Extracting Mural and Volumetric Growth Patterns of Platelet Aggregates on Engineered Surfaces by Use of an Entity Tracking Algorithm

利用实体追踪算法提取工程表面血小板聚集体的壁面和体积生长模式

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Abstract

Thrombosis is a major complication that can occur in both blood-contacting devices and regions and in regions of vascular damage. Microfluidic devices are popular templates to model various thrombogenic settings and to assess conditions that lead to bulk channel occlusion. However, area-averaged measurements miss the opportunity to extract real-time information on thrombus evolution and early dynamics of thrombus formation and propagation, which result in late-stage bulk channel occlusion. To clarify these dynamics, we have developed a standalone tracking algorithm that uses consecutive image connectivity and minimal centroid distance mappings to uniquely index all appearing thrombi in fluorescence time-lapse videos http://links.lww.com/ASAIO/A887 , and http://links.lww.com/ASAIO/A888 . This leads to measurements of all individual aggregates that can in turn be studied as ensembles. We applied tracking to fluorescence time-lapse videos http://links.lww.com/ASAIO/A887 , and http://links.lww.com/ASAIO/A888 of thrombosis across both collagen-functionalized substrate and across the surface of a roughened titanium alloy (Ti6Al4V) at a shear rate of 4000 s -1 . When comparing ensemble-averaged measurements to area-averaged metrics, we unveil immediate, steady thrombus growth at early phases on collagen surfaces and unstable thrombus attachment to roughened Ti6Al4V surfaces on Ti6Al4V surfaces. Additionally, we introduce tracked thrombus eccentricity and fluorescence intensity as additional volumetric measures of thrombus growth that relate back to the primary thrombosis mechanism at play. This work advocates for the complementation of surface macrostate metrics with characteristic thrombus microstate growth patterns to accurately predict critical thrombosis events.

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