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Organ-wide 3D-imaging and topological analysis of the continuous microvascular network in a murine lymph node.

Kelch ID, Bogle G, Sands GB, Phillips AR, LeGrice IJ, Dunbar PR - Sci Rep (2015)

Bottom Line: By focussing on critical immune microenvironments we quantified differences in their vascular topology.We further developed a morphology-based approach to identify High Endothelial Venules, key sites for lymphocyte extravasation.These data represent a comprehensive and continuous blood vessel network of an entire organ and provide benchmark measurements that will inform modelling of blood vessel networks as well as enable comparison of vascular topology in different organs.

View Article: PubMed Central - PubMed

Affiliation: Maurice Wilkins Centre, University of Auckland, Private Bag 92-019, Auckland 1142, New Zealand.

ABSTRACT
Understanding of the microvasculature has previously been limited by the lack of methods capable of capturing and modelling complete vascular networks. We used novel imaging and computational techniques to establish the topology of the entire blood vessel network of a murine lymph node, combining 63,706 confocal images at 2 μm pixel resolution to cover a volume of 3.88 mm(3). Detailed measurements including the distribution of vessel diameters, branch counts, and identification of voids were subsequently re-visualised in 3D revealing regional specialisation within the network. By focussing on critical immune microenvironments we quantified differences in their vascular topology. We further developed a morphology-based approach to identify High Endothelial Venules, key sites for lymphocyte extravasation. These data represent a comprehensive and continuous blood vessel network of an entire organ and provide benchmark measurements that will inform modelling of blood vessel networks as well as enable comparison of vascular topology in different organs.

No MeSH data available.


Related in: MedlinePlus

Network branching.The topology map of full LN vasculature was employed for 3D measurements on the branching pattern from feeding vessels and visualisation of the arterial and venous trees. The branch separation from the main arteriole and vein was calculated and plotted for all branching points within the network (a). Branching from the feeding vessel was further visualised in a rainbow spectrum display in CMGUI for the main arteriole (b) and the exiting vein (c), respectively (a full view is available in Supplementary Movie 3). By selecting only vessels with a diameter above 15 μm, abandoning smaller vessels including the capillary bed (grey), two connected networks can be easily separated, representing the arterial (red) and venous (blue) tree (d–g). Note that the arterial tree appears to have fewer vessels (f), since the diameters of arterioles are generally smaller than veins, and arterioles with a diameter below 15 μm are not included in this view. A 3D view of both vascular trees can be found in Supplementary Movie 4.
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f4: Network branching.The topology map of full LN vasculature was employed for 3D measurements on the branching pattern from feeding vessels and visualisation of the arterial and venous trees. The branch separation from the main arteriole and vein was calculated and plotted for all branching points within the network (a). Branching from the feeding vessel was further visualised in a rainbow spectrum display in CMGUI for the main arteriole (b) and the exiting vein (c), respectively (a full view is available in Supplementary Movie 3). By selecting only vessels with a diameter above 15 μm, abandoning smaller vessels including the capillary bed (grey), two connected networks can be easily separated, representing the arterial (red) and venous (blue) tree (d–g). Note that the arterial tree appears to have fewer vessels (f), since the diameters of arterioles are generally smaller than veins, and arterioles with a diameter below 15 μm are not included in this view. A 3D view of both vascular trees can be found in Supplementary Movie 4.

Mentions: Based on our dataset it was now possible, for each node in the network, to identify the shortest paths to the feeding artery and to the main exit vein. The number of branches along each path was determined, providing branch counts from the main artery and the main vein for every node in the network (Fig. 4). Overall, the arterial and venous trees display very similar branching patterns. The distribution of branch counts from the artery ranges from 1 to 39, and 1 to 43 from the main vein; both branch counts show approximately Gaussian distribution and a peak around 18 branch points, with a mean of 20 (Fig. 4a). The range of branch counts was translated into a rainbow colour spectrum and the data displayed in 3D across the network (Fig. 4b,c; Supplementary Movie 3). The distribution reveals that the majority of vessels lie within 30 branch counts from the feeding artery, apart from a small proportion that lies further away (red in the spectrum display). The inner centre of the LN in close proximity to the hilum exhibits a low degree of branching for both the artery and vein (light blue areas). Remarkably, the rim of the LN displays a very homogeneous number of about 20–25 branches to the feeding artery (yellow areas; Fig. 4b). The distribution to the main vein is less homogeneous at the surface of the LN but contains a concentration of vessels in the centre that show a high branch count to the vein (Fig. 4c). In an alternative approach to visualising arterial and venous branches, we limited the displayed network to vessels with a diameter larger than 15 μm thus excluding the capillary bed and allowing us to isolate two large vascular segments representing the arterial and venous trees (Fig. 4d–g, Supplementary Movie 4). The separate views of the arterial and venous networks clearly illustrate the tissue coverage within this LN (Fig. 4f,g). The venous network of the chosen diameter range is very prominent in the LN and makes up about 44% of the total LN blood vessel volume, whereas the arterial tree within this diameter range represents only 14% of the vascular volume. Collectively, these data further reveal the value of displaying complex measurements in the 3D vascular model, adding new spatial information on vascular branching and arterio-venous relationships to the purely anatomical images.


Organ-wide 3D-imaging and topological analysis of the continuous microvascular network in a murine lymph node.

Kelch ID, Bogle G, Sands GB, Phillips AR, LeGrice IJ, Dunbar PR - Sci Rep (2015)

Network branching.The topology map of full LN vasculature was employed for 3D measurements on the branching pattern from feeding vessels and visualisation of the arterial and venous trees. The branch separation from the main arteriole and vein was calculated and plotted for all branching points within the network (a). Branching from the feeding vessel was further visualised in a rainbow spectrum display in CMGUI for the main arteriole (b) and the exiting vein (c), respectively (a full view is available in Supplementary Movie 3). By selecting only vessels with a diameter above 15 μm, abandoning smaller vessels including the capillary bed (grey), two connected networks can be easily separated, representing the arterial (red) and venous (blue) tree (d–g). Note that the arterial tree appears to have fewer vessels (f), since the diameters of arterioles are generally smaller than veins, and arterioles with a diameter below 15 μm are not included in this view. A 3D view of both vascular trees can be found in Supplementary Movie 4.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4645097&req=5

f4: Network branching.The topology map of full LN vasculature was employed for 3D measurements on the branching pattern from feeding vessels and visualisation of the arterial and venous trees. The branch separation from the main arteriole and vein was calculated and plotted for all branching points within the network (a). Branching from the feeding vessel was further visualised in a rainbow spectrum display in CMGUI for the main arteriole (b) and the exiting vein (c), respectively (a full view is available in Supplementary Movie 3). By selecting only vessels with a diameter above 15 μm, abandoning smaller vessels including the capillary bed (grey), two connected networks can be easily separated, representing the arterial (red) and venous (blue) tree (d–g). Note that the arterial tree appears to have fewer vessels (f), since the diameters of arterioles are generally smaller than veins, and arterioles with a diameter below 15 μm are not included in this view. A 3D view of both vascular trees can be found in Supplementary Movie 4.
Mentions: Based on our dataset it was now possible, for each node in the network, to identify the shortest paths to the feeding artery and to the main exit vein. The number of branches along each path was determined, providing branch counts from the main artery and the main vein for every node in the network (Fig. 4). Overall, the arterial and venous trees display very similar branching patterns. The distribution of branch counts from the artery ranges from 1 to 39, and 1 to 43 from the main vein; both branch counts show approximately Gaussian distribution and a peak around 18 branch points, with a mean of 20 (Fig. 4a). The range of branch counts was translated into a rainbow colour spectrum and the data displayed in 3D across the network (Fig. 4b,c; Supplementary Movie 3). The distribution reveals that the majority of vessels lie within 30 branch counts from the feeding artery, apart from a small proportion that lies further away (red in the spectrum display). The inner centre of the LN in close proximity to the hilum exhibits a low degree of branching for both the artery and vein (light blue areas). Remarkably, the rim of the LN displays a very homogeneous number of about 20–25 branches to the feeding artery (yellow areas; Fig. 4b). The distribution to the main vein is less homogeneous at the surface of the LN but contains a concentration of vessels in the centre that show a high branch count to the vein (Fig. 4c). In an alternative approach to visualising arterial and venous branches, we limited the displayed network to vessels with a diameter larger than 15 μm thus excluding the capillary bed and allowing us to isolate two large vascular segments representing the arterial and venous trees (Fig. 4d–g, Supplementary Movie 4). The separate views of the arterial and venous networks clearly illustrate the tissue coverage within this LN (Fig. 4f,g). The venous network of the chosen diameter range is very prominent in the LN and makes up about 44% of the total LN blood vessel volume, whereas the arterial tree within this diameter range represents only 14% of the vascular volume. Collectively, these data further reveal the value of displaying complex measurements in the 3D vascular model, adding new spatial information on vascular branching and arterio-venous relationships to the purely anatomical images.

Bottom Line: By focussing on critical immune microenvironments we quantified differences in their vascular topology.We further developed a morphology-based approach to identify High Endothelial Venules, key sites for lymphocyte extravasation.These data represent a comprehensive and continuous blood vessel network of an entire organ and provide benchmark measurements that will inform modelling of blood vessel networks as well as enable comparison of vascular topology in different organs.

View Article: PubMed Central - PubMed

Affiliation: Maurice Wilkins Centre, University of Auckland, Private Bag 92-019, Auckland 1142, New Zealand.

ABSTRACT
Understanding of the microvasculature has previously been limited by the lack of methods capable of capturing and modelling complete vascular networks. We used novel imaging and computational techniques to establish the topology of the entire blood vessel network of a murine lymph node, combining 63,706 confocal images at 2 μm pixel resolution to cover a volume of 3.88 mm(3). Detailed measurements including the distribution of vessel diameters, branch counts, and identification of voids were subsequently re-visualised in 3D revealing regional specialisation within the network. By focussing on critical immune microenvironments we quantified differences in their vascular topology. We further developed a morphology-based approach to identify High Endothelial Venules, key sites for lymphocyte extravasation. These data represent a comprehensive and continuous blood vessel network of an entire organ and provide benchmark measurements that will inform modelling of blood vessel networks as well as enable comparison of vascular topology in different organs.

No MeSH data available.


Related in: MedlinePlus