α‐[<sup>11</sup>C]methyl‐L‐tryptophan uptake in patients with periventricular nodular heterotopia and epilepsy
Bibliographic record
Abstract
BACKGROUND: Alpha-[11C]methyl-L-tryptophan (alpha-MTrp) positron emission tomography (PET) is a promising tool in the localization of the epileptogenic area in selected group of focal epilepsy patients. Electrophysiological evidence suggests the involvement of the neocortex in periventricular nodular heterotopia (PVNH). PURPOSE: To determine whether alpha-MTrp PET can detect neocortical changes in patients with PVNH. METHODS: Four patients (2 male, mean age 28, range 23-35 years) with PVNH and intractable seizures were studied. The functional image in each patient was compared with those from 21 healthy controls (mean age 34.6 +/- 14.2 years) by using statistical parametric mapping (SPM). The location of increased alpha-MTrp uptake was compared with the location of the EEG focus. A significant cluster was defined as a cluster with a height p = 0.005 and an extent threshold 100. RESULTS: Alpha-MTrp PET revealed increased cortical uptake in two of four patients. The area of increased alpha-MTrp uptake in one patient was widespread. In the other patient, the area of increased uptake did not include the region where most seizures were generated on EEG. alpha-MTrp PET did not show increased uptake in the heterotopic nodules in any of the patients. CONCLUSIONS: Alpha-MTrp PET suggests abnormal metabolism of tryptophan in the neocortex. The increased uptake may be diffuse and may not co-localize with the EEG focus. This preliminary study suggests that alpha-MTrp PET may be useful, in conjunction with other evaluations, in localizing epileptic focus in patients with PVNH and refractory seizures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".