A Genetically Encoded Magnetic Resonance Imaging Reporter Enables Sensitive Detection and Tracking of Spontaneous Metastases in Deep Tissues
Bibliographic record
Abstract
Metastasis is the leading cause of cancer-related death. However, it remains a poorly understood aspect of cancer biology, and most preclinical cancer studies do not examine metastasis, focusing solely on the primary tumor. One major factor contributing to this paradox is a gap in available tools for accurate spatiotemporal measurements of metastatic spread in vivo. Here, our objective was to develop an imaging reporter system that offers sensitive three-dimensional (3D) detection of cancer cells at high resolutions in live mice. An organic anion-transporting polypeptide 1b3 (oatp1b3) was used as an MRI reporter gene, and its sensitivity was systematically optimized for in vivo tracking of viable cancer cells in a spontaneous metastasis model. Metastases with oatp1b3-MRI could be observed at the single lymph node level and tracked over time as cancer cells spread to multiple lymph nodes and different organ systems in individual animals. While initial single lesions were successfully imaged in parallel via bioluminescence, later metastases were largely obscured by light scatter from the initial node. Importantly, MRI could detect micrometastases in lung tissue comprised on the order of 1,000 cancer cells. In summary, oatp1b3-MRI enables longitudinal tracking of cancer cells with combined high resolution and high sensitivity that provides 3D spatial information and the surrounding anatomical context. SIGNIFICANCE: An MRI reporter gene system optimized for tracking metastasis in deep tissues at high resolutions and able to detect spontaneous micrometastases in lungs of mice provides a useful tool for metastasis research.
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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) | 0.000 | 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) | 0.001 | 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".