Predicting long-term outcomes in preterm infants using multimodal neuroimaging techniques and environmental factors

使用多模式神经影像技术和环境因素预测早产儿的长期结局

基本信息

  • 批准号:
    10681464
  • 负责人:
  • 金额:
    $ 13.21万
  • 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:
    2022-08-10 至 2025-01-31
  • 项目状态:
    未结题

项目摘要

Project Summary/Abstract The outlined proposal expands the previous research in preterm infant brains by integrating multiple advanced neuroimaging methods, including novel quantitative magnetic resonance imaging (MRI) techniques and environmental factors to predict long-term neurodevelopmental issues. Preterm infants have a high rate of long-term neurodevelopmental impairments that often require additional health care and intervention. Recent advances in neuroimaging have provided great insight into the patterns of specific alterations in preterm infants. However, the studies are limited to demonstrate how brain function and structure and their interaction relate to or explain later neurodevelopmental outcomes in preterm infants. Further, while recent studies showed that microstructural tissue properties using recently developed quantitative MRI techniques (multi-shell diffusion tensor imaging, quantitative T1, qT1) are more sensitive and reliable to define underlying neurological diseases and, thus, it is crucial to investigate the microstructural tissue properties during the neonatal period to fully understand how these measures are related to preterm birth and predict later cognitive problems in preterm infants. The overarching aims of this project are designed to use neonatal multimodal neuroimaging techniques, including qT1, for the first time, combining with environmental factors using advanced computational approaches to define early biomarkers of later preterm neurodevelopmental outcomes. We hypothesize that the links between structural-functional brain networks are significantly altered, and when combined, will provide an exclusive prediction on later neurodevelopmental outcomes. Similarly, we will test the working hypothesis preterm infants will have abnormal white and grey matter microstructures, and these patterns will be correlated with the neurodevelopmental problems. Furthermore, we will explore the environmental factors contributing to later cognitive issues that will play an essential role in predicting later neurodevelopmental problems in preterm infants. The proposed research results will provide an early diagnostic tool that could inform the treatments and implementation of preventative interventions before any cognitive problem emerges. It also has an important impact on identifying behavioral targets to improve the life course outcomes in preterm infants.
项目总结/摘要 概述的提案通过整合多种先进的方法扩展了以前对早产儿大脑的研究。 神经成像方法,包括新的定量磁共振成像(MRI)技术, 环境因素来预测长期的神经发育问题。早产儿有很高的 长期的神经发育障碍,往往需要额外的医疗保健和干预。最近 神经影像学的进步为早产儿的特异性改变模式提供了深刻的见解, 婴儿。然而,这些研究仅限于展示大脑的功能和结构及其相互作用 与早产儿后期神经发育结果有关或解释。此外,虽然最近的研究 显示使用最近开发的定量MRI技术(多壳层)的微结构组织特性 弥散张量成像,定量T1,qT 1)更敏感和可靠,以确定潜在的神经 因此,研究新生儿期的微结构组织特性, 完全理解这些措施与早产的关系,并预测未来的认知问题, 早产儿该项目的总体目标是使用新生儿多模态神经成像 技术,包括qT 1,第一次,结合环境因素,使用先进的 计算方法来定义后期早产神经发育结果的早期生物标志物。我们 假设大脑结构-功能网络之间的联系发生了显著改变, 结合起来,将提供对以后神经发育结果的唯一预测。同样,我们将测试 工作假设早产儿将具有异常的白色和灰质微观结构,而这些 模式将与神经发育问题相关。此外,我们将探讨 环境因素导致后来的认知问题,这将在预测后来的认知问题中发挥重要作用。 早产儿的神经发育问题。该研究成果将提供一个早期 诊断工具,可以告知治疗和预防干预措施的实施, 出现了认知问题。它也对确定改善生活的行为目标有重要影响 早产儿的病程结局。

项目成果

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Elveda Gozdas其他文献

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{{ truncateString('Elveda Gozdas', 18)}}的其他基金

Predicting long-term outcomes in preterm infants using multimodal neuroimaging techniques and environmental factors
使用多模式神经影像技术和环境因素预测早产儿的长期结局
  • 批准号:
    10507663
  • 财政年份:
    2022
  • 资助金额:
    $ 13.21万
  • 项目类别:

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