Literature DB >> 31468540

In vivo identification of arteries and veins using two-photon excitation elastin autofluorescence.

Hui Li1,2, Meng Yan1,2, Jia Yu1,2, Qiang Xu1,2, Xianyuan Xia1,2, Jiuling Liao1,2, Wei Zheng1,2.   

Abstract

Distinguishing arteries from veins in vivo has a great significance in clinical practices and preclinical studies. Optical imaging methods such as two-photon microscopy can provide high-resolution morphological information of tissue and are therefore extremely suitable for imaging small blood vessels. However, few optical imaging methods allow in vivo identification of arteries and veins merely utilizing the autofluorescence signal of blood vessels. In this report, we found the arterial wall generates a remarkably stronger two-photon excitation autofluorescence (TPEA) signal compared with the venous wall based on BALB/c mice. According to histological analysis and fluorescence characteristic measurement, the contrast signal is confirmed to be from elastin fibers. Employing this unique feature, we propose an objective and effective artery-vein separation strategy that considers the presence of the elastin-TPEA border as the indicator of arteries. Using this strategy, the arterial and venous networks of the dorsal skin and cerebral cortex of BALB/c mice are demonstrated to be excellently mapped and accurately separated in vivo without depending on any exogenous contrast agent, empirical knowledge, and algorithm. This study may provide a novel technique for mapping arterial and venous networks for anatomic research as well as an extra aid to basic researches on the mechanism, diagnosis, and treatment of blood vessel-related diseases.
© 2019 Anatomical Society.

Entities:  

Keywords:  artery-vein separation; autofluorescence imaging; elastin; two-photon microscopy

Mesh:

Substances:

Year:  2019        PMID: 31468540      PMCID: PMC6904638          DOI: 10.1111/joa.13080

Source DB:  PubMed          Journal:  J Anat        ISSN: 0021-8782            Impact factor:   2.610


  27 in total

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