Luke Werrett and Dr. Kenneth Solen, Chemical Engineering

The objective of this research project was to identify a correlation between a traditional platelet activity test using an aggregometer, and a new test that measures interactions between blood and man-made materials in a simulated blood flow environment. A correlation between these data would give artificial organ recipients and open-heart surgery candidates a more thorough risk analysis of their situation, and indicate the need for caution or additional medication.

Experiments were conducted at the Chemical Engineering Blood Material Interactions Lab from October 2006 to April 2007. Blood donations were taken from volunteers as often as the lab research staff could meet together. Each donor was also prescreened an interviewed, to restrict the blood donations to those that had refrained from medications in the previous two weeks. In all, 15 donors gave blood for testing, but due to the complicated nature of the experiments, only 12 yielded usable data.

The traditional test, using the aggrogometer, measures the platelet aggregation rate of activated blood. ADP (adenosine diphosphate) is added to a sample of blood from a donor that is kept at 37 C. The ADP catalyzes platelet aggregation, and the aggrogometer device measures the increase in resistance to a small current running through the sample. Results are recorded on two separate charts from two separate samples from the donor. There was significant variation between the two charts, but one was not consistently higher or lower than the other. For data analysis, the lower of the two aggregation rates was used.

The flow cell experiment was performed simultaneous to the aggregation experiment. This experiment simulates the interaction between biomaterials and blood and detects microemboli (platelet and protein aggregates) down stream from the simulated flow system by light scattering microemboli detector (LSMD). The flow cell and LSMD technology were developed by Goodman et al and Solen et al respectively, more details on these methods are found in this ORCA project proposal and the included references. Data collected from the LSMD included a count of microemboli to pass the scanner, and the moment or size of each correlating microemboli.

The data from the aggregation experiment is in the form of ohms/minute, the resistance rate being directly proportional to the aggregation rate. To put the LSMD data is a comparable form, four different values were calculated for each experiment. First, the maximum rate of microemboli in moment/minute during the 30-minute test was calculated, using a rolling average over 2 and 3 minute periods. An average rate had to be used, as microembolism does not happen continuously. As the size of thrombi on the biomaterial surface increases, the adhesive nature of the thrombi is overcome by the force of turbulent flow causing a detached emboli to pass through the LSMD in the blood stream. When the emboli pass through the detector, the instantaneous rate is infinite, but averaged over a larger period of time, a rate reflecting a more continuous function can be found (Figure 1). Second, a similar rate, the rolling average count/minute was found over both 2 and 3 minute periods. Third, the total moment, or cumulative size of microemboli for the entire 30 minute period was calculated, and fourth, the similar cumulative count of microemboli was calculated.

The four calculated values from the flow cell experiment were compared individually to the platelet aggregation rate to search for a correlation. The data indicated that as the aggregation rate increases, so do all four indicators for the flow cell experiment. Due to natural biological variation and a low volume of data, none of the relationships were statistically significant. The strongest correlation indicated that the total moment increases according to a quadratic relationship to the aggregation rate. Because R2=0.7613 for this correlation, it only indicates that there may be a quadratic relationship, though the linear relationship had R2=0.5408, indicating a correlation nearly as strong (Figure 2). The strongest linear correlation was for the moment/minute rate vs. the aggregation rate with an R2=0.6156.

While none of these correlations are statistically significant, they indicate that a significant correlation may exist. Biological variation cannot be decreased easily, but more data from donors, including repetitions of the experiment with existing donors, should help to make the correlation more rigorous. The Blood Materials Interaction Laboratory will continue to gather this data and prove that a significant correlation exists between thomboembolism and platelet aggregation and effectively model it.