SU‐GG‐J‐109: Inhomogeneities of Intratumoral FDG Uptake in Human Colon Adenocarcinoma HT29 Tumor Model
Bibliographic record
Abstract
Purpose: It has been shown previously that in rat prostate carcinoma tumor R3327‐AT the highest uptake of 18‐FDG in tumors was observed in the areas of hypoxia rather than the areas of increased blood flow or active cell proliferation. In the present study we investigated the pattern of intratumoral FDG uptake in human colon adenocarcinoma cell line HT29. Method and Materials: Three nude rats were inoculated with HT29 cells. When the tumors reached 25mm in diameter, the animals were injected with 18‐FDG, pimonidazole, and bromodeoxyuridine (BrdU). 1hr later injection animals were injected with Hoechst33342 and sacrificed. Tumors were immediately dissected, frozen and sectioned. One section from each tumor was placed onto a phosphor plate for autoradiography. The images of the fluorescence produced by Hoechst33342 and by fluorescent antibodies raised against pimonidazole and BrdU were acquired from the adjacent sections and co‐registered. Results: All tumors in the study had extensive necrosis well intermixed with viable tumor tissue. Typically, hypoxia was forming bands about 100μm wide at the interface between viable tissue and necrosis. Analysis of the autoradiography data demonstrated associations between 18F‐FDG uptake and all of the markers studied. However, when analysis is done on the viable tumor tissue only by carefully masking out the necrotic areas, 0FDG uptake was positively correlated with staining intensity of pimonidazole and negatively correlated with Hoechst and BrdU. Conclusion: In larger tumors with complicated morphology it is necrotic fraction that plays crucial role in forming FDG uptake variations rather than any of the microenvironmental parameters considered. However, in the viable tumor tissue FDG uptake was positively correlated with staining intensity of pimonidazole and negatively correlated with Hoechst and BrdU, thus demonstrating association of increased FDG uptake with hypoxia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".