ReviewNuclear medicine and molecular imaging2020
Preclinical Voxel-Based Dosimetry in Theranostics: a Review.
Review in Nuclear medicine and molecular imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Utility of Preclinical Dosimetry for First-in-Human Studies with PET Drugs Labeled with Common Radionuclides: A Systematic Review of Radiation Dose Estimates.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026Pooled it
- Personalised Dosimetry in Nuclear Medicine: Bridging Physics, Biology and AI for Next Generation Radiopharmaceutical Therapy.Nuclear medicine and molecular imaging · 2026Review
- A Scoping Review of the Challenges and Future Perspectives in the Use of Alpha-Emitters for Metastatic Ovarian Cancer.Molecules (Basel, Switzerland) · 2026Article
- The evolution of surrogate microspheres in transarterial radioembolization: from SPECT prediction to multimodal AI-guided precision dosimetry.Theranostics · 2026Review
- S-values for bone marrow dosimetry in preclinical radiopharmaceutical studies with rodents.EJNMMI physics · 2025Article
- The heterobivalent (SSTR2/albumin) radioligand [Theranostics · 2024Article
- Aspects and prospects of preclinical theranostic radiopharmaceutical development.Theranostics · 2024Review
- An Overview of In Vitro Assays ofDiagnostics (Basel, Switzerland) · 2023Review
- Article
- A Review on Tumor Control Probability (TCP) and Preclinical Dosimetry in Targeted Radionuclide Therapy (TRT).Pharmaceutics · 2022Review
- Review
- A Brief History of Nuclear Medicine Physics, Instrumentation, and Data Sciences in Korea.Nuclear medicine and molecular imaging · 2021Review
- High through-plane resolution CT imaging with self-supervised deep learning.Physics in medicine and biology · 2021Article
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
Due to the increasing use of preclinical targeted radionuclide therapy (TRT) studies for the development of novel theranostic agents, several studies have been performed to accurately estimate absorbed doses to mice at the voxel level using reference mouse phantoms and Monte Carlo (MC) simulations. Accurate dosimetry is important in preclinical theranostics to interpret radiobiological dose-response relationships and to translate results for clinical use. Direct MC (DMC) simulation is believed to produce more realistic voxel-level dose distribution with high precision because tissue heterogeneities and nonuniform source distributions in patients or animals are considered. Although MC simulation is considered to be an accurate method for voxel-based absorbed dose calculations, it is time-consuming, computationally demanding, and often impractical in daily practice. In this review, we focus on the current status of voxel-based dosimetry methods applied in preclinical theranostics and discuss the need for accurate and fast voxel-based dosimetry methods for pretherapy absorbed dose calculations to optimize the dose computation time in preclinical TRT.
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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.