First-Pass Contrast-Enhanced MR Angiography in Evaluation of Treated Spinal Arteriovenous Fistulas: Is Catheter Angiography Necessary?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Catheter angiography is typically used for follow-up of treated spinal AVFs. The purpose of this study was to determine the diagnostic performance and utility of first-pass contrast-enhanced MRA in the posttreatment evaluation of spinal AVFs compared with DSA. MATERIALS AND METHODS: A retrospective review was performed of all patients at our tertiary referral hospital (from January 2000 to April 2015) who underwent spine MR imaging, first-pass contrast-enhanced MRA, and DSA after surgical and/or endovascular treatment of a spinal AVF. Presence of recurrent or residual fistula on MRA, including vertebral level of the recurrent/residual fistula, was evaluated by 2 experienced neuroradiologists blinded to DSA findings. Posttreatment conventional MR imaging findings were also evaluated, including presence of intramedullary T2 hyperintensity, perimedullary serpentine flow voids, and cord enhancement. The performance of MRA and MR imaging findings for diagnosis of recurrent/residual fistula was determined by using DSA as the criterion standard. RESULTS: In total, 28 posttreatment paired MR imaging/MRA and DSA studies were evaluated in 22 patients with prior spinal AVF and 1 patient with intracranial AVF with prior cervical perimedullary venous drainage. Six image sets of 5 patients demonstrated recurrent/residual disease at DSA. MRA correctly identified all cases with recurrent/residual disease with 1 false-positive (sensitivity, 100%; specificity 95%; P < .001), with correct localization in all cases without interobserver disagreement. Conventional MR imaging parameters were not significantly associated with recurrent/residual spinal AVF. CONCLUSIONS: First-pass MRA demonstrates high sensitivity and specificity for identifying recurrent/residual spinal AVFs and may potentially substitute for DSA in the posttreatment follow-up of patients with spinal AVFs.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 | 0.001 |
| 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".