98万 - 项目类别:
Brain Imaging, APOE & the Preclinical Course of Alzheimer's Disease
脑成像,APOE
- 批准号:
9042912 - 财政年份:2008
- 资助金额:
$ 29.98万 - 项目类别:
Brain Imaging, APOE & the Preclinical Course of Alzheimer's Disease
脑成像,APOE
- 批准号:
8843319 - 财政年份:2008
- 资助金额:
$ 29.98万 - 项目类别:
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