Predictive Value of MRI in Diagnosing Brain AVM Recurrence after Angiographically Documented Exclusion in Children
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: MRI is routinely performed following brain AVM after treatment in children. Our aim was to determine the predictive values of contrast-enhanced MR imaging and TOF-MRA for brain AVM recurrence in children, compared with conventional angiography and the role of 3D rotational angiography–MR imaging fusion in these cases. MATERIALS AND METHODS: We included all pediatric patients with brain AVMs during an 18-year period with angiographically documented obliteration after treatment. Patients underwent 3T MR imaging, including contrast-enhanced MR imaging, TOF-MRA, and conventional angiography, with a subset undergoing 3D rotational angiography. The predictive values of contrast-enhanced MR imaging and TOF-MRA for brain AVM recurrence were determined. CTA sections reconstructed from 3D rotational angiography were coregistered with and fused to 3D-T1WI for analysis. RESULTS: Thirty-nine children (10.8 ± 3.9 years of age; range, 2–17 years; male/female ratio, 19:20; mean Spetzler-Martin grade, 1.9 ± 0.6) met the inclusion criteria. Of these, 13 had angiographically confirmed brain AVM recurrence, 8 following surgery and 5 following embolization. Sensitivity, specificity, and positive and negative predictive values for recurrence were the following: contrast-enhanced MR imaging: 84.6%, 38.5%, 40.7%, 81.8%; TOF-MRA: 50.0%, 96.1%, 85.7%, 79.3%; both: 75.0%, 90.9%, 85.7%, 83.3%. 3D rotational angiography–MR imaging fused images confirmed or excluded recurrence in all available cases (13/13). Embolization-only treatment was a significant predictor of recurrence (OR = 32.4, P = .006). MR imaging features predictive of recurrence included a tuft of vessels on TOF-MRA and nodular juxtamural/linear enhancement with a draining vein on contrast-enhanced MR imaging. CONCLUSIONS: MR imaging is useful for surveillance after brain AVM treatment in children, but conventional angiography is required for definitive diagnosis of recurrence. TOF-MRA and contrast-enhanced MR imaging provide complementary information for determining brain AVM recurrence and should be interpreted in conjunction. 3D rotational angiography–MR imaging fusion increases the diagnostic confidence regarding brain AVM recurrence and is therefore suited for intraoperative neuronavigation.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".