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Theoretical error of sectional method for estimation of shape memory polyurethane foam mass loss

  • Lance M. Graul
  • , Shuling Liu
  • , Duncan J. Maitland

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Measuring in vivo degradation for polymeric scaffolds is critical for analysis of biocompatibility. Traditionally, histology has been used to estimate mass loss in scaffolds, allowing for simultaneous evaluation of mass loss and the biologic response to the implant. Oxidatively degradable shape memory polyurethane (SMP) foams have been implemented in two vascular occlusion devices: peripheral embolization device (PED) and neurovascular embolization device (NED). This work explores the errors introduced when using histological sections to evaluate mass loss. Methods: Models of the SMP foams were created to mimic the device geometry and the tetrakaidekahedral structure of the foam pore. These models were degraded in Blender for a wide range of possible degradation amounts and the mass loss was estimated using m sections. Results: As the number of sections (m) used to estimate mass loss for a volume increased the sampling error decreased and beyond m = 5, the decrease in error was insignificant. NED population and sampling errors were higher than for PED scenarios. When m ≥ 5, the averaged sampling error was below 1.5% for NED and 1% for PED scenarios. Discussion/Conclusion: This study establishes a baseline sampling error for estimating randomly degraded porous scaffolds using a sectional method. Device geometry and the stage of mass loss influence the sampling error. Future studies will use non-random degradation to further investigate in vivo mass loss scenarios.

Original languageEnglish (US)
Pages (from-to)237-247
Number of pages11
JournalJournal of Colloid and Interface Science
Volume625
DOIs
StatePublished - Nov 2022
Externally publishedYes

Funding

The authors would like to thank Achu Byju from the Department of Biomedical Engineering at Texas A&M University for his assistance in developing the computational models of the devices.

Funders
Department of Biomedical Engineering at Texas A&M University

    Keywords

    • Computational porous structures
    • Degradation estimation
    • Histopathology
    • Sampling error
    • Shape memory polyurethane foams

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Surfaces, Coatings and Films
    • Colloid and Surface Chemistry

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