Noninvasive Noncontact High-Density Optical Imaging of Neonatal Intraventricular Hemorrhage

新生儿脑室内出血的无创非接触式高密度光学成像

基本信息

  • 批准号:
    10381502
  • 负责人:
  • 金额:
    $ 53.66万
  • 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
  • 起止时间:
    2020-04-10 至 2025-03-31
  • 项目状态:
    未结题

项目摘要

ABSTRACT Germinal matrix-intraventricular hemorrhage (GM-IVH) is a major complication of premature birth, occurring in up to 45% of very low birthweight neonates (<1500 g) due to fragility of immature blood vessels within the germinal matrix. GM-IVH can also lead to hydrocephalus (HCP) and increased intracranial pressure, which further induces inflammation and brain tissue injury. Though neonatal GM-IVH and HCP are increasingly common due to the rising survival rate of preterm births, there are no established biomarkers or guidelines for their treatments to prevent brain injury. Preterm infants with GM-IVH/HCP are vulnerable to alterations in cerebral blood flow (CBF) because they have impaired cerebrovascular autoregulation. However, there are no reliable functional imaging methods at the bedside of neonatal intensive care units (NICUs) for repeatedly assessing either degree of cerebral injury or effectiveness of interventions. Near-infrared spectroscopy and tomography technologies have been used for decades as noninvasive bedside tools for continuous monitoring of cerebral blood oxygen saturation (StO2). However, most systems lack the combination of spatial resolution and wide field- of-view (FOV) to image distributed brain functions and discriminate the brain signal from overlaying scalp and skull. A few high-density tomographic systems use numerous discrete sources and detectors coupled with fiber bundles to a head cap. However, adjusting and maintaining a stable optical coupling of numerous fibers to a small fragile neonatal head (i.e., a contact measurement) is labor-intensive and poses great challenges to head cap design with safety concern. To overcome these limitations, we propose to develop a novel, noncontact, high-density-detection (using a CCD/CMOS camera), multi-wavelength speckle contrast diffuse correlation tomography (MW-scDCT) system to accommodate fast, high-resolution, functional imaging of both CBF and StO2 over a large FOV on the neonatal head. The MW-scDCT will be rigorously calibrated and optimized using standard tissue phantoms (Aim 1). In vivo calibration/evaluation will be conducted against MRI and histological examination in an IVH/HCP model of neonatal piglets who preserve great similarities with human neonates (Aim 2). A pilot clinical observational study will be performed in preterm neonates with GM-IVH/HCP under standard of care in the NICU (Aim 3). Cerebral hemodynamics/metabolism, cerebrovascular autoregulation, and cerebral functional connectivity will be analyzed from serial functional images taken over several weeks after birth. We hypothesize that cerebral hemodynamic/metabolic alterations detected by MW-scDCT correlate with progression of brain injury after GM-IVH/HCP and recovery after treatment. Multiple parameters will provide more comprehensive assessments of neonatal brain injury/recovery compared to a single parameter alone. This study will fulfill a critical need in the field of neonatology to provide objective measures/biomarkers to guide timing of treatment for GM-IVH and HCP. We anticipate that noninvasive, repeated, and longitudinal cerebral monitoring for the guidance of interventions could be eventually implemented as standard of care in NICUs.
摘要 脑室内出血(GM-IVH)是早产的一种主要并发症, 高达45%的极低出生体重新生儿(<1500 g)由于血管内未成熟血管的脆弱性, 几何矩阵GM-IVH还可导致脑积水(HCP)和颅内压升高, 进一步诱发炎症和脑组织损伤。虽然新生儿GM-IVH和HCP越来越多, 由于早产存活率的上升,目前还没有确定的生物标志物或指南, 防止脑损伤的治疗方法患有GM-IVH/HCP的早产儿易受脑内 血流量(CBF),因为他们有受损的脑血管自动调节。然而,没有可靠的 新生儿重症监护病房(NICU)床边功能成像方法,用于反复评估 脑损伤程度或干预措施的有效性。近红外光谱和层析成像 这些技术已经作为非侵入性床边工具使用了几十年, 血氧饱和度(StO 2)。然而,大多数系统缺乏空间分辨率和宽视场的组合, 视野(FOV)来对分布式脑功能进行成像,并从覆盖的头皮和 头骨少数高密度层析成像系统使用许多离散源和与光纤耦合的检测器 捆到头帽上。然而,调节和维持多个光纤到光纤的稳定光耦合是不可能的。 小而脆弱的新生儿头部(即,接触式测量)是劳动密集型的, 具有安全考虑的帽设计。为了克服这些局限性,我们建议开发一种新颖的,非接触的, 高密度检测(使用CCD/CMOS相机),多波长散斑对比度扩散相关 断层扫描(MW-scDCT)系统,以适应CBF和 新生儿头部大FOV范围内的StO 2。MW-scDCT将通过以下方式进行严格校准和优化: 标准组织模型(Aim 1)。将根据MRI和组织学进行体内校准/评价 在新生仔猪IVH/HCP模型中进行检查,这些新生仔猪与人类新生儿保持很大的相似性(目的 2)的情况。将在患有GM-IVH/HCP的早产儿中进行一项初步临床观察性研究, NICU的护理(目标3)。脑血流动力学/代谢、脑血管自动调节和脑 将根据出生后几周内拍摄的系列功能图像分析功能连接性。我们 假设MW-scDCT检测到脑血流动力学/代谢改变与 GM-IVH/HCP后脑损伤的进展和治疗后的恢复。多个参数将提供 与单独的单个参数相比,更全面地评估新生儿脑损伤/恢复。这 本研究将满足乳腺病学领域的一项关键需求,即提供客观指标/生物标志物以指导时间选择 GM-IVH和HCP的治疗。我们预计,无创,重复,纵向脑监测, 指导干预措施最终可作为NICU的护理标准实施。

项目成果

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Guoqiang Yu其他文献

Guoqiang Yu的其他文献

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{{ truncateString('Guoqiang Yu', 18)}}的其他基金

Time-resolved laser speckle contrast imaging of resting-state functional connectivity in neonatal brain
新生儿大脑静息态功能连接的时间分辨激光散斑对比成像
  • 批准号:
    10760193
  • 财政年份:
    2023
  • 资助金额:
    $ 53.66万
  • 项目类别:
Development of a Wearable Fluorescence Imaging Device for IntraoperativeIdentification of Brain Tumors
开发用于术中识别脑肿瘤的可穿戴荧光成像装置
  • 批准号:
    10697009
  • 财政年份:
    2023
  • 资助金额:
    $ 53.66万
  • 项目类别:
Integrating Astrocytes into Models of Neural Circuits Regulating Behavior
将星形胶质细胞整合到调节行为的神经回路模型中
  • 批准号:
    10294803
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
Data Science Core
数据科学核心
  • 批准号:
    10294802
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
Integrating Astrocytes into Models of Neural Circuits Regulating Behavior
将星形胶质细胞整合到调节行为的神经回路模型中
  • 批准号:
    10461225
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
Integrating Astrocytes into Models of Neural Circuits Regulating Behavior
将星形胶质细胞整合到调节行为的神经回路模型中
  • 批准号:
    10693168
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
Data Science Core
数据科学核心
  • 批准号:
    10461224
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
Data Science Core
数据科学核心
  • 批准号:
    10693164
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
High-density optical tomography of cerebral blood flow and metabolism in small animals
小动物脑血流和代谢的高密度光学断层扫描
  • 批准号:
    10323090
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:
High-density optical tomography of cerebral blood flow and metabolism in small animals
小动物脑血流和代谢的高密度光学断层扫描
  • 批准号:
    10461939
  • 财政年份:
    2021
  • 资助金额:
    $ 53.66万
  • 项目类别:

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