Heat impact during laser ablation extraction of mineralised tissue micropillars
Abstract The underlying constraint of ultrashort pulsed laser ablation in both the clinical and micromachining setting is the uncertainty regarding the impact on the composition of material surrounding the ablated region. A heat model representing the laser-tissue interaction was implemented into a...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/bb0fb53550c640aa969b643d24757abf |
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| Sumario: | Abstract The underlying constraint of ultrashort pulsed laser ablation in both the clinical and micromachining setting is the uncertainty regarding the impact on the composition of material surrounding the ablated region. A heat model representing the laser-tissue interaction was implemented into a finite element suite to assess the cumulative temperature response of bone during ultrashort pulsed laser ablation. As an example, we focus on the extraction of mineralised collagen fibre micropillars. Laser induced heating can cause denaturation of the collagen, resulting in ultrastructural loss which could affect mechanical testing results. Laser parameters were taken from a used micropillar extraction protocol. The laser scanning pattern consisted of 4085 pulses, with a final radial pass being 22 $$\upmu {\text {m}}$$ μ m away from the micropillar. The micropillar temperature was elevated to 70.58 $$^{\circ }{\text {C}}$$ ∘ C , remaining 79.42 $$^{\circ }{\text {C}}$$ ∘ C lower than that of which we interpret as an onset for denaturation. We verified the results by means of Raman microscopy and Energy Dispersive X-ray Microanalysis and found the laser-material interaction had no effect on the collagen molecules or mineral nanocrystals that constitute the micropillars. We, thus, show that ultrashort pulsed laser ablation is a safe and viable tool to fabricate bone specimens for mechanical testing at the micro- and nanoscale and we provide a computational model to efficiently assess this. |
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