ReviewInternational journal of nanomedicine2023
IONPs-Based Medical Imaging in Cancer Care: Moving Beyond Traditional Diagnosis and Therapeutic Assessment.
Review in International journal of nanomedicine, 2023. 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.
- AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation.Radiology. Imaging cancer · 2026Article
- Sustainable nanomaterials for precision dental medicine: green synthesis, therapeutic applications, and future directions.Journal of nanobiotechnology · 2026Review
- Theranostic Potentials of Metallic Nanoparticles in Thyroid Diseases: Challenges and Prospects.International journal of nanomedicine · 2026Review
- Magnetic Hyperthermia with Iron Oxide Nanoparticles: From Toxicity Challenges to Cancer Applications.Nanomaterials (Basel, Switzerland) · 2025Review
- Advancements in Nano-Mandoor Bhasma: Unravelling the Particle Size-Ascorbic Acid Synergy for Enhanced Iron Bioavailability for Anemia Treatment.Biological trace element research · 2025Article
- Nanotheranostics: A Cutting-edge Technology for Cancer Management.Current pharmaceutical biotechnology · 2025Review
- Iron Oxide Nanoparticle-Based TNanomaterials (Basel, Switzerland) · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer-related burden of morbidity and mortality is rapidly rising worldwide. Medical imaging plays an important role in every phase of cancer management, including diagnosis, staging, treatment planning and evaluation. Iron oxide nanoparticles (IONPs) could serve as contrast agents or labeling agents to enhance the identification and visualization of pathological tissues as well as target cells. Multimodal or multifunctional imaging can be easily acquired by modifying IONPs with other imaging agents or functional groups, allowing the accessibility of combined imaging techniques and providing more comprehensive information for cancer care. To date, IONPs-enhanced medical imaging has gained intensive application in early diagnosis, monitoring treatment as well as guiding radio-frequency ablation, sentinel lymph node dissection, radiotherapy and hyperthermia therapy. Besides, IONPs mediated imaging is also capable of promoting the development of anti-cancer nanomedicines through identifying patients potentially sensitive to nanotherapeutics. Based on versatile imaging modes and application fields, this review highlights and summarizes recent research advances of IONPs-based medical imaging in cancer management. Besides, currently existing challenges are also discussed to provide perspectives and advices for the future development of IONPs-based imaging in cancer management.
Indexed as
Identifiers
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.