Various lung diseases, including pulmonary hypertension, chronic obstructive pulmonary disease or bronchopulmonary dysplasia, are associated with structural and architectural alterations of the pulmonary vasculature. The light microscopic (LM) analysis of the blood vessels is limited by the fact that it is impossible to identify which generation of the arterial tree an arterial profile within a LM microscopic section belongs to. Therefore, we established a workflow that allows for the generation-specific quantitative (stereological) analysis of pulmonary blood vessels. A whole left rabbit lung was fixed by vascular perfusion, embedded in glycol methacrylate and imaged by micro-computed tomography (µCT). The lung was then exhaustively sectioned and 20 consecutive sections were collected every 100 µm to obtain a systematic uniform random sample of the whole lung. The digital processing involved segmentation of the arterial tree, generation analysis, registration of LM sections with the µCT data as well as registration of the segmentation and the LM images. The present study demonstrates that it is feasible to identify arterial profiles according to their generation based on a generation-specific color code. Stereological analysis for the first three arterial generations of the monopodial branching of the vasculature included volume fraction, total volume, lumen-to-wall ratio and wall thickness for each arterial generation. In conclusion, the correlative image analysis of µCT and LM-based datasets is an innovative method to assess the pulmonary vasculature quantitatively.

各种肺部疾病，包括肺动脉高压，慢性阻塞性肺疾病或支气管肺发育不良，都与肺血管的结构和结构改变有关。血管的光学显微镜（LM）分析受到以下事实的限制：无法识别LM显微镜部分内的动脉轮廓属于哪一代动脉树。因此，我们建立了一个工作流程，可以对肺血管进行特定世代的定量（立体）分析。整个兔左肺通过血管灌注固定，包埋在甲基丙烯酸乙二醇酯中，并通过微计算机断层扫描（µCT）进行成像。然后将肺彻底切开，每100 µm收集20个连续切片，以获得整个肺的系统均匀的随机样本。数字处理包括动脉树的分割，生成分析，LM切片与µCT数据的配准以及分割和LM图像的配准。本研究表明，根据一代特定的颜色代码，根据它们的生成来识别动脉轮廓是可行的。脉管系统单脚掌分支的前三个动脉世代的体视学分析包括每个动脉世代的体积分数，总体积，管腔壁比和壁厚。结论，