ReviewNanomedicine (London, England)2025
Nanomedicine and clinical diagnostics part I: applications in conventional imaging (MRI, X-ray/CT, and ultrasound).
Review in Nanomedicine (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
7 citing papers in PubMed.
- Nanotechnology in Pediatric Neurology: Applications and Innovations.Pharmaceutics · 2026Review
- Smart Nanomedicines for Neurodegenerative Diseases: Empowering New Therapies with Molecular Imaging and Artificial Intelligence.Molecular diagnosis & therapy · 2026Review
- New strategies for tumor diagnosis and therapy with ultrasound assisted by nanomaterials.Ultrasonics sonochemistry · 2025Review
- Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration.Frontiers in medicine · 2025Review
- Revolutionizing healthcare: the transformative potential of nanotechnology in medicine.Frontiers in drug delivery · 2025Review
- Artificial intelligence in imaging for liver disease diagnosis.Frontiers in medicine · 2025Review
- Lipid functionalized silver-coated carbon dot-capped manganese ferrite as drug-free core-shell nanoparticles for multimodal imaging and therapy.ADMET & DMPK · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrating nanotechnologies in diagnostic imaging presents a promising step forward compared to traditional methods, which carry certain limitations. Conventional imaging routes, such as X-ray/computed tomography and magnetic resonance imaging, derive significant advantages from nanoparticles (NPs), which allow researchers and clinicians to overcome some of the limitations of traditional imaging agents. In this literature review, we explore recent advancements in nanomaterials being applied in conventional diagnostic imaging techniques by exploring relevant reviews and original research papers (e.g. experimental models and theoretical model studies) in the literature. Collectively, there are numerous nanomaterials currently being examined for use in conventional imaging modalities, and each imaging technique has unique NPs with properties that can be manipulated to answer an array of clinical questions specific to that imaging modality. There are still challenges to consider, including getting regulatory approval for clinical research and routine use about long-term biocompatibility, which collectively emphasize the need for continued research to facilitate the integration of nanotechnology into routine clinical practice. Most importantly, there is a continued need for strong, collaborative efforts between researchers, biomedical engineers, clinicians, and industry stakeholders, which are necessary to bridge the persistent gap between translational ideas and implementation in clinical settings.
Indexed as
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What OpenQuestion holds
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 OpenQuestion graph.