Cranial Dural Arteriovenous Fistula: Diagnosis and Classification with Time-Resolved MR Angiography at 3T
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The diagnosis of dural arteriovenous fistula (DAVF) remains one of the few uncontested indications for catheter based cerebral angiography. We report our experience of using a commercially available form of time-resolved MR angiography (trMRA) at 3T for the diagnosis and classification of a cranial DAVF compared with the reference standard of digital subtraction angiography (DSA). MATERIALS AND METHODS: A retrospective review of our patient records identified patients who had undergone trMRA at 3T and DSA for the evaluation of DAVF. The trMRA consisted of whole-head, contrast-enhanced "time-resolved imaging of contrast kinetics" (TRICKS) MRA. Image sets were independently reviewed by 3 readers for the presence, location, and classification of a DAVF. The reported result of the DSA was used as the gold standard against which the performance of the trMRA was measured. RESULTS: Forty patients were identified who had undergone DSA and trMRA for evaluation of DAVF, yielding a total of 42 cases. On DSA, the results of 7 cases were normal, 15 cases were performed for surveillance of a previously cured fistula, and a new fistula (14) or persistent (6) fistula was found in 20 cases. Of these 20 fistulas, on DSA, 13 were Borden I, 2 were Borden II, and 5 were Borden III. In 93% (39/42) of DAVF cases, the 3 readers were unanimous and correct in their independent interpretation of the trMRA, correctly identifying (or excluding) all fistulas and accurately classifying them when encountered. CONCLUSIONS: In this small series, trMRA at 3T seems be a reliable technique in the screening and surveillance of DAVF in specific clinical situations.
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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 it