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研究肺血管的三维重建和体视学的最新进展。

Recent developments in 3-D reconstruction and stereology to study the pulmonary vasculature.

机构信息

Institute of Functional and Applied Anatomy, Hannover Medical School , Hannover , Germany.

Cluster of Excellence REBIRTH (From Regenerative Biology to Reconstructive Therapy), Hannover , Germany.

出版信息

Am J Physiol Lung Cell Mol Physiol. 2018 Aug 1;315(2):L173-L183. doi: 10.1152/ajplung.00541.2017. Epub 2018 Apr 12.

DOI:10.1152/ajplung.00541.2017
PMID:29644892
Abstract

Alterations of the pulmonary vasculature are an important feature of human lung diseases such as chronic obstructive pulmonary disease, pulmonary hypertension, and bronchopulmonary dysplasia. Experimental studies to investigate the pathogenesis or a therapeutic intervention in animal models of these diseases often require robust, meaningful, and efficient morphometric data that allow for appropriate statistical testing. The gold standard for obtaining such data is design-based stereology. However, certain morphological characteristics of the pulmonary vasculature make the implementation of stereological methods challenging. For example, the alveolar capillary network functions according to the sheet flow principle, thus making unbiased length estimations impossible and requiring other strategies to obtain mechanistic morphometric data. Another example is the location of pathological changes along the branches of the vascular tree. For developmental defects like in bronchopulmonary dysplasia or for pulmonary hypertension, it is important to know whether certain segments of the vascular tree are preferentially altered. This cannot be overcome by traditional stereological methods but requires the combination of a three-dimensional data set and stereology. The present review aims at highlighting the great potential while discussing the major challenges (such as time consumption and data volume) of this combined approach. We hope to raise interest in the potential of this approach and thus stimulate solutions to overcome the existing challenges.

摘要

肺血管的改变是人类肺部疾病(如慢性阻塞性肺疾病、肺动脉高压和支气管肺发育不良)的一个重要特征。为了研究这些疾病的发病机制或在动物模型中进行治疗干预,实验研究通常需要可靠、有意义且高效的形态计量学数据,以便进行适当的统计检验。获得这些数据的金标准是基于设计的体视学。然而,肺血管的某些形态特征使得体视学方法的实施具有挑战性。例如,肺泡毛细血管网络根据片流原理发挥作用,因此不可能进行无偏长度估计,需要采用其他策略来获得机械形态计量学数据。另一个例子是血管树分支上病理变化的位置。对于支气管肺发育不良等发育缺陷或肺动脉高压,了解血管树的某些节段是否优先发生改变非常重要。这不能通过传统的体视学方法来克服,需要结合三维数据集和体视学。本综述旨在强调这种联合方法的巨大潜力,同时讨论其主要挑战(如时间消耗和数据量)。我们希望引起人们对这种方法潜力的兴趣,从而激发解决现有挑战的方法。

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