ArticleAustin journal of biomedical engineering2014
Comparison of Kinetic Models for Dual-Tracer Receptor Concentration Imaging in Tumors.
Article in Austin journal of biomedical engineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 19 citations in OpenAlex.
- Mapping estimates of vascular permeability with a clinical indocyanine green fluorescence imaging system in experimental pancreatic adenocarcinoma tumors.Journal of biomedical optics · 2023Article
- Prediction of optimal contrast times post-imaging agent administration to inform personalized fluorescence-guided surgery.Journal of biomedical optics · 2020Article
- Fluorescence imaging reversion using spatially variant deconvolution.Scientific reports · 2019Article
- Paired-agent imaging for detection of head and neck cancers.Proceedings of SPIE--the International Society for Optical Engineering · 2019Article
- Correcting for targeted and control agent signal differences in paired-agent molecular imaging of cancer cell-surface receptors.Journal of biomedical optics · 2018Article
- Ratiometric optical nanoprobes enable accurate molecular detection and imaging.Chemical Society reviews · 2018Review
- Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging.Biomedical optics express · 2018Article
- Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions.Physics in medicine and biology · 2017Article
- In vivo quantifying molecular specificity of Cy5.5-labeled cyclic 9-mer peptide probe with dynamic fluorescence imaging.Biomedical optics express · 2016Article
- Residualization Rates of Near-Infrared Dyes for the Rational Design of Molecular Imaging Agents.Molecular imaging and biology · 2015Article
- Quantitative in vivo cell-surface receptor imaging in oncology: kinetic modeling and paired-agent principles from nuclear medicine and optical imaging.Physics in medicine and biology · 2015Review
- Quantification of the binding potential of cell-surface receptors in fresh excised specimens via dual-probe modeling of SERS nanoparticles.Scientific reports · 2015Article
- Microscopic lymph node tumor burden quantified by macroscopic dual-tracer molecular imaging.Nature medicine · 2014Article
- Pixel-based absorption correction for dual-tracer fluorescence imaging of receptor binding potential.Biomedical optics express · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Molecular differences between cancerous and healthy tissue have become key targets for novel therapeutics specific to tumor receptors. However, cancer cell receptor expression can vary within and amongst different tumors, making strategies that can quantify receptor concentration
Identifiers
25414912PMC4235770W2182482451What 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.