IMPROVEMENT OF DEPTH SENSITIVITY TO CEREBRAL HEMODYNAMICS W/ TIME GATED SYSTEM

利用时间门控系统提高脑血流动力学的深度敏感性

• 批准号: 7602561
• 负责人: David A Boas
• 金额: $ 11.77万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7602561
• 关键词: Brain imaging; Cerebrum; Computer Retrieval of Information on Scientific Projects Database; Data; Depth; Detection; Devices; Discrimination; Fiber; Frequencies; Funding; Grant; Head; Human; Image; Institution; Lasers; Lateral; Length; Manuscripts; Numbers; Penetration; Photons; Physiologic pulse; Pulse taking; Research; Research Personnel; Resolution; Resources; Sapphire; Source; System; Three-Dimensional Image; Three-Dimensional Imaging; Time; United States National Institutes of Health; absorption; base; charge coupled device camera; detector; hemodynamics; human data; improved; interest; new technology; reconstruction; response; size

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. By recording the distribution of times of flight of photons, Time Domain (TD) systems intrinsically provide more information that continuous wave (CW) ones. In particular, they enable depth discrimination at a single source-detector (SD) separation. This is of particular interest for functional brain imaging, where cortical activation is often hidden by superficial systemic response. Our TD device is based on a Ti:Sapphire pulsed laser and an intensified CCD camera (ICCD). We have developed a probe combining depth sensitivity and 2D imaging. It consists in 2 halves  one per hemisphere  each with 4¿4 sources and 3¿3 detectors in a square geometry (SD = 2.5 cm). Each detector consists of 7 fibers of different lengths, for parallel detection at 7 delays. All 126 fibers are imaged in parallel on the ICCD array. The 32 sources are illuminated sequentially, with 4 sets of 8 sources that are turned on during the same CCD frame without causing significant cross-talk. This source time-multiplexing and the parallel detection allow for an imaging frequency of almost 2 Hz for the whole head. After successful demonstration of the systems improved depth penetration in phantoms and humans, we are now developing a linear 3D image reconstruction, using the information at all delay gates and all SD pairs simultaneously to better realize the full potential of this new technology. The forward sensitivity matrix A (size number of voxels ¿ [number of SD pairs ¿ number of delay gates]) relates the changes in the absorption coefficient ¿¿a to the changes in normalized intensity ¿I/I0 in the normalized Born approximation: ¿I/I0 = A . ¿¿a. The reconstructed image is obtained by inversion of the sensitivity matrix, using the covariance matrix in the regularization. This reconstruction enables both depth resolution and better lateral uniformity than CW data. A manuscript on these reconstruction results is being prepared. We will be applying the reconstructions to more human data over the next years.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。列出的机构为 研究中心，而研究中心不一定是研究者所在的机构。 通过记录光子的飞行时间分布，时域（TD）系统本质上提供了比连续波（CW）系统更多的信息。特别是，他们能够在一个单一的源检测器（SD）分离的深度歧视。这对于功能性脑成像是特别感兴趣的，其中皮层激活通常被表面系统反应所隐藏。 我们的TD设备是基于钛：蓝宝石脉冲激光器和增强型CCD相机（ICCD）。我们开发了一种结合深度灵敏度和2D成像的探头。它由两半组成  每个半球一个  每个具有正方形几何形状的4 <$4个源和3 <$3个探测器（SD = 2.5 cm）。每个探测器由7个不同长度的光纤组成，用于以7个延迟并行检测。所有126根光纤在ICCD阵列上并行成像。这32个光源被依次照亮，其中4组8个光源在同一CCD帧期间被打开，而不会引起显著的串扰。这种源时间复用和并行检测允许整个头部的成像频率几乎为2 Hz。 在成功演示了该系统改善了幻影和人类的深度穿透后，我们现在正在开发线性3D图像重建，同时使用所有延迟门和所有SD对的信息，以更好地实现这项新技术的全部潜力。前向灵敏度矩阵A（体素的大小数量<$[SD对的数量<$$>延迟门的数量]）将吸收系数<$$> a的变化与归一化玻恩近似中归一化强度<$I/I 0的变化联系起来：<$I/I 0 = A。好吧。重建图像通过灵敏度矩阵的求逆获得，在正则化中使用协方差矩阵。这种重建能够实现深度分辨率和比CW数据更好的横向均匀性。目前正在编写关于这些重建结果的手稿。我们将在未来几年内将重建应用于更多的人类数据。