McDowell Konnor P, Berthiaume Andrée-Anne, Tieu Taryn, Hartmann David A, Shih Andy Y
Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA, USA.
Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.
Quant Imaging Med Surg. 2021 Mar;11(3):969-982. doi: 10.21037/qims-20-920.
Multi-photon imaging of the cerebrovasculature provides rich data on the dynamics of cortical arterioles, capillaries, and venules. Vascular diameter is the major determinant of blood flow resistance, and is the most commonly quantified metric in studies of the cerebrovasculature. However, there is a lack of accessible and easy-to-use methods to quantify vascular diameter in imaging data.
We created VasoMetrics, a macro written in ImageJ/Fiji for spatiotemporal analysis of microvascular diameter. The key feature of VasoMetrics is rapid analysis of many evenly spaced cross-sectional lines along the vessel of interest, permitting the extraction of numerous diameter measurements from individual vessels. Here we demonstrated the utility of VasoMetrics by analyzing multi-photon imaging stacks and movies collected from lightly sedated mice, as well as data from optical coherence tomography angiography (OCTA) of human retina.
Compared to the standard approach, which is to measure cross-sectional diameters at arbitrary points along a vessel, VasoMetrics accurately reported spatiotemporal features of vessel diameter, reduced measurement bias and time spent analyzing data, and improved the reproducibility of diameter measurements between users. VasoMetrics revealed the dynamics in pial arteriole diameters during vasomotion at rest, as well as changes in capillary diameter before and after pericyte ablation. Retinal arteriole diameter was quantified from a human retinal angiogram, providing proof-of-principle that VasoMetrics can be applied to contrast-enhanced clinical imaging of microvasculature.
VasoMetrics is a robust macro for spatiotemporal analysis of microvascular diameter in imaging applications.
脑血管系统的多光子成像提供了关于皮质小动脉、毛细血管和小静脉动力学的丰富数据。血管直径是血流阻力的主要决定因素，也是脑血管系统研究中最常用的量化指标。然而，在成像数据中缺乏可获取且易于使用的方法来量化血管直径。
我们创建了VasoMetrics，这是一个用ImageJ/Fiji编写的用于微血管直径时空分析的宏。VasoMetrics的关键特性是能够快速分析沿感兴趣血管的许多均匀间隔的横截面线，从而允许从单个血管中提取大量直径测量值。在此，我们通过分析从轻度镇静小鼠收集的多光子成像堆栈和电影，以及来自人类视网膜光学相干断层扫描血管造影（OCTA）的数据，展示了VasoMetrics的实用性。
与在血管上任意点测量横截面直径的标准方法相比，VasoMetrics能够准确报告血管直径的时空特征，减少测量偏差和数据分析时间，并提高了用户之间直径测量的可重复性。VasoMetrics揭示了静息时血管运动期间软脑膜小动脉直径的动态变化，以及周细胞消融前后毛细血管直径的变化。从人类视网膜血管造影中量化了视网膜小动脉直径，证明了VasoMetrics可应用于微血管造影增强的临床成像。
VasoMetrics是一种强大的宏，用于成像应用中微血管直径的时空分析。
