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Optimizing MRS to Detect Mild Cognitive Impairment

优化 MRS 以检测轻度认知障碍

基本信息

批准号：
7491665
负责人：
Ileana Hancu
金额：
$ 31.38万
依托单位：
GENERAL ELECTRIC GLOBAL RESEARCH CTR
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-01 至 2010-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7491665
关键词：
Acute Brain Injuries Affect Age Alzheimer&apos s Disease Autopsy Biochemistry Brain Cell Count Characteristics Class Clinical Clinical Research Clinical Trials Computer software Creatine Daily Data Dementia Detection Development Diagnosis Diagnostic Diffusion Disease Down-Regulation Equipment Evaluation Glutamates Glutamine Glycine Goals Gold Guidelines Hepatic Encephalopathy Hip region structure Hippocampus (Brain)Image In Vitro Individual Inositol Intervention Left Libraries Literature Magnetic Resonance Spectroscopy Manufacturer Name Measurement Measures Medical center Memory Memory impairment Methods Modification Monitor Multiple Sclerosis N-acetylaspartate Neurofibrillary Tangles Neuroglia Neurologic Neurons Neuropsychological Tests Patient Monitoring Patients Persons Pharmaceutical Preparations Physicians Physiologic pulse Psychometrics Pulse taking Rate Recruitment Activity Reporting Reproducibility Research Retrospective Studies Risk Senile Plaques Severity of illness Simulate Staging Standards of Weights and Measures Structure Symptoms Taurine Techniques Testing Time Tissues Work base cohort cost data acquisition drug development improved in vivo interest mild neurocognitive impairment normal aging novel programs prospective research study simulation success volunteer

项目摘要

DESCRIPTION (provided by applicant): The long term goal of the proposed research is to develop novel magnetic resonance spectroscopy (MRS) data acquisition techniques, capable to identify and monitor patients affected by mild cognitive impairment (MCI). MCI is generally defined as a transitional state between normal aging and dementia, and is currently diagnosed through extensive neuropsychological testing. A hallmark characteristic of this transitional state is an early change in the brain biochemistry, which can be non-invasively detected through 1H MRS techniques. Such techniques also have the potential to provide faster, more efficient treatment monitoring in MCI and disease detection prior to the onset of memory impairment symptoms. We will carefully optimize 1H MRS data acquisition techniques, to accurately measure two metabolites whose concentrations are reported to change in MCI: myo-Inositol (mI) -a marker of glial cell numbers- and N-acetyl aspartate (NAA)-a marker of neuronal integrity. Through simulations, we will tailor pulse sequences to acquire simplified in vivo spectra, by filtering out metabolites reported to be constant in the disease, while maintaining the two metabolites of interest in the spectrum. We hypothesize that simpler spectra will leave less room for error while quantifying data through fitting, therefore allowing increased measurement reproducibility and the detection of smaller changes that can be attributed to disease or treatment. We will implement the most successful pulse sequences on a 3T clinical scanner, and perform in vitro experiments to validate the improved measurement reproducibility for the metabolites of interest. Through a comprehensive partnership between GE Global Research and Albany Medical Center, we will also compare the sensitivities of the newly developed methods in separating a cohort of MCI patients from a cohort of age-matched normal controls. Tailoring pulse sequences for accurate NAA and mI detection may significantly improving MCI diagnosis and monitoring. Decreased disease diagnosis costs, as well as more efficient monitoring of disease, leading to lower clinical trial costs involving MCI patients, can be obtained as a consequence of this study. Moreover, the direct results of this study, i.e., metabolite tailored pulse sequences, have the potential to benefit detection and monitoring of other diseases, in which up- or down- regulation of NAA or mI are reported including multiple sclerosis, acute brain injury, or hepatic encephalopathy.

描述（由申请人提供）：拟议研究的长期目标是开发新型磁共振波谱（MRS）数据采集技术，能够识别和监测受轻度认知障碍（MCI）影响的患者。MCI通常被定义为正常衰老和痴呆之间的过渡状态，目前通过广泛的神经心理学测试进行诊断。这种过渡状态的标志性特征是脑生物化学的早期变化，这可以通过1H MRS技术非侵入性地检测到。这些技术也有可能提供更快，更有效的治疗监测MCI和疾病检测之前的记忆障碍症状发作。我们将仔细优化1H MRS数据采集技术，以准确测量两种代谢物，据报道，这两种代谢物的浓度在MCI中会发生变化：肌肌醇（mI）-神经胶质细胞数量的标志物-和N-乙酰天冬氨酸（NAA）-神经元完整性的标志物。通过模拟，我们将定制脉冲序列，以获得简化的体内光谱，通过过滤掉代谢物报告是恒定的疾病，同时保持在频谱中的两个感兴趣的代谢物。我们假设，更简单的光谱将留下更少的误差空间，同时通过拟合量化数据，因此允许增加测量重现性和检测可归因于疾病或治疗的较小变化。我们将在3 T临床扫描仪上实现最成功的脉冲序列，并进行体外实验，以验证感兴趣的代谢物的测量重现性。通过GE全球研究中心和奥尔巴尼医学中心之间的全面合作，我们还将比较新开发的方法在分离MCI患者队列和年龄匹配的正常对照队列方面的灵敏度。为准确的NAA和mI检测定制脉冲序列可以显著改善MCI的诊断和监测。降低疾病诊断成本，以及更有效的疾病监测，导致涉及MCI患者的临床试验成本降低，可以作为本研究的结果。此外，这项研究的直接结果，即，代谢物定制的脉冲序列具有有益于检测和监测其它疾病的潜力，其中报道了NAA或mI的上调或下调，包括多发性硬化、急性脑损伤或肝性脑病。