<i>N</i> -Acetylaspartate Distribution in Proton Spectroscopic Images of Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: It is generally considered that tissue that appears abnormal on T2 MRI is already infarcted and that any penumbra lies outside the T2-visible lesion. We investigated the distribution of infarcted tissue using proton spectroscopic MRI. METHODS: In patients with symptoms of acute hemispheric ischemic stroke, imaged within a maximum of 3 days of stroke, we explored the distribution of N:-acetylaspartate (NAA), a marker of intact neurons, within and around the abnormal (hyperintense) areas on T2-weighted MR images, using proton spectroscopic MRI. RESULTS: In 11 patients, imaged 24 to 72 hours after stroke onset, there was little evidence of damaged neurons (reduced NAA) beyond the margins of hyperintensity on the T2 image. However, within the abnormal T2 area, there were statistically significant differences in the amount of NAA (ie, the proportion of intact neurons) between areas that were obviously abnormal on T2 (very hyperintense) and those that were only slightly abnormal (slightly hyperintense). CONCLUSIONS: The extent and degree of hyperintensity of the T2-visible lesion directly reflect the amount of neuronal damage; lack of a T2-visible lesion would suggest predominantly intact neurons at the time of imaging. We hypothesize that once tissue damage has reached a critical (probably irreversible) level, the T2 image quickly becomes abnormal without any significant time lag between the pathological staging of the infarct and its visualization on T2. Further testing in a larger study with information on blood flow levels would be required to confirm this.
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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".