ReviewEuropean journal of nuclear medicine and molecular imaging2025
Exploring the landscape of current in vitro and in vivo models and their relevance for targeted radionuclide theranostics.
Review in European journal of nuclear medicine and molecular imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Challenges in tracer development for tumor microenvironment (TME) imaging.European journal of nuclear medicine and molecular imaging · 2026Review
- A 3D co-culture model with fibroblast-restricted FAP expression for cancer therapy using [EJNMMI radiopharmacy and chemistry · 2026Article
- Using advanced cell models for targeted radionuclide therapy evaluation: increased efficacy in 3D versus 2D.EJNMMI research · 2026Article
- Physiologically Relevant Organotypic Tissue Slice Model for Evaluating Cell Responses to Ionizing Radiation.International journal of molecular sciences · 2026Review
- Review
- Vessel-on-a-Chip to Study Vascular Endothelial Inflammation.Current protocols · 2025Article
- Compact accelerator-based production of carrier-freeEJNMMI radiopharmacy and chemistry · 2025Article
- Nature-Inspired Strategies in Cancer Management: The Potential of Plant Extracts in Modulating Tumour Biology.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Cancer remains a leading cause of mortality globally, driving ongoing research into innovative treatment strategies. Preclinical research forms the base for developing these novel treatments, using both in vitro and in vivo model systems that are, ideally, as clinically representative as possible. Emerging as a promising approach for cancer management, targeted radionuclide theranostics (TRT) uses radiotracers to deliver (cytotoxic) radionuclides specifically to cancer cells. Since the field is relatively new, more advanced preclinical models are not yet regularly applied in TRT research. This narrative review examines the currently applied in vitro, ex vivo and in vivo models for oncological research, discusses if and how these models are now applied for TRT studies, and whether not yet applied models can be of benefit for the field. A selection of different models is discussed, ranging from in vitro two-dimensional (2D) and three-dimensional (3D) cell models, including spheroids, organoids and tissue slice cultures, to in vivo mouse cancer models, such as cellline-derived models, patient-derived xenograft models and humanized models. Each of the models has advantages and limitations for studying human cancer biology, radiopharmaceutical assessment and treatment efficacy. Overall, there is a need to apply more advanced models in TRT research that better address specific TRT phenomena, such as crossfire and abscopal effects, to enhance the clinical relevance and effectiveness of preclinical TRT evaluations.
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.