Evaluating Hydroxyapatite, Gold Nanoparticles, and Graphene-Copper as Bimodal Agents for X-ray and Computed Tomography.
Bruno Pugliese PereiraClaudia AntoineAline Oliveira da Silva de BarrosLeonardo de Castro PacíficoMartha Sahylí Ortega PijeiraAlexandre Malta RossiEduardo Ricci-JuniorLuciana Magalhães Rebelo AlencarPedro Filho Noronha SouzaPublished in: Bioengineering (Basel, Switzerland) (2023)
A global need exists for new and more effective contrast agents for computed tomography and traditional X-ray modalities. Among the few options available nowadays, limitations imposed by industrial production, performance, and efficacy restrict the use and reduce the potential of both imaging techniques. The use of nanomaterials as new contrast agents for X-ray and computed tomography is an innovative and viable way to increase the options and enhance performance. In this study, we evaluated eight nanomaterials: hydroxyapatite doped with zinc (Zn-HA 10%); hydroxyapatite doped with strontium (Sr-HA 10%); hydroxyapatite without thermal treatment (HA 282 STT); thermally treated hydroxyapatite (HA 212 500 °C and HA 01.256 CTT 1000 °C); hydroxyapatite microspheres (HA microspheres); gold nanoparticles (AuNP); and graphene oxide doped with copper (Cu-GO). The results showed that for both imaging modalities; HA microspheres were the best option, followed by hydroxyapatite thermally treated at 1000 °C. The nanomaterials with the worst results were hydroxyapatite doped with zinc (Zn-HA 10%), and hydroxyapatite doped with strontium (Sr-HA 10%). Our data demonstrated the potential of using nanomaterials, especially HA microspheres, and hydroxyapatite with thermal treatment (HA 01.256 CTT 1000 °C) as contrast agents for X-ray and computed tomography.
Keyphrases
- computed tomography
- bone regeneration
- dual energy
- lactic acid
- high resolution
- gold nanoparticles
- tissue engineering
- quantum dots
- positron emission tomography
- contrast enhanced
- magnetic resonance imaging
- highly efficient
- magnetic resonance
- metal organic framework
- image quality
- molecularly imprinted
- electronic health record
- climate change
- pet ct
- artificial intelligence
- deep learning
- fluorescence imaging