Comparison of Time-Resolved and First-Pass Contrast-Enhanced MR Angiography in Pretherapeutic Evaluation of Spinal Dural Arteriovenous Fistulas
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Different MRA techniques used to evaluate spinal dural arteriovenous fistulas offer unique advantages and limitations with regards to temporal and spatial resolution. The purpose of this study was to compare the efficacy and interobserver agreement of 2 commonly used contrast-enhanced spinal MRA techniques, multiphase time-resolved MRA and single-phase first-pass MRA, in assessment of spinal dural arteriovenous fistulas. MATERIALS AND METHODS: Retrospective review of 15 time-resolved and 31 first-pass MRA studies in patients with clinical suspicion of spinal dural arteriovenous fistula was performed by 2 independent, blinded observers. DSA was used as the reference standard to compare the diagnostic performance of the 2 techniques. RESULTS: There were 10 cases of spinal dural arteriovenous fistula in the time-resolved MRA group and 20 in the first-pass MRA group. Time-resolved MRA detected spinal dural arteriovenous fistulas with sensitivity and specificity of 100% and 80%, respectively, with 100% correct-level localization rate. First-pass MRA detected spinal dural arteriovenous fistulas with sensitivity and specificity of 100% and 82%, respectively, with 87% correct-level localization rate. Interobserver agreement for localization was excellent for both techniques; however, it was higher for time-resolved MRA. In 5 cases, the site of fistula was not included in the FOV, but a prominent intradural radicular vein was observed at the edge of the FOV. CONCLUSIONS: Multiphase time-resolved MRA and single-phase first-pass MRA were comparable in diagnosis and localization of spinal dural arteriovenous fistulas and demonstrated excellent interobserver agreement, though there were more instances of ambiguity in fistula localization on first-pass MRA.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".