Ivy Sign in Moyamoya Disease: A Comparative Study of the FLAIR Vascular Hyperintensity Sign Against Contrast-Enhanced MRI
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The ability of the ivy sign on contrast-enhanced T1-weighted MR imaging (CEMR) to reflect cerebral perfusion and postoperative revascularization in Moyamoya disease remains largely unknown. We aimed to compare the capabilities of CEMR and FLAIR. MATERIALS AND METHODS: CEMR, FLAIR, arterial spin-labeling, and DSA were performed in 44 patients with Moyamoya disease. The ivy sign was scored separately on CEMR and FLAIR using the Alberta Stroke Program Early CT Score. The status of leptomeningeal collaterals was scored on DSA. The postoperative Matsushima grade was evaluated at least 3 months after surgical revascularization. RESULTS: Scoring of the ivy sign on CEMR showed excellent interrater reliability, and FLAIR vascular hyperintensity showed moderate interrater reliability. Correlation analyses revealed that DSA scores were more consistent with the CEMR-based ivy sign score (r = 0.25, P = .03) than with FLAIR vascular hyperintensity (r = 0.05, P = .65). The CEMR-based ivy sign score was significantly correlated with CBF in late-Suzuki stage Moyamoya disease (t = −2.64, P = .02). The CEMR-based ivy sign score at baseline was significantly correlated with the postoperative Matsushima grade (r = 0.48, P = .03). CONCLUSIONS: In this study, CEMR outperformed FLAIR in capturing the ivy sign in Moyamoya disease. In addition, the CEMR-based ivy sign score provided adequate information on hemodynamic status and postoperative neovascularization. The current study suggested that CEMR could be considered as an alternative to FLAIR in future studies investigating leptomeningeal collaterals in Moyamoya disease.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".