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Simpleware Case Study: Analyzing the Formation of Thrombosis in Malapposed Coronary Stents

Stent thrombosis is a major complication of coronary stent and scaffold intervention. While often unanticipated and lethal, its incidence is low making mechanistic examination difficult through clinical investigation alone. Thus, throughout the technological advancement of these devices, experimental models have been indispensable in furthering our understanding of device safety and efficacy. Beyond models we require new analysis methods that leverage advance imaging processing techniques. Digital signal processing was used in an established flow loop model of coronary stent performance to investigate local flow effects due to geometric stent features and ultimately its relationship to thrombus formation.

Overview

Stent thrombosis is a major complication of coronary stent and scaffold intervention. While often unanticipated and lethal, its incidence is low making mechanistic examination difficult through clinical investigation alone. Thus, throughout the technological advancement of these devices, experimental models have been indispensable in furthering our understanding of device safety and efficacy. Beyond models we require new analysis methods that leverage advance imaging processing techniques. Digital signal processing was used in an established flow loop model of coronary stent performance to investigate local flow effects due to geometric stent features and ultimately its relationship to thrombus formation.

Highlights

  • Workflow uses MicroCT image data to investigate geometric stent features and their relationship to thrombus formation
  • Simpleware software used to reconstruct stent struts, and link quantitative data to MATLAB tool for analysis
  • Combination of experimental data and advanced image process gives insights into stent design and clot formation

Reference

Brown, J, O¡¯Brien, C.C., Lopes, A.C., Kolandaivelu, K., Edelman, E.R., 2018. , Journal of Biomechanics, 71, 296-301.

Thanks to

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.¡±

Collecting Experimental Data

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.

Image Processing with Simpleware Software

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 stent strut reconstructed in Simpleware ScanIP software

Close-up of one of the stent struts reconstructed in Simpleware ScanIP software

Results and Future Work

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.

Calculation of wall distances for each vessel sample with stent

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.

No clot is present on the struts but rather dispersed in between the 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.

Any Questions?

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