3D Functional Photoacoustic Imaging of Human Brain with a Stretchable Ultrasound Matrix Array

使用可拉伸超声矩阵阵列对人脑进行 3D 功能光声成像

基本信息

  • 批准号:
    10252441
  • 负责人:
  • 金额:
    $ 86.74万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-05 至 2024-09-04
  • 项目状态:
    已结题

项目摘要

Abstract Many scientific efforts have been devoted to understanding the brain functions, and the relevance of its dynamics during development, aging, and in diseased conditions. Alterations of the brain functions can result from multifactorial processes and be reflected by various biomarkers. The ability to quantify these changes at multiple scales will improve our understanding of brain anatomical and functional architectures, and the relations between these networks in both normal and diseased conditions. By virtue of the rich optical absorption contrast, high spatial and temporal resolutions, and relatively deep penetration, photoacoustic tomography (PAT) is a promising imaging modality that can address the limitations of functional magnetic resonance imaging (fMRI) and functional optical imaging for humans. There are major challenges associated with the skull that need to be addressed before PAT can be adopted to functional human brain imaging. The human skull severely distorts the photoacoustic (PA) signals, giving rise to suboptimal images. The standard approach to mitigate the distortion is to use CT-scans of the skull in concert with an image reconstruction method that considers the heterogeneity of the speed of sound. In addition, conventional ultrasound arrays are rigid and therefore cannot conform to the curvature of the skull. This creates a major challenge for efficient tissue-transducer coupling. Here, we propose to develop an ultrasound image- based approach for skull phase correction, which would eliminate the need of CT scans as well as image co- registration. To address the tissue-transducer coupling issue, we propose to use a stretchable matrix array that can seamlessly conform to the skull’s non-developable surface. Optical fibers will be integrated with the array to provide contact light delivery. The specific tasks to be completed during this grant period are: First, develop, fabricate, and characterize a 256-element stretchable sparse matrix array, second, numerically verify our phase correction and imaging algorithms, third, assess the array and algorithms experimentally using head-mimicking phantoms. At the end of this project we would have confirmed the performance of the stretchable matrix array and the accuracy of the phase correction and imaging algorithms. The preliminary results obtained from this proof-of- concept project will provide the basis upon which we can expand the size of the array and the number of elements to 1024. Such an array will offer a wide field of view for probing human brain functions and will be evaluated on human subjects.
摘要 许多科学工作致力于了解大脑功能及其动力学的相关性 在发育、衰老和患病的情况下。大脑功能的改变可能会导致 多因素的过程,并反映了各种生物标志物。能够在多个时间点量化这些变化, 量表将提高我们对大脑解剖和功能结构的理解,以及它们之间的关系。 这些网络在正常和疾病条件下。凭借丰富的光学吸收对比度, 空间和时间分辨率,以及相对深的穿透,光声层析成像(PAT)是一种很有前途的 可以解决功能性磁共振成像(fMRI)和功能性磁共振成像(MRI)的局限性的成像模式, 人类的光学成像。 在采用PAT之前,需要解决与颅骨相关的主要挑战, 功能性人脑成像人类头骨严重扭曲光声(PA)信号,从而引起 次优图像。标准的方法来减轻失真是使用CT扫描的头骨在音乐会上 利用考虑声速的不均匀性的图像重建方法。此外,本发明还提供了一种方法, 传统的超声阵列是刚性的,因此不能符合颅骨的曲率。这将创建 有效的组织-换能器耦合的主要挑战。在这里,我们建议开发一个超声波图像- 基于方法的颅骨相位校正,这将消除CT扫描的需要,以及图像共- 登记为了解决组织-换能器耦合问题,我们建议使用可拉伸矩阵阵列, 可以完美地贴合头骨的不可展表面光纤将与阵列集成, 提供接触光传输。在这个资助期内要完成的具体任务是:一是发展, 制作并表征了一个256单元的可拉伸稀疏矩阵阵列,其次,数值验证了我们的相位 校正和成像算法,第三,使用头部模拟实验评估阵列和算法 幻影 在这个项目的最后,我们已经确认了可伸缩矩阵阵列的性能, 相位校正和成像算法的精度。从这个证明中获得的初步结果- 一个概念项目将提供一个基础,在此基础上,我们可以扩大数组的大小和元素的数量 到1024。这样的阵列将为探测人脑功能提供广阔的视野,并将在 人类实验对象

项目成果

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Yun Jing其他文献

Yun Jing的其他文献

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{{ truncateString('Yun Jing', 18)}}的其他基金

3D Functional Photoacoustic Imaging of Human Brain with a Stretchable Ultrasound Matrix Array
使用可拉伸超声矩阵阵列对人脑进行 3D 功能光声成像
  • 批准号:
    10612652
  • 财政年份:
    2021
  • 资助金额:
    $ 86.74万
  • 项目类别:
Toward an accuracy-efficiency balanced model for modeling high intensity focused ultrasound
建立用于模拟高强度聚焦超声的精度-效率平衡模型
  • 批准号:
    10115992
  • 财政年份:
    2018
  • 资助金额:
    $ 86.74万
  • 项目类别:

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