Article: Theoretical error of sectional method for estimation of shape memory polyurethane foam mass loss
Journal of colloid and interface science. 2022 Nov., v. 625
2022
Abstract: 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 ... ...
Abstract | 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. 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. 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. 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. |
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Keywords | biocompatibility ; foams ; geometry ; histology ; polyurethanes |
Language | English |
Dates of publication | 2022-11 |
Size | p. 237-247. |
Publishing place | Elsevier Inc. |
Document type | Article |
ZDB-ID | 241597-5 |
ISSN | 1095-7103 ; 0021-9797 |
ISSN (online) | 1095-7103 |
ISSN | 0021-9797 |
DOI | 10.1016/j.jcis.2022.06.045 |
Database | NAL-Catalogue (AGRICOLA) |
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