Figure 2.

Construction of a computational single-cell-based model from two whole slide scans of a liver lobe by an image processing and analysis chain

(A) PCNA stained micrograph of a mouse liver lobe.

(B) A neighboring slice stained for glutamine synthetase (GS).

(C) Intermediate step in which the contrast of the micrographs was enhanced by contrast-limited adaptive histogram equalization (CLAHE). The localization of the capsule (red outline) and of larger vessels (blue/cyan) was determined. The effect of CLAHE is illustrated within the red rectangle in (B). GS permits distinguishing between central veins and portal veins or arteries. Each central vein of a liver lobule is circumvented by GS-positive hepatocytes. The green coloring shows the GS staining of (B) used to identify the central veins among the larger vessels in the image (red in (D)).

(E–G) Growth simulation of a liver lobe. Time series of proliferating and growing lobe. (E) t = 0 days, (F) t = 2 days, (G) t = 5 days.

(H–J) Exemplary 3D models automatically constructed from the dataset (A). (H-J) only differ in the height that is extrapolated from (A) (H: 3D with a height of 4 cell layers, I: 3D with a height of 10 cell layers). In (H–J) model cells were omitted to reveal the sinusoidal network. The coloring of the network in (H–J) illustrates the predicted oxygen concentration within the sinusoids (blue = high concentration in the portal field, red = low concentration near the central veins). All simulations were carried out for the whole lobe but only half of the lobe was visualized. (J) Magnified sinusoidal network within the lobe model. The sinusoids were not directly reconstructed from bright-field micrographs but are based on the statistical data obtained from the corresponding three-dimensional volume datasets obtained by confocal fluorescence microscopy (Hoehme et al., 2010).