Positron Emission Tomography in Imaging Spinal Cord Tumors
Bibliographic record
Abstract
The ability of positron emission tomography (PET) to detect spinal cord tumors was studied prospectively in 14 patients presenting over a 5-year period. Abnormal uptake by [18F]-fluorodeoxyglucose (FDG) or 11C-methionine was detected in all except one. These data were assessed in relation to magnetic resonance imaging (MRI) findings with regard to tumor type and extent preoperatively, findings at operation, and subsequent clinical course. The group consisted of six astrocytomas, five ependymomas, one mixed ependymoma and astrocytoma, one schwannoma, and one ganglioglioma, all confirmed histologically. This is the largest study comparing spinal PET to MRI. Accurate preoperative correlation between PET and MRI was found in all eight patients scanned at first presentation. The PET uptake was in keeping with the low-grade histology of the tumors. Postoperatively, PET and MRI findings were in agreement in nine patients. In eight of these the findings were in keeping with the subsequent clinical course. In three patients, however, the PET findings were at variance with the clinical course and MRI findings. In one, persistent FDG uptake after radiotherapy was seen where there was subsequent tumor resolution. In two patients with low-grade astrocytomas, scanned with FDG and 11C-methionine, respectively, tracer was not taken up by residual tumor. In this small group of patients, PET did not provide additional useful information. This could be because all tumors studied were low grade and the limited spatial resolution of PET does not lend itself to imaging small spinal cord tumors. The prospective study of larger numbers of patients with a wider range of tumor types is required, but this might be difficult to achieve given the rarity of spinal cord tumors.
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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".