Imaging Features of Primary and Recurrent Esophageal Cancer at FDG PET
Bibliographic record
Abstract
Because of the poor prognosis for patients with esophageal cancer and the risks associated with surgical intervention, accurate staging is essential for optimal treatment planning. Positron emission tomography (PET) with 2-[fluorine-18]fluoro-2-deoxy-d-glucose (FDG) is a useful adjunct to more conventional imaging modalities in this setting. FDG PET is not an appropriate first-line diagnostic procedure in the detection of esophageal cancer and is not helpful in detecting local invasion by the primary tumor, and further studies are required to determine its efficacy in the detection of local nodal metastases. However, FDG PET is superior to anatomic imaging modalities in the ability to detect distant metastases. Metastases to the liver, lungs, and skeleton can readily be identified at FDG PET. In addition, FDG PET has proved valuable in determining the resectability of disease and allows scanning of a larger volume than is possible with computed tomography. Recurrent disease is readily diagnosed and differentiated from scar tissue with FDG PET. In addition, FDG PET may play a valuable role in the follow-up of patients who undergo chemotherapy and radiation therapy, allowing early changes in treatment for unresponsive tumors. The management of most patients with esophageal cancer can be improved with use of FDG PET.
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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".