Abstract
Purpose: :
Measurement of retinal blood flow has been used to provide a microcirculatory assessment of the haemodynamic state of the retina. To date, there have been no studies that have looked at measuring real-time blood velocity in bulbar conjunctival vessels. The objective was to design and develop a system to non-invasively quantify the blood velocity in the conjunctival vessels, with the prospect of gaining a comprehensive understanding of the conjunctival circulation in health and disease.
Methods: :
Over an 8 hour diurnal period, conjunctival vessels of healthy individuals were digitally imaged with high enough magnification to clearly resolve movement of the blood within the vessel. Calibrated videos were imported into the video processing utility VirtualDub and cropped into image sequences of manageable size. After the image sequences were converted to AVI files, pre-processed and registered to improve image quality, vessels within the sequences were automatically recognized. For each vessel, a signal that correlated to blood cell position was extracted from each frame, and the inter-frame displacement was estimated through a modified DTW (dynamic time warping) algorithm. This provided the red blood cell velocity over time in each point of the vessels. Thus, from these estimates, the mean red blood cell velocity for each vessel may be easily evaluated.
Results: :
Velocity in imaged bulbar conjunctival vessels ranges from 0 to 698 ± 87 microns/sec. In some vessels, velocity was negative, with flow changing direction during a cardiac cycle. Analysis of diurnal data suggests that, although variable between subjects and depending on vessel diameter, velocity is at a maximum later in the day and at a minimum at approximately midday.
Conclusions: :
Signal displacement estimation through DTW algorithm can be used to estimate both local and mean red blood cell velocity measurements over time and promises to enable the study of conjunctival haemodynamics under various experimental and physiological conditions.
Keywords: conjunctiva • imaging/image analysis: non-clinical • anterior segment