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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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Cross-correlation on raster-scanned xy-images.(a)–(e) Confocal xy-images acquired by detecting the signal of 1-μm fluorescent beads undergoing laminar flow in a square borosilicate capillary (inner section, 720 μm); λexc = 514 nm, detection bandwidth = 530–600 nm, fline = 1000 Hz, δx = 0.04 μm; scale bar, 3 μm. The angle γ between the flow velocity vector v and the scan path (pointing as the positive x-axis) was varied in the four quadrants of the Cartesian xy-plane. In (a), (b) and (c) v (in green) points in the positive x-direction: the diagonal lines due to the beads motion keep the same orientation irrespectively of the angle γ, which affects their length and slope. In (d) and (e) v points in the negative x-direction (i.e., opposite to the scan path) and the orientation of the diagonal lines is reversed. In each image γ is reported according to the definition of panel (h). (f) A raster-scanned image (or a region of interest) is a matrix of NxxNy pixels, representing a series of intensity measurements from many adjacent confocal excitation volumes (sampled along the red pattern). The sketch highlights (dark green) two arbitrary pixels involved in the computation of the forth cross-correlation between two columns (light green) l = J-I pixels apart. (g) Exemplary CCF computed on panel (a) for (J–I)δx = 7.4 μm. (h) Definition of the angle γ between the vector v and the scan axis (positive x-axis); the range of its possible values and four arbitrarily-directed vectors for the flow velocity are shown.
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f1: Cross-correlation on raster-scanned xy-images.(a)–(e) Confocal xy-images acquired by detecting the signal of 1-μm fluorescent beads undergoing laminar flow in a square borosilicate capillary (inner section, 720 μm); λexc = 514 nm, detection bandwidth = 530–600 nm, fline = 1000 Hz, δx = 0.04 μm; scale bar, 3 μm. The angle γ between the flow velocity vector v and the scan path (pointing as the positive x-axis) was varied in the four quadrants of the Cartesian xy-plane. In (a), (b) and (c) v (in green) points in the positive x-direction: the diagonal lines due to the beads motion keep the same orientation irrespectively of the angle γ, which affects their length and slope. In (d) and (e) v points in the negative x-direction (i.e., opposite to the scan path) and the orientation of the diagonal lines is reversed. In each image γ is reported according to the definition of panel (h). (f) A raster-scanned image (or a region of interest) is a matrix of NxxNy pixels, representing a series of intensity measurements from many adjacent confocal excitation volumes (sampled along the red pattern). The sketch highlights (dark green) two arbitrary pixels involved in the computation of the forth cross-correlation between two columns (light green) l = J-I pixels apart. (g) Exemplary CCF computed on panel (a) for (J–I)δx = 7.4 μm. (h) Definition of the angle γ between the vector v and the scan axis (positive x-axis); the range of its possible values and four arbitrarily-directed vectors for the flow velocity are shown.

Mentions: FLICS relies on single xy-images acquired in confocal or two-photon excitation microscopy by raster scanning a sample where the fluorescence signal comes from flowing brightly fluorescent objects (genetically modified red blood cells, injected fluorescent beads, quantum dots, etc), which produce in the xy-image diagonal lines superimposed to morphological details. The orientation of these diagonal lines with respect to the reference Cartesian xy-plane depends on the flow direction relative to the positively x-oriented scan path (Fig. 1a–e). The slope and width of the diagonal lines are determined by the image acquisition parameters and by the fluorescent particles properties: size, diffusion coefficient and, most importantly, flow speed /v/. A key role is played by the scan frequency: horizontal lines are obtained for scan speeds lower than the drift speed, whereas the slope increases when the scan speed is higher than the modulus /v/. In this case, quantitative information regarding the flow speed can be achieved by computing the Cross-Correlation Function (CCF) of the fluorescence fluctuations detected in pairs of columns of a selected Region Of Interest (ROI) of the xy-image where diagonal lines appear. The CCF is defined as the normalized time average of the product of the fluorescence intensity fluctuations detected in the pixels sampled at time t in the first column and at a delayed time t + τ in the second column. The CCF allows therefore the exploitation of the spatio-temporal information intrinsically enclosed in a single raster-scanned image for the measurement of the blood flow speed. In this regard, FLICS shares the approach of previous image correlation-based methods222324 conceived for the investigation of slow diffusive or directional motions of fluorescently labeled macromolecules within the plasma membrane of living cells2526.


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)

Cross-correlation on raster-scanned xy-images.(a)–(e) Confocal xy-images acquired by detecting the signal of 1-μm fluorescent beads undergoing laminar flow in a square borosilicate capillary (inner section, 720 μm); λexc = 514 nm, detection bandwidth = 530–600 nm, fline = 1000 Hz, δx = 0.04 μm; scale bar, 3 μm. The angle γ between the flow velocity vector v and the scan path (pointing as the positive x-axis) was varied in the four quadrants of the Cartesian xy-plane. In (a), (b) and (c) v (in green) points in the positive x-direction: the diagonal lines due to the beads motion keep the same orientation irrespectively of the angle γ, which affects their length and slope. In (d) and (e) v points in the negative x-direction (i.e., opposite to the scan path) and the orientation of the diagonal lines is reversed. In each image γ is reported according to the definition of panel (h). (f) A raster-scanned image (or a region of interest) is a matrix of NxxNy pixels, representing a series of intensity measurements from many adjacent confocal excitation volumes (sampled along the red pattern). The sketch highlights (dark green) two arbitrary pixels involved in the computation of the forth cross-correlation between two columns (light green) l = J-I pixels apart. (g) Exemplary CCF computed on panel (a) for (J–I)δx = 7.4 μm. (h) Definition of the angle γ between the vector v and the scan axis (positive x-axis); the range of its possible values and four arbitrarily-directed vectors for the flow velocity are shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f1: Cross-correlation on raster-scanned xy-images.(a)–(e) Confocal xy-images acquired by detecting the signal of 1-μm fluorescent beads undergoing laminar flow in a square borosilicate capillary (inner section, 720 μm); λexc = 514 nm, detection bandwidth = 530–600 nm, fline = 1000 Hz, δx = 0.04 μm; scale bar, 3 μm. The angle γ between the flow velocity vector v and the scan path (pointing as the positive x-axis) was varied in the four quadrants of the Cartesian xy-plane. In (a), (b) and (c) v (in green) points in the positive x-direction: the diagonal lines due to the beads motion keep the same orientation irrespectively of the angle γ, which affects their length and slope. In (d) and (e) v points in the negative x-direction (i.e., opposite to the scan path) and the orientation of the diagonal lines is reversed. In each image γ is reported according to the definition of panel (h). (f) A raster-scanned image (or a region of interest) is a matrix of NxxNy pixels, representing a series of intensity measurements from many adjacent confocal excitation volumes (sampled along the red pattern). The sketch highlights (dark green) two arbitrary pixels involved in the computation of the forth cross-correlation between two columns (light green) l = J-I pixels apart. (g) Exemplary CCF computed on panel (a) for (J–I)δx = 7.4 μm. (h) Definition of the angle γ between the vector v and the scan axis (positive x-axis); the range of its possible values and four arbitrarily-directed vectors for the flow velocity are shown.
Mentions: FLICS relies on single xy-images acquired in confocal or two-photon excitation microscopy by raster scanning a sample where the fluorescence signal comes from flowing brightly fluorescent objects (genetically modified red blood cells, injected fluorescent beads, quantum dots, etc), which produce in the xy-image diagonal lines superimposed to morphological details. The orientation of these diagonal lines with respect to the reference Cartesian xy-plane depends on the flow direction relative to the positively x-oriented scan path (Fig. 1a–e). The slope and width of the diagonal lines are determined by the image acquisition parameters and by the fluorescent particles properties: size, diffusion coefficient and, most importantly, flow speed /v/. A key role is played by the scan frequency: horizontal lines are obtained for scan speeds lower than the drift speed, whereas the slope increases when the scan speed is higher than the modulus /v/. In this case, quantitative information regarding the flow speed can be achieved by computing the Cross-Correlation Function (CCF) of the fluorescence fluctuations detected in pairs of columns of a selected Region Of Interest (ROI) of the xy-image where diagonal lines appear. The CCF is defined as the normalized time average of the product of the fluorescence intensity fluctuations detected in the pixels sampled at time t in the first column and at a delayed time t + τ in the second column. The CCF allows therefore the exploitation of the spatio-temporal information intrinsically enclosed in a single raster-scanned image for the measurement of the blood flow speed. In this regard, FLICS shares the approach of previous image correlation-based methods222324 conceived for the investigation of slow diffusive or directional motions of fluorescently labeled macromolecules within the plasma membrane of living cells2526.

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