Morphology and variations of middle cerebral artery: systematic review and meta-analysis
Bibliographic record
Abstract
To review morphometry, morphology, branching patterns and anomalies of middle cerebral artery (MCA).The databases of PubMed, Google Scholar and Scopus were searched with different keywords.The review comprised of 45 studies.Meta-analysis was done for dimensions of MCA, shapes, patterns and MCA anomalies.Newcastle-Ottawa Scale was used for assessment of literature.Statistical analysis was done using R software using meta package.Thirteen research were combined to determine the proportion of MCA length and pooled proportion was 16.53 cm (15.33 to 17.72 cm); I 2 =98%; P-value<0.01.Nine studies were combined to determine proportion of MCA diameter and pooled proportion was 2.85 cm (2.52 to 3.17 cm); I 2 =100%; P-value<0.05.M1 segment mean length is more on left side as compared to right side.Mean length in males (16.57±1.40cm) is more than females (15.9±1.32 cm).Mean diameter of M1 segment is similar on both sides.Mean diameter in males (3.20±0.09cm) is higher than females (3.14±0.18cm).Different branching patterns observed were single trunk, early bifurcation, bifurcation, trifurcation, quadrifurcation and multiple trunks.The most typical MCA branching pattern is bifurcation.The shapes of MCA like straight shaped, U shaped, C shaped, inverted U shaped and S-shaped of M1 segment have been described.Straight MCA is the most common shape.The MCA measurements and branching pattern will assist surgeons in limiting errors in the treatment of cerebral aneurysms and infarcts and providing the best possible result for the patients.An understanding of MCA shape will aid surgeons and physicians in effective endovascular recanalization.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.017 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".