<i>In Vivo</i> MR Imaging of Tumor-Associated Macrophages: The Next Frontier in Cancer Imaging
Bibliographic record
Abstract
There is a complex interaction between cancer and the immune system. Tumor-associated macrophages (TAMs) can be subverted by the cancer to adopt a pro-tumor phenotype to aid tumor growth. These anti-inflammatory, pro-tumor TAMs have been shown to contribute to a worsened outcome in several different types of cancer. Various strategies aimed at combating the pro-tumor TAMs have been developed. Several therapies, such as oncolytic viral therapy and high-intensity focused ultrasound, have been shown to stimulate TAMs and suppress tumor growth. Targeting TAMs is a promising way to combat cancer, but sensitive imaging methods that are capable of detecting these therapeutic responses are needed. A promising idea is to use imaging contrast agents to label TAMs to determine their relative number and location within, and around the tumor. This can provide information about the efficacy of TAM depletion therapies, as well as macrophage-stimulating therapies. In this review, we describe various in vivo MRI methods capable of tracking TAMs, and conclude with a short section on tracking TAMs in patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".