Review of the anatomy of the distal anterior cerebral artery and its anomalies
Bibliographic record
Abstract
The anterior cerebral artery (ACA) varies considerably and this complicates the description of the normal anatomy. The segmentation of the ACA is mostly agreed on by different authors, although the relationship of the pericallosal and callosomarginal arteries (CmA) is not agreed upon. The two basic configurations of the ACA are determined by the presence or absence of the CmA. The diameter, length and origin of the cortical branches have been measured and described by various authors and display great variability. Common anomalies of the ACA include the azygos, bihemispheric, and median anterior cerebral arteries. A pilot study was done on 19 hemispheres to assess the variation of the branches of the ACA. The most common variations included absence and duplication. The inferior internal parietal artery and the CmA were most commonly absent and the paracentral lobule artery was the most frequently duplicated (36.8%). The inferior internal parietal artery originated from the posterior cerebral artery in 40.0% and this was the most unusual origin observed. It is important to be aware of the possibility of variations since these variations can have serious clinical implications. The knowledge of these variations can be helpful to clinicians and neurosurgeons. The aim of this article is to review the anatomy and variations of the anterior cerebral artery, as described in the literature. This was also compared to the results from a pilot study.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".