Magnetic Resonance Spectroscopy in Epilepsy: Clinical Issues
Bibliographic record
Abstract
Summary: Proton magnetic resonance spectroscopy (MRS) studies have shown focal reductions of N‐acetyl aspartate (NAA) signal in patients with different forms of temporal lobe epilepsy (TLE), including those with normal magnetic resonance imaging (MRI), as well as extratemporal partial epilepsies. Both single‐voxel and multivoxel 1H‐MRS have high sensitivity for detecting low NAA, indicative of neuronal dysfunction in focal epilepsies. Decreases in NAA correlate strongly with EEG abnormalities and severity of cell loss, and may be a more sensitive measure than structural MRI. However, the NAA decrease is often more widespread than the epileptogenic focus. The results of published MRS studies suggest that in patients with partial epilepsy, there is a metabolic abnormality throughout the brain, with patterns of asymmetry and focal accentuation that are useful for noninvasive localization of epileptogenic foci. A major limitation of current proton MRS studies in epilepsy is the inability to cover the entire brain in a single acquisition, thus leading to major sampling bias. The area of maximal abnormality may reside farther away, even when there is an abnormality inside of the volume of interest used for that particular examination. Decreased NAA ratios are present even in children at the onset of their epilepsy, and evidence points to a gradual and progressive course of further reduction in NAA values. Conversely, the relative NAA concentration can recover ipsilaterally and contralaterally after successful resection of a temporal lobe focus. These observations, together with the fact of the often widespread NAA abnormality, must be taken into account for the correct and adequate interpretation of proton MRS studies in the assessment of partial epilepsies.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".