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. 2012 Oct;19(7):619-31.
doi: 10.1111/j.1549-8719.2012.00197.x.

Laser Speckle Flowmetry Method for Measuring Spatial and Temporal Hemodynamic Alterations Throughout Large Microvascular Networks

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Free PMC article

Laser Speckle Flowmetry Method for Measuring Spatial and Temporal Hemodynamic Alterations Throughout Large Microvascular Networks

Joshua K Meisner et al. Microcirculation. .
Free PMC article

Abstract

Objectives: 1) To develop and validate laser speckle flowmetry (LSF) as a quantitative tool for individual microvessel hemodynamics in large networks. 2) To use LSF to determine if structural differences in the dorsal skinfold microcirculation (DSFWC) of C57BL/6 and BALB/c mice impart differential network hemodynamic responses to occlusion.

Methods: We compared LSF velocity measurements with known/measured velocities in vitro using capillary tube tissue phantoms and in vivo using mouse DSFWCs and cremaster muscles. Hemodynamic changes induced by feed arteriole occlusion were measured using LSF in DSFWCs implanted on C57BL/6 and BALB/c mice.

Results: In vitro, we found that the normalized speckle intensity (NSI) versus velocity linear relationship (R(2) ≥ 0.97) did not vary with diameter or hematocrit and can be shifted to meet an expected operating range. In vivo, DSFWC and cremaster muscle preparations (R(2) = 0.92 and 0.95, respectively) demonstrated similar linear relationships between NSI and centerline velocity. Stratification of arterioles into predicted collateral pathways revealed significant differences between C57BL/6 and BALB/c strains in response to feed arteriole occlusion.

Conclusions: These data demonstrate the applicability of LSF to intravital microscopy microcirculation preparations for determining both relative and absolute hemodynamics on a network-wide scale while maintaining the resolution of individual microvessels.

Figures

Figure 1
Figure 1. Generation of 2 dimensional blood velocity maps in large microvascular networks
A uniform field of laser light is used to illuminate the intravital tissue preparation. This produces a dynamic speckle pattern that is acquired by a CCD (or CMOS) camera. From the raw digital speckle image, a relative velocity measurement for each pixel (Pij), based on the variance of the speckle pattern in the surrounding 7×7 pixel neighborhood (Eq 1), is used to generate a relative velocity map at the given field of view. For more robust measurements, individual processed speckle images are averaged and then merged into the larger microvascular network (scale bar is 500 μm for all images).
Figure 2
Figure 2. In vitro relationship between normalized speckle index (NSI, arbitrary units, a.u.) and absolute average velocity
A) Glass capillary diameter was increased to approximately 2- (282μm) and 3- (447μm) fold of the initial 142μm diameter with no significant variation in the NSI-velocity relationship (3ms exposure). B) Increasing hematocrit from 36% PCV to 54% PCV demonstrated no significant variation in the NSI-velocity relationship (3ms exposure). C) The linear dynamic range (in log-log scale) of the in vitro NSI-velocity relationship can be shifted by adjusting exposure rate from 3ms exposure (open circles) to 20ms exposure (closed circles). Linear relationship (log-transformed) is displayed with dotted lines (20ms, circles, excludes last 4 non-linear values; 3ms, cross-hatches, excludes first 4 non-linear values).
Figure 3
Figure 3. In vivo validation of NSI versus absolute velocity relationship
A) Circulating fluorescent microspheres were used to calculate centerline velocity (pulsed excitation source, 10ms intervals) at each field of view. Inset depicts microsphere traveling in centerline. B) LSF velocity maps were generated for the same field of view immediately after microsphere imaging (scale bar is 100 μm, 3ms exposure). This method was applied in mouse cremaster muscle and dorsal skinfold window chamber. C,E) In vivo relationships between NSI and centerline velocity in the mouse cremaster (C, binned by 0.1mm/s divisions, n=4 muscles) and dorsal skinfold (E, binned by 0.1mm/s divisions, n=5 windows) microcirculation. D,F) Individual fields of view were then merged to form velocity distribution maps of entire microvascular networks ( 3ms exposure, scale bar is 500 μm).
Figure 4
Figure 4. Dorsal skinfold window chamber network structure for C57BL/6 and BALB/c mouse strains
A, B) Demarcated brightfield images of dorsal skinfold window chamber microvascular networks demonstrate differences in network structure between C57BL/6 and BALB/c strains (arterioles in red, venules in blue, scale bar is 500 μm). C) Histogram of pre-ligation arteriole diameters shows skewing of BALB/c segments toward smaller diameters and a significant increase in segments >57 μm in diameter in C57BL/6 networks (* indicates significantly different than other strain within same diameter bin at p<0.05, n=5 windows per strain). D) Microvascular arcade loop analysis demonstrates significantly more arteriole loops in C57BL/6 mice, but fewer venular loops compared to BALB/c networks (* indicates significantly different than other strain at p< 0.05, n=5 windows per strain).
Figure 5
Figure 5. Network hemodynamic alterations after arteriole occlusion in C57BL/6 and BALB/c dorsal skinfold window chambers
A) Representative window chamber network with the chosen site for micro-occlusion (marked by ‘X’) and the predicted collateral pathways (circled in white) (scale bar is 500 μm). B) Bar graph analysis of collateral and background arteriole pathways shows significant increase in collateral velocity and shear stress from pre- to 24 hrs post-microvessel occlusion for the C57BL/6 networks (*, p<0.05 between collateral and background changes within strain, n=5 windows per strain). C, D) Histograms representing global analysis of hemodynamic changes (NSI, proportional to velocity, and SSR, proportional to wall shear stress) without stratification. No significant differences were observed between strains (binned by percent change, n=5 windows per strain).
Figure 6
Figure 6. Illustration of how hemodynamic changes and microvascular structure may be mapped in individual microvessels over time using LSF
A–C) Brightfield images of network structure over 6 days after arteriole occlusion in an example window chamber network (green arrows denote collateral pathway exposed to increased velocity, yellow arrow denotes segment exposed to decreased velocity, white arrow indicates site of arteriole occlusion, C57BL/6 strain). Note the increased tortuosity, indicative of outward remodeling, along the high flow pathway. D, E) LSF velocity maps from pre- to 24hrs post-arteriole occlusion. F, G, H) Overlays of changes in velocity, shear stress, and diameter, respectively, on the pre-ligation network demonstrate how changes in hemodynamics using LSF can be mapped back to changes in network structure in a preparation that allows for chronic measurements.

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