ArticleSmall (Weinheim an der Bergstrasse, Germany)2024
Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs.
Article in Small (Weinheim an der Bergstrasse, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Tailoring inter-core distance of clustered SPIONs using silica spacers for enhanced magnetic particle imaging (MPI).Nanoscale · 2026Article
- Biosafety of micron-sized FeJournal of thoracic disease · 2026Article
- The Development and Challenges of PET/MRI Dual-Modality Imaging Probes-An Update.Journal of magnetic resonance imaging : JMRI · 2025Review
- TriMag Microrobots: 3D-Printed Microrobots for Magnetic Actuation, Imaging, and Hyperthermia.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Microfluidic formulation and characterization of size-tunable microparticle magnetic particle imaging tracers.Journal of magnetism and magnetic materials · 2025Article
- Spillover can limit accurate signal quantification in MPI.Npj imaging · 2025Article
- Advances in engineering nanoparticles for magnetic particle imaging (MPI).Science advances · 2025Review
- Machine Learning and Deep Learning Applications in Magnetic Particle Imaging.Journal of magnetic resonance imaging : JMRI · 2025Review
- Pulsed MPI Relaxometry of Brownian and Néel Field-Dependent Relaxation in Superparamagnetic Magnetite Nanoparticles Confirm Theory and Simulations.Small (Weinheim an der Bergstrasse, Germany) · 2024Article
- Post-synthesis Oxidation of Superparamagnetic Iron Oxide Nanoparticles to Enhance Magnetic Particle Imaging Performance.ACS applied nano materials · 2024Article
- The Application of Nanovaccines in Autoimmune Diseases.International journal of nanomedicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.