ArticleTheranostics2020
Noninvasive quantification of target availability during therapy using paired-agent fluorescence tomography.
Article in Theranostics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 10 citations in OpenAlex.
- SMK-002 inhibits the growth of bladder cancer cells and increases their sensitivity to OsimertinibThe Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2026Article
- Dynamic Tracking ofMolecular pharmaceutics · 2025Article
- Dual-channel pulse-dye densitometry can enable correction of fluorescent targeted and control agent plasma input function differences for quantitative paired-agent molecular imaging: a simulation study.Journal of biomedical optics · 2025Article
- Measurement of specific and nonspecific tissue uptake of antibodies in tumor by SPECT imaging and nonlinear compartmental modeling.EJNMMI research · 2025Article
- Quantitative pharmacokinetic and biodistribution studies for fluorescent imaging agents.Biomedical optics express · 2024Article
- Improved Discrimination of Tumors with Low and Heterogeneous EGFR Expression in Fluorescence-Guided Surgery Through Paired-Agent Protocols.Molecular imaging and biology · 2023Article
- Identification of a Suitable Untargeted Agent for the Clinical Translation of ABY-029 Paired-Agent Imaging in Fluorescence-Guided Surgery.Molecular imaging and biology · 2023Article
- Examining the Feasibility of Quantifying Receptor Availability Using Cross-Modality Paired-Agent Imaging.Molecular imaging and biology · 2022Article
- Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics.Frontiers in medicine · 2022Review
- Monitoring cancer cell surface receptor expression during anti-angiogenesis therapy in vivo.Proceedings of SPIE--the International Society for Optical Engineering · 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
7 authors at 2 institutions in 1 country.
Funding
Abstract
Immuno-oncological treatment strategies that target abnormal receptor profiles of tumors are an increasingly important feature of cancer therapy. Yet, assessing receptor availability (RA) and drug-target engagement, important determinants of therapeutic efficacy, is challenging with current imaging strategies, largely due to the complex nonspecific uptake behavior of imaging agents in tumors. Herein, we evaluate whether a quantitative noninvasive imaging approach designed to compensate for nonspecific uptake, MRI-coupled paired-agent fluorescence tomography (MRI-PAFT), is capable of rapidly assessing the availability of epidermal growth factor receptor (EGFR) in response to one dose of anti-EGFR antibody therapy in orthotopic brain tumor models.
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.