Our device supplies a target pressure to a blood vessel using a serological pipette connected directly to the vessel. As the plunger is manually moved, the amount of liquid in the closed vessel is changed along with pressure.
Our device uses diameter as a method to estimate pressure. The imaging stand shown is designed for a phone camera to capture the vessel in a light controlled setting. Furthermore the stand provides standardization of image collection allowing for increased replicability.
Above shows the process in which images taken with the imaging stand are processed to calculate the average diameter of a vessel. The steps are as follows: A) Convert the image to binary format. B) Crop out the vessel. C) Crop out the calibration tool. D/E) Find the number of white pixels associated with each grouping. F) Use calculations to calculate average diameter.
6 cylindrical representations of a Pulmonary Artery were printed with differing diameters and processed using the routine described above. This result was compared to that of a digital caliper to give the results below.
This graph visualizes the relationship between the measured diameter and the known diameter. A perfect measurement system would have a slope of exactly 1 with no offset. In this case the slope is very close to 1, suggesting high precision, but there is some positive offset that decreases accuracy.
Important numerical results are the average error: 0.061 mm, the standard deviation: 0.01 mm, and the maximum %error of 4.84%.
We checked the ability of our serological pipette to inject and maintain a static pressure with the inflation of a balloon over time. We found that the connector piece provided a watertight seal over time intervals relevant for our project. However, we encountered issues with plunger movement. With high pressures in the balloon the plunger of the pipette moved releasing pressure. This would be largely harmful to our purpose if this issue persisted at pressures we would inflate vessels to. However, we believe that this will not be an issue as the resistance and scale of the balloon is much greater than what is expected in a murine pulmonary artery.
After testing with our device we found that there is a relatively large offset when compared to the low standard deviation, suggesting non-ideal accuracy. This is accentuated when looking at small vessels such as the one shown in trial 6 (error of 4.84%). However, we estimate that the offset is not an issue with our measurement capabilities. This is because the known measurement was made before the cylinders were color adjusted to be viable with our imaging system. By painting each cylinder we artificially introduced some offset, and so we believe our accuracy is likely much higher. Furthermore, the standard deviation of our measurements is 0.01 mm which is equivalent to that of a digital caliper. This indicates that the actual precision of our measurement system could be greater than shown, as the error may have been introduced by the known measurement determined by the digital caliper rather than through our measurement system.
For these reasons we do not believe that this testing has fully described the measurement capabilities of our device. However, we are hopeful that precision will increase or remain constant, and that accuracy will be largely increased given further testing. Furthermore, the offset can also be adjusted on a small scale with alterations of the image processing script which can provide fine tuning of the accuracy.
In order to provide certainty as to the capabilities of our device we want to perform testing using the laser tool provided by the DVJ lab which can reveal the limits of our diameter measurement with its high accuracy and precision.
In order to improve the research capabilities of our device we want to implement mechanical automation along with a pressure sensor. Currently we have no access to a viable pressure sensor due to cost and size constraints, and so instead we estimate pressure using recently taken pressure-diameter data. With a pressure sensor we would not have to rely on this relationship. Furthermore, it would enable automation through access to constant time data.