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In vivo flow mapping in complex vessel networks by single image correlation.

Sironi L, Bouzin M, Inverso D, D'Alfonso L, Pozzi P, Cotelli F, Guidotti LG, Iannacone M, Collini M, Chirico G - Sci Rep (2014)

Bottom Line: Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details.The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity.The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

View Article: PubMed Central - PubMed

Affiliation: Università degli Studi di Milano-Bicocca, Physics Department, Piazza della Scienza 3, I-20126, Milan, Italy.

ABSTRACT
We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

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Measurement in time of the blood flow speed in the hepatic microcirculation.(a) xy-image acquired by detecting the photoluminescence (shown in white) of 5-nm QDs (λexc = 900 nm, detection bandwidth = 640–690 nm); fline = 850 Hz, δx = 0.051 μm, scale bar, 10 μm. CCFs have been derived on the evidenced ROIs (ROI 1: 240 × 210 pixels; ROI 2: 450 × 120 pixels; ROI 3: 145 × 250 pixels) for (J-I)δx = 0.5–2 μm and fitted (equation (3)), leading to /v/ = 235 ± 4 μm/s, 235 ± 3 μm/s and 229 ± 8 μm/s for ROIs 1, 2 and 3, respectively. A color coding is assigned for the speed /v/, while the arrows indicate the flow direction. γ, fixed to 50°, −4° and 80° in ROIs 1, 2 and 3, is sketched in the reference xy-plane. (b), (c) The xy-image in (a) is one out of ten frames of an xyt-stack (Δt = ti + 1–ti = 0.88 s is the interval between the sampling of the same pixel in two consecutive frames i and i + 1). The first five frames, each identified by its sampling time ti = iΔt, are shown for ROIs 1 (b) and 2 (c). The same color code of panel (a) is adopted for the centreline. Scale bar, 5 μm; same calibration bar (in arbitrary units) in (b) and (c). (d), (e) Estimates for /v/ (triangles) and /v/0 (squares) versus time in ROIs 1 (d) and 2 (e). The average ratio /v///v/0 is 0.92 and 0.95 in ROIs 1 and 2, respectively.
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f3: Measurement in time of the blood flow speed in the hepatic microcirculation.(a) xy-image acquired by detecting the photoluminescence (shown in white) of 5-nm QDs (λexc = 900 nm, detection bandwidth = 640–690 nm); fline = 850 Hz, δx = 0.051 μm, scale bar, 10 μm. CCFs have been derived on the evidenced ROIs (ROI 1: 240 × 210 pixels; ROI 2: 450 × 120 pixels; ROI 3: 145 × 250 pixels) for (J-I)δx = 0.5–2 μm and fitted (equation (3)), leading to /v/ = 235 ± 4 μm/s, 235 ± 3 μm/s and 229 ± 8 μm/s for ROIs 1, 2 and 3, respectively. A color coding is assigned for the speed /v/, while the arrows indicate the flow direction. γ, fixed to 50°, −4° and 80° in ROIs 1, 2 and 3, is sketched in the reference xy-plane. (b), (c) The xy-image in (a) is one out of ten frames of an xyt-stack (Δt = ti + 1–ti = 0.88 s is the interval between the sampling of the same pixel in two consecutive frames i and i + 1). The first five frames, each identified by its sampling time ti = iΔt, are shown for ROIs 1 (b) and 2 (c). The same color code of panel (a) is adopted for the centreline. Scale bar, 5 μm; same calibration bar (in arbitrary units) in (b) and (c). (d), (e) Estimates for /v/ (triangles) and /v/0 (squares) versus time in ROIs 1 (d) and 2 (e). The average ratio /v///v/0 is 0.92 and 0.95 in ROIs 1 and 2, respectively.

Mentions: Experimentally, the approximate /v/0 has also been compared with the value /v/ obtained from the CCFs fit (taken as un unbiased estimate of the flow speed) for all the data presented in this work (Figures 2,3,4): the average ratio /v///v/0 ranges from 0.87 to 0.96, suggesting that the blood flow speed can be obtained directly from the peak time of the experimental CCFs in most of the examined cases, thereby simplifying the analysis.


In vivo flow mapping in complex vessel networks by single image correlation.

Sironi L, Bouzin M, Inverso D, D'Alfonso L, Pozzi P, Cotelli F, Guidotti LG, Iannacone M, Collini M, Chirico G - Sci Rep (2014)

Measurement in time of the blood flow speed in the hepatic microcirculation.(a) xy-image acquired by detecting the photoluminescence (shown in white) of 5-nm QDs (λexc = 900 nm, detection bandwidth = 640–690 nm); fline = 850 Hz, δx = 0.051 μm, scale bar, 10 μm. CCFs have been derived on the evidenced ROIs (ROI 1: 240 × 210 pixels; ROI 2: 450 × 120 pixels; ROI 3: 145 × 250 pixels) for (J-I)δx = 0.5–2 μm and fitted (equation (3)), leading to /v/ = 235 ± 4 μm/s, 235 ± 3 μm/s and 229 ± 8 μm/s for ROIs 1, 2 and 3, respectively. A color coding is assigned for the speed /v/, while the arrows indicate the flow direction. γ, fixed to 50°, −4° and 80° in ROIs 1, 2 and 3, is sketched in the reference xy-plane. (b), (c) The xy-image in (a) is one out of ten frames of an xyt-stack (Δt = ti + 1–ti = 0.88 s is the interval between the sampling of the same pixel in two consecutive frames i and i + 1). The first five frames, each identified by its sampling time ti = iΔt, are shown for ROIs 1 (b) and 2 (c). The same color code of panel (a) is adopted for the centreline. Scale bar, 5 μm; same calibration bar (in arbitrary units) in (b) and (c). (d), (e) Estimates for /v/ (triangles) and /v/0 (squares) versus time in ROIs 1 (d) and 2 (e). The average ratio /v///v/0 is 0.92 and 0.95 in ROIs 1 and 2, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256590&req=5

f3: Measurement in time of the blood flow speed in the hepatic microcirculation.(a) xy-image acquired by detecting the photoluminescence (shown in white) of 5-nm QDs (λexc = 900 nm, detection bandwidth = 640–690 nm); fline = 850 Hz, δx = 0.051 μm, scale bar, 10 μm. CCFs have been derived on the evidenced ROIs (ROI 1: 240 × 210 pixels; ROI 2: 450 × 120 pixels; ROI 3: 145 × 250 pixels) for (J-I)δx = 0.5–2 μm and fitted (equation (3)), leading to /v/ = 235 ± 4 μm/s, 235 ± 3 μm/s and 229 ± 8 μm/s for ROIs 1, 2 and 3, respectively. A color coding is assigned for the speed /v/, while the arrows indicate the flow direction. γ, fixed to 50°, −4° and 80° in ROIs 1, 2 and 3, is sketched in the reference xy-plane. (b), (c) The xy-image in (a) is one out of ten frames of an xyt-stack (Δt = ti + 1–ti = 0.88 s is the interval between the sampling of the same pixel in two consecutive frames i and i + 1). The first five frames, each identified by its sampling time ti = iΔt, are shown for ROIs 1 (b) and 2 (c). The same color code of panel (a) is adopted for the centreline. Scale bar, 5 μm; same calibration bar (in arbitrary units) in (b) and (c). (d), (e) Estimates for /v/ (triangles) and /v/0 (squares) versus time in ROIs 1 (d) and 2 (e). The average ratio /v///v/0 is 0.92 and 0.95 in ROIs 1 and 2, respectively.
Mentions: Experimentally, the approximate /v/0 has also been compared with the value /v/ obtained from the CCFs fit (taken as un unbiased estimate of the flow speed) for all the data presented in this work (Figures 2,3,4): the average ratio /v///v/0 ranges from 0.87 to 0.96, suggesting that the blood flow speed can be obtained directly from the peak time of the experimental CCFs in most of the examined cases, thereby simplifying the analysis.

Bottom Line: Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details.The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity.The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

View Article: PubMed Central - PubMed

Affiliation: Università degli Studi di Milano-Bicocca, Physics Department, Piazza della Scienza 3, I-20126, Milan, Italy.

ABSTRACT
We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

Show MeSH
Related in: MedlinePlus