Porous Upconversion Nanostructures as Bimodal Biomedical Imaging Contrast Agents

Abstract

Lanthanide ion doped upconversion nanoparticles (UCNPs) hold great promise as multimodal contrast agents for a range of medical imaging techniques, including optical bioimaging (OBI), magnetic resonance imaging (MRI), and computed tomography (CT). However, it is challenging to obtain UCNPs with both maximal contrast enhancement effects for both OBI and MRI simultaneously owing to the dilemma in the size of UCNPs. UCNPs in large dimensions contain more photonic Ln ions and less surface defects, which is favored for high luminescent emissions, while small UCNPs with high specific surface areas allow a higher proportion of paramagnetic Ln ions to be more accessible to water molecules, which offers enhanced contrast in MRI. In this work, we report the novel design of core−porous shell UCNPs with both high luminescent emissions and magnetic relaxivities as potential dual-modal contrast agents. The core–porous shell UCNPs were fabricated via the selective etching of the inert shell of NaYF4: 30%Gd at the active core of NaYF4: 20%Yb, 1%Er. Their morphology and composition were carefully characterized using transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy, X-ray diffraction, and high resolution TEM. Their photoluminescent and magnetic resonance properties were experimentally determined and compared for the core, core–dense shell, and core–porous shell UCNPs. Core–porous shell UCNPs were found to display bright luminescence and superior MRI contrast enhancement, thus showing great potential as bimodal OBI and MRI contrast agents.

Laser Ablation–Inductively Coupled Plasma–Mass Spectrometry Imaging in Biology

“…The combination of LA-ICP-MS with CT or MRI provides several advantages in clinical and research applications, connecting in vivo experiments and highly resolved quantitative data. Nanoparticles and metal-complexed contrasting agents are promising innovative materials to improve diagnostic imaging 253 and are suitable for multimodal imaging with LA-ICP-MS to monitor their distribution and fate. Pugh et al 356 studied the distribution of Gd-based MRI contrasting agents and novel Gdtagged liposome nanoparticles in pig brains and investigated synergies of both techniques.…”

“…Little is known about their uptake, biodistribution, accumulation, and toxicological effects. Previous methods to evaluate in vivo and in vitro behavior of NPs were performed using a variety of techniques including transmission electron microscopy (TEM), X-ray spectroscopy, and X-ray diffraction. − ICP-MS and LA-ICP-MS have the potential to provide a new perspective on the characterization, fate, and toxicology of nanomaterials. Quantitative high spatial resolution LA-ICP-MS has been applied to the analysis of various nanomaterials including AuNPs, AgNPs, doped Fe-oxide particles, and SeCd/ZnS quantum dots .…”

Metrology of convex-shaped nanoparticles via soft classification machine learning of TEM images

“…The sample consists of NaGdF 4 :49%Yb,1%Tm upconversion nanoparticles (UCNPs). UCNPs capable of converting near-infrared excitation into UV and visible emissions are becoming a sought-after optical nanomaterial for use in biomedical fields including deep-tissue optical bio-imaging 47 , multiple imaging modalities 48 , and photothermal/dynamic treatment 49,50 Since the quantum yield is intrinsically low, careful control of the UCNPs morphology, including shape (and size), is critical to their photonic, electronic and magnetic properties.…”

Analysis of Ti- and Pb-based particles in the aqueous environment of Melbourne (Australia) via single particle ICP-MS

“…As new scientific and industrial applications for NMs have emerged in the last century, the production of engineered NMs has increased. Research applications include dedicated drug delivery systems [ 5 ], diagnostic imaging [ 6 , 7 ] and therapeutic agents [ 5 ]. Industrial applications range from electronics, alternative energy sources [ 8 ], agriculture [ 9 ], coatings and paints [ 10 ].…”