P767Automated detection and measurement of isolated retinal arterioles by a combination of edge enhancement and cost analysis.

Cardiovascular Research

PubMedID: 25020494

Fernandez J, Bankhead P, Zhou H, Mcgeown J, Curtis T. P767Automated detection and measurement of isolated retinal arterioles by a combination of edge enhancement and cost analysis. Cardiovasc Res. 2014;103 Suppl 1S140.
PURPOSE
Pressure myography studies have played a crucial role in our understanding of vascular physiology and pathophysiology. Such studies depend upon the reliable measurement of changes in the diameter of isolated vessel segments over time. Although several software packages are available to carry out such measurements on arteries and veins, no software exists to study smaller vessels (<50┬Ám in diameter). The purpose of this study is to present a new algorithm to assist with the measurement and tracking of the diameters of small arterioles.

METHODS
Several automatic or semi-automatic algorithms have been developed to assist with the measurement of large arteries and veins, but those programs rely heavily on the use of thresholding methods which are unsuitable to study smaller vessels. Our algorithm uses a different approach based on cost analysis and edge enhancement to measure and track the mid-wall diameter of small arterioles. Vessels from rat and bovine retinas were used in this study. Manual measurements were carried out on a dataset of 102 images by 3 different users and compared to automatic measurements obtained by the software.

RESULTS
Automatic measurements were found to be comparable to manual ones (as shown in Bland-Altman plots; P=0.68, paired t-test), with high correlation (R=0.998) and no bias (slope of regression line not significantly different from 0; P=0.11, unpaired t-test) present between manual and automatic data. The program was also able to track both fast and slow constrictions and dilations during intraluminal pressure changes and following application of several drugs. Variability in automated measurements during analysis of videos (mean SD=0.08um) and processing times (mean time=19ms for mean size=~44000 squared pixels) were also investigated.

CONCLUSION
We present here new software to assist during pressure myography experiments on small isolated retinal arterioles. It provides fast and accurate measurements with low levels of noise and works with both individual images and videos. Although the program was developed to work with small arterioles, it is also capable of tracking the walls of other types of microvessels, including venules and capillaries. It also works well with larger arteries, and therefore may provide an alternative to other packages developed for larger vessels when its features are considered advantageous. The program is presented as a freely available ImageJ plug-in.