F-18-FDG and C-11-Choline Positron Emission Tomography in Human Esophago-Gastric Cancer: Prediction of Response to Therapy
Bibliographic record
Abstract
Background: To determine the utility of F-18-FDG and C-11-Choline uptake, in patients with esophageal and esophago-gastric junction tumors who are to undergo either neo-adjuvant or palliative chemotherapy, in predicting response (pathological and survival). Methods: Eighteen patients with biopsy proven cancer were recruited prospectively. Patients underwent PET imaging before and during the first cycl e of chemotherapy (seven and 14 days) with both F-18-FDG and C-11-Choline. Tracer uptake was quantified using Standardized Uptake Values. Pathological tumor response was determined using the Mandard criteria. Cellular proliferation was determined using ki-67 immunohistochemistry. Relationships between tracer uptake and response, one-year survival and cellular proliferation were determined. Results: All 18 tumors were imaged by F-18-FDG PET compared to 16/18 with C-11-Choline. Change in uptake of either tracer did not correlate with pathological response. Pathological response did not influence survival (median-survival, responders = 16.1 months; non-responders = 19.0 months, p = 0.978). There was no significant correlation of change in tracer uptake with survival. C-11-Choline tumor uptake did not correlate with cellular proliferation. Conclusion: F-18-FDG PET is superior for imaging of the primary tumor. Neither F-18-FDG nor C-11-Choline PET was able to predict response accurately. Â World J Oncol. 2010;1(2):66-67 doi: https://doi.org/10.4021/wjon2010.04.201w Â
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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 | 0.001 | 0.001 |
| 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".