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一种基于人工智能的新型方法用于卵外绒毛尿囊膜模型中血管生成的定量评估。

A Novel Artificial Intelligence-Based Approach for Quantitative Assessment of Angiogenesis in the Ex Ovo CAM Model.

作者信息

Faihs Lorenz, Firouz Bardia, Slezak Paul, Slezak Cyrill, Weißensteiner Michael, Ebner Thomas, Ghaffari Tabrizi-Wizsy Nassim, Schicho Kurt, Dungel Peter

机构信息

Department of Oral and Maxillofacial Surgery, Medical University of Vienna, 1090 Vienna, Austria.

Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, 1200 Vienna, Austria.

出版信息

Cancers (Basel). 2022 Sep 1;14(17):4273. doi: 10.3390/cancers14174273.

Abstract

Angiogenesis is a highly regulated process. It promotes tissue regeneration and contributes to tumor growth. Existing therapeutic concepts interfere with different steps of angiogenesis. The quantification of the vasculature is of crucial importance for research on angiogenetic effects. The chorioallantoic membrane (CAM) assay is widely used in the study of angiogenesis. Ex ovo cultured chick embryos develop an easily accessible, highly vascularised membrane on the surface. Tumor xenografts can be incubated on this membrane enabling studies on cancer angiogenesis and other major hallmarks. However, there is no commonly accepted gold standard for the quantification of the vasculature of the CAM. We compared four widely used measurement techniques to identify the most appropriate one for the quantification of the vascular network of the CAM. The comparison of the different quantification methods suggested that the CAM assay application on the IKOSA platform is the most suitable image analysis application for the vasculature of the CAM. The new CAM application on the IKOSA platform turned out to be a reliable and feasible tool for practical use in angiogenesis research. This novel image analysis software enables a deeper exploration of various aspects of angiogenesis and might support future research on new anti-angiogenic strategies for cancer treatment.

摘要

血管生成是一个高度受调控的过程。它促进组织再生并有助于肿瘤生长。现有的治疗理念会干扰血管生成的不同步骤。脉管系统的量化对于血管生成效应的研究至关重要。鸡胚绒毛尿囊膜(CAM)试验在血管生成研究中被广泛应用。体外培养的鸡胚在其表面形成一个易于接近且血管高度丰富的膜。肿瘤异种移植物可在该膜上孵育,从而能够对癌症血管生成及其他主要特征进行研究。然而,对于CAM脉管系统的量化尚无普遍认可的金标准。我们比较了四种广泛使用的测量技术,以确定最适合量化CAM血管网络的技术。不同量化方法的比较表明,IKOSA平台上的CAM试验应用是最适合用于CAM脉管系统的图像分析应用。IKOSA平台上的新型CAM应用被证明是血管生成研究实际应用中一种可靠且可行的工具。这种新颖的图像分析软件能够更深入地探索血管生成的各个方面,并可能支持未来关于癌症治疗新抗血管生成策略的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ba/9454718/38006db7de5b/cancers-14-04273-g001.jpg

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