MR Quantification of Flow in Children with Vein of Galen Malformations
Bibliographic record
Abstract
SUMMARY: Vein of Galen vascular malformations are either Vein of Galen Aneurysmal malformations (VGAMs) or Vein of Galen Aneurysmal Dilatations (VGADs). VGAMs may be of the choroidal or mural type and are fistulas associated with the precursor of the vein of Galen. The treatment of VGAMs is aimed at controlling the size of the vascular shunt since it is believed that the shunt is responsible for venous hypertension, cardiac stress, delayed development and may be so large as to damage the brain. In VGAMs as noted by Berenstein and Lasjaunias. Absolute measures of flow may contribute to our understanding of CNS disease and permit objective measures of the success or failure of therapeutic interventions (5). MR phase contrast cine angiographic techniques can be employed to measure bulk flow in intracranial vessels. Vein of Galen vascular malformations are an ideal model to measure venous flow as the draining vein is large and angiographic evaluation is limited. Thus our goal was to develop an objective non-invasive method of measuring vascular flow in VGAMs and VGADs (6) . Herein we report our experience using this technique in a group of patients with Vein of Galen vascular malformations. We also hypothesized that the degree of shunting would correlate to the degree of cardiac stress and be an indicator of optimal timing for intervention. We believe that we have succeeded in our goal to develop an objective, non-invasive method of shunt quantification using velocity encoded MR sequences. This promises new insight into the hemodynamics, natural history and treatment response of vascular malformations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".