Fluorodeoxyglucose and Methionine Uptake in Lhermitte-Duclos Disease: Case Report
Bibliographic record
Abstract
OBJECTIVE AND IMPORTANCE: Lhermitte-Duclos disease (LDD) represents a focally indolent dysplastic growth of the cerebellar cortex. The 106 cases reported previously in the literature show an extremely slow evolution, and the operative indications and techniques for this disease entity are still controversial. The authors present the first case of LDD studied with positron emission tomography using the labeled tracers [(18)F]2-fluoro-2-deoxy-d-glucose ([(18)F]FDG) and (11)C-labeled methionine ([(11)C]Met) to study the glucose and protein metabolism of the lesion. CLINICAL PRESENTATION: A 40-year-old woman suddenly became unconscious then completely recovered 5 minutes later. Magnetic resonance imaging of her brain showed a well-delineated 10 x 5-cm abnormal area with enlarged cerebellar folia, which led to the diagnosis of LDD. TECHNIQUE: On positron emission tomographic scans, [(18)F]FDG and [(11)C]Met uptake in the normal cerebral and cerebellar cortex appeared higher than normal, reaching levels found in patients with primary malignant brain tumors. Moreover, the uptake of both tracers was heterogeneous, in contrast to the homogeneous uptake visualized on magnetic resonance imaging scans. The areas of greatest [(11)C]Met and [(18)F]FDG uptake were discordant. Some areas of greater than normal [(18)F]FDG uptake corresponded to areas of moderate or low [(11)C]Met uptake. Because of the important mass effect in the posterior fossa, total surgical resection was performed. A histological examination confirmed the diagnosis of LDD. CONCLUSION: This first reported metabolic study of LDD supports the view that LDD is an active and evolving disease. These data should prompt reevaluation of the indications for surgery in patients with this disease as well as the timing of surgery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".