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Line-scanning particle image velocimetry: an optical approach for quantifying a wide range of blood flow speeds in live animals.

Kim TN, Goodwill PW, Chen Y, Conolly SM, Schaffer CB, Liepmann D, Wang RA - PLoS ONE (2012)

Bottom Line: LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface.To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM.Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Accelerated Vascular Research, Division of Vascular Surgery, Department of Surgery, University of California San Francisco, San Francisco, California, United States of America.

ABSTRACT

Background: The ability to measure blood velocities is critical for studying vascular development, physiology, and pathology. A key challenge is to quantify a wide range of blood velocities in vessels deep within living specimens with concurrent diffraction-limited resolution imaging of vascular cells. Two-photon laser scanning microscopy (TPLSM) has shown tremendous promise in analyzing blood velocities hundreds of micrometers deep in animals with cellular resolution. However, current analysis of TPLSM-based data is limited to the lower range of blood velocities and is not adequate to study faster velocities in many normal or disease conditions.

Methodology/principal findings: We developed line-scanning particle image velocimetry (LS-PIV), which used TPLSM data to quantify peak blood velocities up to 84 mm/s in live mice harboring brain arteriovenous malformation, a disease characterized by high flow. With this method, we were able to accurately detect the elevated blood velocities and exaggerated pulsatility along the abnormal vascular network in these animals. LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface. In addition to analyzing in vivo data, we validated the accuracy of LS-PIV up to 800 mm/s using simulations with known velocity and noise parameters.

Conclusions/significance: To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM. Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies.

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LS-PIV analysis of in vivo two-photon line-scan data measured in cortical artery. A, TPLSM projection of cortical vasculature in ephrin-B2+/H2B−eGFP mouse with the blood plasma labeled by intravenous injection of Texas Red-dextran. Ephrin-B2+/H2B−eGFP mice express nuclear GFP in arterial endothelial cells, which allows these vessels to be distinguished with cellular resolution. B, TPLSM image through the center of an arteriole from the white box in (A). The double-headed arrow indicates the location where line-scans were recorded and the single-headed arrow represents the direction of flow. C, Line-scan data from the vessel in (B) where each sequential line-scan appears beneath the one before, forming a space-time image with time increasing from top to bottom. Each dark streak corresponds to a single RBC as it moves along the scan path. D, LS-PIV applied between pairs of sequential line-scans from vessel (C). Individual cross-correlation results are oriented along the y-axis with time advancing left to right. Each respective probability distribution is normalized and color-coded according to the inset key. The y-axis is converted from units of distance to units of speed by dividing by the time interval between line-scans. E, The final RBC velocity along the scan line is determined from the peak value at each time point in (D). The dotted line represents time-averaged velocity. The temporal resolution of analysis is shown here at 1.3 kHz (1/2 of maximum) to better illustrate individual points.
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pone-0038590-g002: LS-PIV analysis of in vivo two-photon line-scan data measured in cortical artery. A, TPLSM projection of cortical vasculature in ephrin-B2+/H2B−eGFP mouse with the blood plasma labeled by intravenous injection of Texas Red-dextran. Ephrin-B2+/H2B−eGFP mice express nuclear GFP in arterial endothelial cells, which allows these vessels to be distinguished with cellular resolution. B, TPLSM image through the center of an arteriole from the white box in (A). The double-headed arrow indicates the location where line-scans were recorded and the single-headed arrow represents the direction of flow. C, Line-scan data from the vessel in (B) where each sequential line-scan appears beneath the one before, forming a space-time image with time increasing from top to bottom. Each dark streak corresponds to a single RBC as it moves along the scan path. D, LS-PIV applied between pairs of sequential line-scans from vessel (C). Individual cross-correlation results are oriented along the y-axis with time advancing left to right. Each respective probability distribution is normalized and color-coded according to the inset key. The y-axis is converted from units of distance to units of speed by dividing by the time interval between line-scans. E, The final RBC velocity along the scan line is determined from the peak value at each time point in (D). The dotted line represents time-averaged velocity. The temporal resolution of analysis is shown here at 1.3 kHz (1/2 of maximum) to better illustrate individual points.

Mentions: We initially found that existing methods for analyzing TPLSM-based data could not quantify RBC velocities in large brain AVMs of Notch4* mice. RBCs often moved too quickly to be tracked as individual streaks in the space-time data (Figure S2A–B). However, we reasoned that many of the same cells were re-imaged in sequential line-scans and could still be used to calculate velocity by cross-correlation analysis. We therefore developed LS-PIV and first tested it in cortical arteries with moderate RBC speeds. Figure 2 shows analysis of line-scan data measured from an arterial segment in a collateral loop. These cerebral collateral vessels were ideal for early tests as they generally harbored lower RBC velocities than similarly sized arteries in arborizing networks. Arteries were identified by their morphology, direction of flow, and endothelial expression of histone-tagged GFP under control of the endogenous promoter for arterial marker ephrin-B2[38] (N = 34 vessels in 3 mice, Figure 2A). The blood plasma was labeled with high-molecular-weight Texas Red-dextran and the cortical vasculature was imaged through a cranial window over the right parietal cortex. Image stacks were acquired with 1 µm steps along the optical axis and visualized as average projections (Figure 2A).


Line-scanning particle image velocimetry: an optical approach for quantifying a wide range of blood flow speeds in live animals.

Kim TN, Goodwill PW, Chen Y, Conolly SM, Schaffer CB, Liepmann D, Wang RA - PLoS ONE (2012)

LS-PIV analysis of in vivo two-photon line-scan data measured in cortical artery. A, TPLSM projection of cortical vasculature in ephrin-B2+/H2B−eGFP mouse with the blood plasma labeled by intravenous injection of Texas Red-dextran. Ephrin-B2+/H2B−eGFP mice express nuclear GFP in arterial endothelial cells, which allows these vessels to be distinguished with cellular resolution. B, TPLSM image through the center of an arteriole from the white box in (A). The double-headed arrow indicates the location where line-scans were recorded and the single-headed arrow represents the direction of flow. C, Line-scan data from the vessel in (B) where each sequential line-scan appears beneath the one before, forming a space-time image with time increasing from top to bottom. Each dark streak corresponds to a single RBC as it moves along the scan path. D, LS-PIV applied between pairs of sequential line-scans from vessel (C). Individual cross-correlation results are oriented along the y-axis with time advancing left to right. Each respective probability distribution is normalized and color-coded according to the inset key. The y-axis is converted from units of distance to units of speed by dividing by the time interval between line-scans. E, The final RBC velocity along the scan line is determined from the peak value at each time point in (D). The dotted line represents time-averaged velocity. The temporal resolution of analysis is shown here at 1.3 kHz (1/2 of maximum) to better illustrate individual points.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3383695&req=5

pone-0038590-g002: LS-PIV analysis of in vivo two-photon line-scan data measured in cortical artery. A, TPLSM projection of cortical vasculature in ephrin-B2+/H2B−eGFP mouse with the blood plasma labeled by intravenous injection of Texas Red-dextran. Ephrin-B2+/H2B−eGFP mice express nuclear GFP in arterial endothelial cells, which allows these vessels to be distinguished with cellular resolution. B, TPLSM image through the center of an arteriole from the white box in (A). The double-headed arrow indicates the location where line-scans were recorded and the single-headed arrow represents the direction of flow. C, Line-scan data from the vessel in (B) where each sequential line-scan appears beneath the one before, forming a space-time image with time increasing from top to bottom. Each dark streak corresponds to a single RBC as it moves along the scan path. D, LS-PIV applied between pairs of sequential line-scans from vessel (C). Individual cross-correlation results are oriented along the y-axis with time advancing left to right. Each respective probability distribution is normalized and color-coded according to the inset key. The y-axis is converted from units of distance to units of speed by dividing by the time interval between line-scans. E, The final RBC velocity along the scan line is determined from the peak value at each time point in (D). The dotted line represents time-averaged velocity. The temporal resolution of analysis is shown here at 1.3 kHz (1/2 of maximum) to better illustrate individual points.
Mentions: We initially found that existing methods for analyzing TPLSM-based data could not quantify RBC velocities in large brain AVMs of Notch4* mice. RBCs often moved too quickly to be tracked as individual streaks in the space-time data (Figure S2A–B). However, we reasoned that many of the same cells were re-imaged in sequential line-scans and could still be used to calculate velocity by cross-correlation analysis. We therefore developed LS-PIV and first tested it in cortical arteries with moderate RBC speeds. Figure 2 shows analysis of line-scan data measured from an arterial segment in a collateral loop. These cerebral collateral vessels were ideal for early tests as they generally harbored lower RBC velocities than similarly sized arteries in arborizing networks. Arteries were identified by their morphology, direction of flow, and endothelial expression of histone-tagged GFP under control of the endogenous promoter for arterial marker ephrin-B2[38] (N = 34 vessels in 3 mice, Figure 2A). The blood plasma was labeled with high-molecular-weight Texas Red-dextran and the cortical vasculature was imaged through a cranial window over the right parietal cortex. Image stacks were acquired with 1 µm steps along the optical axis and visualized as average projections (Figure 2A).

Bottom Line: LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface.To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM.Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Accelerated Vascular Research, Division of Vascular Surgery, Department of Surgery, University of California San Francisco, San Francisco, California, United States of America.

ABSTRACT

Background: The ability to measure blood velocities is critical for studying vascular development, physiology, and pathology. A key challenge is to quantify a wide range of blood velocities in vessels deep within living specimens with concurrent diffraction-limited resolution imaging of vascular cells. Two-photon laser scanning microscopy (TPLSM) has shown tremendous promise in analyzing blood velocities hundreds of micrometers deep in animals with cellular resolution. However, current analysis of TPLSM-based data is limited to the lower range of blood velocities and is not adequate to study faster velocities in many normal or disease conditions.

Methodology/principal findings: We developed line-scanning particle image velocimetry (LS-PIV), which used TPLSM data to quantify peak blood velocities up to 84 mm/s in live mice harboring brain arteriovenous malformation, a disease characterized by high flow. With this method, we were able to accurately detect the elevated blood velocities and exaggerated pulsatility along the abnormal vascular network in these animals. LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface. In addition to analyzing in vivo data, we validated the accuracy of LS-PIV up to 800 mm/s using simulations with known velocity and noise parameters.

Conclusions/significance: To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM. Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies.

Show MeSH
Related in: MedlinePlus