Is the Hypointensity in Motor Cortex the Hallmark of Amyotrophic Lateral Sclerosis?
Bibliographic record
Abstract
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a devastating disease that targets motor neurons. Upper motor neurons degeneration is pathologically characterized by brain iron accumulation. Signal attenuation in the shape of a ribbon at the posterior border of the precentral gyrus can be observed on conventional magnetic resonance imaging (MRI) sequences including T2-weighted sequence. METHODS: With the aim to know the qualities of this potential marker of ALS, we conducted a prospective study. Patients with definite ALS in the age range of 40-70 years and healthy controls underwent 3T brain MRI using a standardized sequence. A second MRI was performed 18 months later under the same conditions in the patients with ALS. RESULTS: Most of the patients with ALS (91.66%) exhibited a "black ribbon" (BR) with an average area of 79.98 mm3. Signal attenuation discriminated ALS with a mean value of 63.97 arbitrary units (AU) on the left BR (95% CI: 60.67-67.27), a mean value of 59.15 AU (95% CI: 54.78-63.53) on the right BR, and a significant difference with control subjects presenting a mean value of 107.85 AU (p < 0.001). The optimal cut-off point for differentiating patients with ALS from controls (sensitivity, 0.92; specificity, 0.93) was 83 AU. Forced vital capacity and muscle strength in the contralateral upper extremity were significantly correlated with the ribbon intensity in ALS. Patients who underwent a second study exhibited significant changes in the BR related to the rapid evolution of the disease. CONCLUSIONS: This marker represents a valuable tool for the selection of candidates and their follow-up in clinical trials.
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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 | 0.002 |
| 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) | 0.002 | 0.001 |
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".