Advantages of a dual-tracer model over reference tissue models for binding potential measurement in tumors
Bibliographic record
Abstract
The quantification of tumor molecular expression in vivo could have a significant impact for informing and monitoring emerging targeted therapies in oncology. Molecular imaging of targeted tracers can be used to quantify receptor expression in the form of a binding potential (BP) if the arterial input curve or a surrogate of it is also measured. However, the assumptions of the most common approaches (reference tissue models) may not be valid for use in tumors. In this study, the validity of reference tissue models is investigated for use in tumors experimentally and in simulations. Three different tumor lines were grown subcutaneously in athymic mice and the mice were injected with a mixture of an epidermal growth factor receptor-targeted fluorescent tracer and an untargeted fluorescent tracer. A one-compartment plasma input model demonstrated that the transport kinetics of both tracers was significantly different between tumors and all potential reference tissues, and using the reference tissue model resulted in a theoretical underestimation in BP of 50% ± 37%. On the other hand, the targeted and untargeted tracers demonstrated similar transport kinetics, allowing a dual-tracer approach to be employed to accurately estimate BP (with a theoretical error of 0.23% ± 9.07%). These findings highlight the potential for using a dual-tracer approach to quantify receptor expression in tumors with abnormal hemodynamics, possibly to inform the choice or progress of molecular cancer therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".