ArticleScientific reports2017
Non-invasive quantitative imaging of hepatocellular carcinoma growth in mice by micro-CT using liver-targeted iodinated nano-emulsions.
Article in Scientific reports, 2017. 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
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
11 citing papers in PubMed.
- New strategies for tumor diagnosis and therapy with ultrasound assisted by nanomaterials.Ultrasonics sonochemistry · 2025Review
- Lipid-nanoparticle-enabled nucleic acid therapeutics for liver disorders.Acta pharmaceutica Sinica. B · 2024Review
- Advances of Nanotechnology in the Diagnosis and Treatment of Hepatocellular Carcinoma.Journal of clinical medicine · 2023Review
- Ultrahigh resolution whole body photon counting computed tomography as a novel versatile tool for translational research from mouse to man.Zeitschrift fur medizinische Physik · 2023Article
- Review
- Ultrasound and nanomaterial: an efficient pair to fight cancer.Journal of nanobiotechnology · 2022Review
- Antitumor effects of cadmium against diethylnitrosamine-induced liver tumors in mice.Oncology letters · 2022Article
- Tracking Dynamics of Spontaneous Tumors in Mice Using Photon-Counting Computed Tomography.iScience · 2019Article
- Ultrasound-Guided Approaches to Improve Orthotopic Mouse Xenograft Models for Hepatocellular Carcinoma.Current protocols in mouse biology · 2019Article
- Development of Severe Combined Immunodeficient (SCID) Pig Models for Translational Cancer Modeling: Future Insights on How Humanized SCID Pigs Can Improve Preclinical Cancer Research.Frontiers in oncology · 2018Article
- Longitudinal Imaging of Liver Cancer Using MicroCT and Nanoparticle Contrast Agents in CRISPR/Cas9-Induced Liver Cancer Mouse Model.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is the only cancer for which non-invasive diagnosis is recognized by international guidelines. Contrast agent free ultrasound imaging, computed tomography (CT) and/or magnetic resonance imaging are techniques used for early detection and confirmation. Clinical evidence depicts that CT is 30% less precise as compared to MRI for detection of small tumors. In our work, we have reported some novel tools that can enhance the sensitivity and precision of CT applied to preclinical research (micro-CT). Our system, containing non-toxic nano-droplets loaded with iodine has high contrasting properties, liver and hepatocyte specificity and strong liver persistence. Micro-CT was performed on HCC model implanted in nude mice by intrahepatic injection. Contrast agent was administrated intravenously. This method allows an unprecedented high precision of detection, quantitative measurement of tumor volume and quantitative follow-up of the tumor development.
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.