Analysis of Vascular Architecture and Parenchymal Damage Generated by Reduced Blood Perfusion in Decellularized Porcine Kidneys Using a Gray Level Co-occurrence Matrix

Abstract

There is no cure for kidney failure, but a bioartificial kidney may help address this global problem. Decellularization provides a promising platform to generate transplantable organs. However, maintaining a viable vasculature is a significant challenge to this technology. Even though angiography offers a valuable way to assess scaffold structure/function, subtle changes are overlooked by specialists. In recent years, various image analysis methods in radiology have been suggested to detect and identify subtle changes in tissue architecture. The aim of our research was to apply one of these methods based on a gray level co-occurrence matrix (Topalovic et al.) computational algorithm in the analysis of vascular architecture and parenchymal damage generated by hypoperfusion in decellularized porcine. Perfusion decellularization of the whole porcine kidneys was performed using previously established protocols. We analyzed and compared angiograms of kidneys subjected to pathophysiological arterial perfusion of whole blood. For regions of interest Santos et al. covering kidney medulla and the main elements of the vascular network, five major GLCM features were calculated: angular second moment as an indicator of textural uniformity, inverse difference moment as an indicator of textural homogeneity, GLCM contrast, GLCM correlation, and sum variance of the co-occurrence matrix. In addition to GLCM, we also performed discrete wavelet transform analysis of angiogram ROIs by calculating the respective wavelet coefficient energies using high and low-pass filtering. We report statistically significant changes in GLCM and wavelet features, including the reduction of the angular second moment and inverse difference moment, indicating a substantial rise in angiogram textural heterogeneity. Our findings suggest that the GLCM method can be successfully used as an addition to conventional fluoroscopic angiography analyses of micro/macrovascular integrity following in vitro blood perfusion to investigate scaffold integrity. This approach is the first step toward developing an automated network that can detect changes in the decellularized vasculature.

Keywords: angiography; bioartificial kidney; bioengineering; decellularized kidney; decellularized porcine kidney; gray level co-occurrence matrix algorithm; parenchymal damage; vascular architecture.

Figure 1

Photographs of the bioreactor used to perfuse decellularized scaffolds with whole blood. (A) Image outlining the arterial line (which was then attached to the cannulated renal artery) and venous lines (which was left open to act as a venous reservoir to facilitate fluid recirculation) before the addition of the scaffold. (B) Image of an acellular kidney perfused with PBS illustrates how the scaffold recirculated fluid that emanated from its renal vein (red arrow) and open-ended venous line. (C) Image of a scaffold being perfused with whole pig blood.

Figure 2

Fluoroscopic angiography. (A) Photograph of a decellularized scaffold that was set to be infused with contrast agent. (B) An angiogram of the scaffold before it was perfused with blood displaying the decellularized vascular network and region of interest Davidovic et al., dashed rectangular region, covering kidney medulla and the main elements of this network. (C) An angiogram of the scaffold after 24 h of hypoperfusion (arterial infusion rate 20 ml/min). The major arterial branches of the renal vasculature are defined as follows, RA, renal artery; SA, segmental artery; LA, lobar artery; IA, interlobar artery; and AA, arcuate artery.

Figure 3

Estimated diameters of each major arterial branch of the renal vasculature. A comparison of the diameters of the major arterial branch of the renal vasculature in non-perfused and hypoperfused decellularized kidneys.

Figure 4

Renal arterial branching patterns. A comparison of changes to the innate (non-perfused) branching patterns that occurred with hypoperfusion using the following criteria: 1°, only the renal artery was left intact; 2°, only the renal and segmental arteries were left intact; 3°, only the renal, segmental, and lobar arteries were left intact; 4°, only the renal, segmental, lobar, interlobar arteries were left intact; and 5°, all five vascular branches were left intact.

Figure 5

GLCM indicators before and after blood perfusion. (A) Angular second moment. (B) Inverse difference moment. (C) GLCM Contrast. (D) GLCM Correlation. (E) GLCM Variance. *p < 0.05; **p < 0.01.