Cloud native EDA tools & pre-optimized hardware platforms
Brown, J, O¡¯Brien, C.C., Lopes, A.C., Kolandaivelu, K., Edelman, E.R., 2018. , Journal of Biomechanics, 71, 296-301.
Jonathan Brown, Project Manager, (Harvard-MIT Biomedical Engineering Center):
¡°ScanIP was a huge help as it was a tool that allowed us not only to visualize our bench top sample results but also to extract quantitative data that would have otherwise been impossible to investigate.¡±
An in vitro flow loop setup was used to simulate blood flow conditions similar to those in a human coronary artery. Stents were deployed within the flow loops under a range of under expansion condition. Upon completion of the flow loop run samples was MicroCT scanned and the DICOM files were exported for processing in Simpleware ScanIP.
MicroCT data was imported into Simpleware ScanIP and pre-computed thresholding levels were used from prior experimental test to segment stent struts from clot formation and the fluid volume. Smoothing filters were further used to create continuous structures as part of a 3D visualization workflow. The Simpleware ScanIP API was later used to extract pixel valves for each mask for each MicroCT slice and plotted as an indication of clot formation. A custom MATLAB program was utilized to further extract strut position and calculate wall distances from mask pixel values on each slice.
Close-up of one of the stent struts reconstructed in Simpleware ScanIP software
Results indicated that geometric stent features play a significant role in clotting patterns, specifically at a frequency of 0.6225?Hz corresponding to a geometric distance of 1.606?mm. The magnitude-squared coherence between geometric features and clot distribution was greater than 0.4 in all samples.
The top three panels display Wall Distance vs. length along the vessel for each sample with red points indicating the median value for each microCT slice, and green points indicating the mean. The gray shaded region displays the 25%-75% interquartile range for each slice along the length of the vessel. The bottom panel displays clot formation vs. length along the vessel calculated as the number of pixel defined as clot over the total number of lumen defined pixels for each vessel
In stents with poor wall apposition, ranging from 0.27?mm to 0.64?mm maximum malapposition (model of real-world heterogeneity), clots were found to have formed in between stent struts rather than directly adjacent to struts.
Phase lag suggests the fact that no clot is present on the struts but rather dispersed in between the struts
This early work shows how the use of experimental benchtop methods and advance image analysis can be used to gain deeper insight into not only the quantity of clot formation present, but also the spatial location of the clot. This method can lead to a more detailed investigation into the interaction between stent design and deployment on clot formation in the benchtop setting.
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