A multilevel framework to reconstruct anatomical 3D models of the hepatic vasculature in rat livers

Abstract

The intricate (micro)vascular architecture of the liver has not yet been fully unravelled. Although current models are often idealized simplifications of the complex anatomical reality, correct morphological information is instrumental for scientific and clinical purposes. Previously, both vascular corrosion casting (VCC) and immunohistochemistry (IHC) have been separately used to study the hepatic vasculature. Nevertheless, these techniques still face a number of challenges such as dual casting in VCC and limited imaging depths for IHC. We have optimized both techniques and combined their complementary strengths to develop a framework for multilevel reconstruction of the hepatic circulation in the rat. The VCC and micro-CT scanning protocol was improved by enabling dual casting, optimizing the contrast agent concentration, and adjusting the viscosity of the resin (PU4ii). IHC was improved with an optimized clearing technique (CUBIC) that extended the imaging depth for confocal microscopy more than five-fold. Using in-house developed software (DeLiver), the vascular network - in both VCC and IHC datasets - was automatically segmented and/or morphologically analysed. Our methodological framework allows 3D reconstruction and quantification of the hepatic circulation, ranging from the major blood vessels down to the intertwined and interconnected sinusoids. We believe that the presented framework will have value beyond studies of the liver, and will facilitate a better understanding of various parenchymal organs in general, in physiological and pathological circumstances.

Keywords: 3D modeling; confocal laser scanning; hepatic vasculature; immunohistochemistry; micro-CT-scanning; morphological analysis; rat liver; vascular corrosion casting.

Figure 1

(A) Segmentation pipeline of the macrocirculation obtained by vascular corrosion casting (VCC) and μCT scanning: (i) original image with three different gray values for hepatic artery (HA), portal vein (PV), and hepatic vein (HV) is exposed to (ii) a dynamic region growing; (iii) subsequently a closing operation is performed; (iv) which is then followed by smart expansion (of the borders) and slight manual operations. (B) Segmentation pipeline of the microcirculation obtained by immunohistochemistry (IHC) and confocal laser scanning: (i) original image is (ii) preprocessed; (iii) thereafter binarized and despeckled, and finally (iv) a morphological cavity‐filling algorithm and several morphological operations (opening, closing, remove small objects) are executed.

Figure 2

Schematic illustration of the morphological analysis approach. (A) Example of a converged diameter‐defined top‐down ordering method for the macrocirculation (black structures). The analysis is applied to the skeleton of the macrocirculation (white), whereby intersection nodes are indicated as yellow circles. Branches are connected to at least one intersection node. For the ordering method, branches (e.g. three branches belonging to the inlet) are first combined into one coupled branch if the tapering of the radius is higher than 0.7 and the angle (α) between the last segment (last five nodes) of the parent branch and the first segment (first five nodes) of the daughter branch is greater than 160°. The generation numbers are then iteratively reordered based on the mean radius of the coupled branches compared with the mean radii (R _n) and standard deviations (SD _n) of the generations. (B) Simplified 2D sinusoidal network (black) with its skeleton (white). Intersection branches (1) are found in‐between adjacent intersection nodes (yellow circles). Dead‐end branches (2) are only connected to one intersection node. Composite branches (3) are located between two intersection nodes, which are not part of a dead‐end branch and usually comprise several intersection branches. Image is based on Hammad et al. (2014).

Figure 3

Vascular corrosion cast of a rat liver, showing the liver lobes. The medial lobe is formed by the right medial lobe (RML) and left medial lobe (LML). The right liver lobe is formed by the superior right lateral lobe (SRL) and the inferior right lateral lobe (IRL). The left liver lobe is formed by the left lateral lobe (LLL). The caudate lobe (CL) is formed by the anterior caudate lobe (ACL), posterior caudate lobe (PCL) and caudate process (CP). (A) The portal venous (and part of the hepatic venous) system is colored blue, whereas the hepatic arterial (and part of the hepatic venous) system is pigmented with a yellow dye. A smaller sample was dissected from the right medial lobe (RML) to study the microcirculation. (B) Yellow‐colored parts of the intestines' arterial system are also included (see black arrow) as well as the portal venous catheter (see dashed arrow). (C) Dissected microvascular sample of a rat liver. (D) Microscope image of the cast surface, illustrating the liver lobules (i.e. cloud‐like structures in the image; black contour). (E) SEM‐image of the sinusoids.

Figure 4

3D reconstructions of a rat liver. (A) The three vascular trees. (B) 3D reconstruction of the microcirculation containing sinusoids (red), afferent and efferent microvessels. (C) A virtually dissected and reconstructed 3D cube containing only sinusoids with the dimensions 350 × 350 × 200 μm³. (D) Hepatic venous system. (E) Portal venous system. (F) Hepatic arterial system.

Figure 5

Diameter‐defined top‐down ordering method for the vascular trees, resulting in nine, eight and six generations for the (A) hepatic vein [HV; including caudal vena cava (CVC)], (B) portal vein (PV), and (C) hepatic artery (HA), respectively. The HV mean radii decreased from 2.73  (CVC) to 9.61 × 10⁻² mm, the PV radii from 1.18 to 9.84 × 10⁻² mm, and the HA radii from 1.80 × 10⁻¹ to 4.36 × 10⁻² mm.

Figure 6

Example of intensity decay in Z stacks acquired through confocal microscopy. Non‐cleared sample (A) versus cleared liver tissue sample (B) at imaging depths z = 14, 78 and 144 μm. For cleared liver tissue, a uniform image intensity can be maintained over the entire information retrieval depth, whereas the intensity decay is clearly noticeable for non‐cleared liver samples.

Figure 7

The morphological graph analysis pipeline for microsamples obtained by immunohistochemistry (IHC) and vascular corrosion casting (VCC). (A) Segmented 2D image stack of a IHC cleared sample (B) 3D reconstruction of the segmented structures (dimensions 322 × 322 × 170 μm³). (C) Visualization of the network graph, where the edges are colored according to their branch length. (D) Histogram of the branch length. (E) Visualization of the network graph, where the nodes are colored according to their branch mean radius. (F) Histogram of the branch mean radius.

Figure 8

Overview of the measured morphological parameters in case of non‐cleared (n = 3), cleared (n = 3) and μCT (n = 3) samples. Calculated parameters include (i) the mean composite branch radius; (ii) mean composite branch length; (iii) mean composite branch tortuosity; (iv) number of composite branches for each sample; (v) mean sinusoidal porosity; and (vi) the maximal information retrieval depth.