Abstract T P169: Acute Cardioembolic vs. Large Artery Atherosclerotic Infarction-related Lesion Topography and Right-Left Propensity: A Multi-center Quantitative Magnetic Resonance Imaging Study
Bibliographic record
Abstract
Background and Purpose: A recent study showed that cardiogenic emboli might flow more frequently into the right hemisphere, whereas atheromatous aortic arch emboli might flow more frequently into the left hemisphere. We tried to 1) see if cardioembolic (CE) infarct volume would be larger in the right hemisphere than in the left hemisphere, and 2) depict anatomical regions showing CE vs. large artery atherosclerotic (LAA) infarction-related right-left propensity. Methods: In this study on carotid artery territory CE (n = 694) vs. LAA (n = 1162) acute ischemic stroke patients who were enrolled consecutively from 11 nationwide stroke centers, we quantitatively registered diffusion magnetic resonance imaging lesions onto the Montreal Neurologic Institute brain template. Results: In patients with bilateral CE stroke (n = 163), right hemispheric infarct size was about two times bigger than the contralateral left hemispheric infarct size (p = 0.002). However, in patients with either unilateral (n = 925) or bilateral (n = 184) LAA stroke, there was no significant difference in the right vs. left hemispheric infarct size between the right vs. left unilateral infarct groups or within the bilateral infarct group (all p > 0.05). In patients with unilateral CE stroke (n = 510), there was no significant difference in the infarct size between the groups with right vs. left hemispheric lesions. Age and infarct volume-adjusted p-value maps of the CE vs. LAA stroke patients, which were corrected for multiple comparisons, revealed the brain regions with a significantly higher infarct frequency in CE stroke than in LAA stroke. The significant clusters were observed only in the right hemisphere, encompassing both the superior and inferior division middle cerebral artery territories, particularly in the pial and corticosubcortical regions including the claustrum and insula. Conclusion: The present multi-center quantitative magnetic resonance imaging study confirms the ‘right > left’ propensity of CE (vs. LAA) stroke.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".