A new hand-held holder optimizes the parameters of the laser-induced choroidal neovascularization model in mice.

Abstract:

BACKGROUND:The laser-induced choroidal neovascularization (CNV) mouse model, as the most classic animal model of age-related macular degeneration (AMD), has been widely used. We designed a hand-held mouse holder to optimize mouse fixation in the laser-induced CNV modelling process, which was inconvenient until now. This study aimed to evaluate the effectiveness of our in-house hand-held mouse holder design in the laser-induced CNV mouse modelling process. METHODS:Six ophthalmic residents were invited to perform laser-induced CNV mouse modelling by hand or using the holder. We compared the learning time of residents and their physical and mental fatigue with the two methods. In addition, we compared the parameters of CNV modelling with two methods by a skilled operator, including the time of photocoagulation, induction rate and uniformity of CNV lesions. RESULTS:In the learning phase, the average learning time to master the modelling method was significantly shortened by utilizing the holder. The fatigue in the operation process was quantified to a level from 0 to 4, and the physical fatigue by using holder (0.8 ± 0.3) was lower than by hand (2.6 ± 0.4), and the mental fatigue was relieved from 2.3 ± 0.5 to 0.4 ± 0.3. On the other hand, the skilled operator can significantly shorten the time of laser photocoagulation from 146.7 ± 36.0 s to 63.6 + 5.7 s and improve the success rate of modelling from 50.0% ± 8.3%-87.5% ± 6.7% by using a holder compared to hand. In addition, the standard error of the mean (SEM) of the distance between the CNV lesion and the optic nerve (ON) and the distance between each lesion was reduced. CONCLUSION:This hand-held mouse holder could optimize the setting and conditions of laser-induced CNV mouse modelling by improving the learning curve, reducing fatigue, shortening the time for photocoagulation, improving the success rate and consistency of laser-induced lesions.

journal_name

Exp Eye Res

authors

Xue B,Zhang S,Gan L,Lu W,Li J

doi

10.1016/j.exer.2020.108392

subject

Has Abstract

pub_date

2020-12-15 00:00:00

pages

108392

eissn

0014-4835

issn

1096-0007

pii

S0014-4835(20)30650-3

journal_volume

203

pub_type

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