A combined morphometric approach to feature mouse kidney vasculature.

Physiological kidney function is closely related to the state of the vascular network. Disorders, such as capillary rarefaction, predispose to chronic kidney disease (CKD). In this context, deepening of the methodologies for studying the renal vascular network can be of basic importance. To meet this need, numerous animal models and, in parallel, several methods have been developed. In this work we propose a protocol to accurately feature kidney vasculature in mouse, however, the same protocol is suitable to be applied also to other animal models. The approach is multiparametric and mainly based on micro-computed tomography (μCT) technique. Micro-ct allows to study in detail the vascular network of any organ by exploiting the possibility to perfuse the sample with a contrast agent. The proposed protocol provides a fast and reliable method to extract quantitative information from the μCT scan by using only the basic functions of the software supplied by the scanner without any additional analysis. Through iterative cropping of the scanned ROI and calculation of a sample-specific threshold we calculated that the average volume of a female BALB/c kidney of eighth weeks is 147.8 mm (5.4%). We also pointed out that the average volume of the vascular network is 4.9% (0.3%). In parallel we performed traditional histological and immunofluorescence techniques to integrate the information gained via μCT and to frame them in the tissue context. Vessel count on histological sections showed a different density in the different regions of the organ parenchyma, in detail, vessel density in the cortex was 19.03 ± 2.51 vessels/ROI while in the medulla it was 10.6 ± 1.7 vessels/ROI and 5.4 ± 1.3 vessels/ROI in the outer and inner medulla, respectively. We then studied vessel distribution in the renal parenchyma which showed that the 55% of vascular component is included in the cortex, the 30% in the outer medulla and the 15% in the inner medulla. Collectively, we propose an integrated approach that can be particularly useful in the preclinical setting to characterize the vasculature of any organ accurately and rapidly.