Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, 80137 Naples, Italy.
Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, 80137 Naples, Italy; Center for Advanced Biomaterials for Healthcare, Istituto Italiano di Tecnologia, 80125 Naples, Italy.
Ann Anat. 2021 Sep;237:151727. doi: 10.1016/j.aanat.2021.151727. Epub 2021 Mar 30.
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.
生理肾脏功能与血管网络状态密切相关。毛细血管稀疏等异常会导致慢性肾脏病（CKD）。在这种情况下，深入研究肾脏血管网络的方法可能具有基础重要性。为了满足这一需求，已经开发了许多动物模型和几种方法。在这项工作中，我们提出了一种在小鼠中准确描述肾脏血管结构的方案，但该方案也适用于其他动物模型。该方法是多参数的，主要基于微计算机断层扫描（μCT）技术。微 CT 技术通过对样本进行造影剂灌注，能够详细研究任何器官的血管网络。该方案通过仅使用扫描仪提供的基本功能对 μCT 扫描进行快速、可靠的定量信息提取，无需任何额外的分析。通过对 ROI 进行迭代裁剪和计算特定于样本的阈值，我们计算出 8 周龄雌性 BALB/c 肾脏的平均体积为 147.8mm（5.4%）。我们还指出，血管网络的平均体积为 4.9%（0.3%）。同时，我们还进行了传统的组织学和免疫荧光技术，以整合通过 μCT 获得的信息，并将其置于组织背景下。对组织切片上的血管计数显示，器官实质的不同区域的血管密度不同，具体而言，皮质中的血管密度为 19.03±2.51 个/ROI，而在髓质中为 10.6±1.7 个/ROI，在外髓和内髓中分别为 5.4±1.3 个/ROI。然后，我们研究了肾脏实质中的血管分布，结果表明血管成分的 55%包含在皮质中，30%包含在外髓中，15%包含在内髓中。总的来说，我们提出了一种综合方法，在临床前环境中，该方法特别有助于快速准确地描述任何器官的血管结构。
