A processing work-flow for measuring erythrocytes velocity in extended vascular networks from wide field high-resolution optical imaging data
A processing work-flow for measuring erythrocytes velocity in extended vascular networks from wide field high-resolution optical imaging data
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DOI：
10.1016/j.neuroimage.2011.08.081
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发表时间：
2012-02-01
期刊：
影响因子：
5.7
通讯作者：
Vanzetta, Ivo
中科院分区：
文献类型：
--
作者：
Deneux, Thomas;Takerkart, Sylvain;Vanzetta, Ivo
需要关于血管反应的时空动力学的全面信息，以支持基于血流动力学的功能成像所使用的信号。最近的研究表明，可以从大脑皮层固有吸收变化的宽视场光学成像记录中提取红细胞的速度及其变化。在这里，我们描述了一个完整的处理流程，用于可靠地估计大脑皮层网络中的RBC速度。实现了几个预处理步骤：图像配准，用于校正血管系统的微小运动；半自动图像分割，用于快速和可重现的血管选择；重建每个微血管的RBC轨迹模式；以及时空滤波，以增强所需的数据特征。主要的分析步骤由两种估计RBC速度场的稳健算法组成。还估计了血管直径及其变化，以及背向散射光强度的局部变化。这一完整的处理链是通过免费分发的软件套件实现的。该软件使用高效的数据管理来处理通过活体光学成像获得的非常大的数据集。它提供了一个完整和用户友好的图形用户界面，以及用于显示和探索数据和结果的可视化工具。还提供了完整的数据模拟框架，以针对数据的几个特征来优化算法的性能。我们举例说明了我们的方法在三种不同的活体数据情况下的性能。我们首先记录了麻醉大鼠躯体感觉皮质中由扩散性抑制引起的大规模红细胞速度反应。其次，我们展示了视觉刺激在麻醉猫视皮层中所引起的速度反应。最后，我们首次报道了清醒猴纹外皮质扩展血管网络中视觉诱发的RBC速度反应。(C)2011 Elsevier Inc.保留所有权利。
Comprehensive information on the spatio-temporal dynamics of the vascular response is needed to underpin the signals used in hemodynamics-based functional imaging. It has recently been shown that red blood cells (RBCs) velocity and its changes can be extracted from wide-field optical imaging recordings of intrinsic absorption changes in cortex. Here, we describe a complete processing work-flow for reliable RBC velocity estimation in cortical networks. Several pre-processing steps are implemented: image co-registration, necessary to correct for small movements of the vasculature, semi-automatic image segmentation for fast and reproducible vessel selection, reconstruction of RBC trajectories patterns for each micro-vessel, and spatio-temporal filtering to enhance the desired data characteristics. The main analysis step is composed of two robust algorithms for estimating the RBCs' velocity field. Vessel diameter and its changes are also estimated, as well as local changes in backscattered light intensity. This full processing chain is implemented with a software suite that is freely distributed. The software uses efficient data management for handling the very large data sets obtained with in vivo optical imaging. It offers a complete and user-friendly graphical user interface with visualization tools for displaying and exploring data and results. A full data simulation framework is also provided in order to optimize the performances of the algorithm with respect to several characteristics of the data. We illustrate the performance of our method in three different cases of in vivo data. We first document the massive RBC speed response evoked by a spreading depression in anesthetized rat somato-sensory cortex. Second, we show the velocity response elicited by a visual stimulation in anesthetized cat visual cortex. Finally, we report, for the first time, visually-evoked RBC speed responses in an extended vascular network in awake monkey extrastriate cortex. (C) 2011 Elsevier Inc. All rights reserved.