Susceptibility weighted imaging for qualitative grading of persistent arteriovenous shunting in deep-seated arteriovenous malformations after stereotactic radiation surgery
Bibliographic record
Abstract
Background and purpose To investigate Susceptibility Weighted Imaging (SWI) signal changes in the draining vein of deep-seated arterio-venous malformations (AVMs) following stereotactic radiosurgery (SRS). Methods and Materials This is a retrospective study of 32 patients with deep-seated AVMs who were treated with SRS. Pre-SRS treatment and post-SRS treatment MRI were performed at 6, 12, and 24-month intervals. Deep-seated AVMs were classified based on their anatomical location and venous drainage pattern. AVM nidal volume (cm 3 ) was estimated using the ABC/2 method. AV shunting of the AVM draining veins were graded according to its SWI signal intensity: hyperintense (grade III), mixed signal intensity (grade II), hypointense (grade I) and absent (grade 0). Conventional time-of-flight (TOF)-MRA and contrast enhanced (CE)-MRA sequences were performed to document the patency of the vein. Results Pre-SRS treatment AVM draining veins were either grade III 18/32 (56%) or grade II 14/32 (44%). Using mixed effects analysis, we demonstrate that each month following the SRS treatment nidal volumes decreased at the rate of 0.51 cm 3 /per month (CI −0.61 to (−0.40)) p =.00. Following the treatment, there was a clinically significant relationship between the signal and nidal volume: signal 0 corresponded with average nidal volume of 1.81 cm 3 (CI 1.40–2.21), signal 1 with nidal volume of 2.06 cm 3 (CI 1.69–2.44), signal 2 with nidal volume 2.73 cm 3 (CI 2.35–3.11) and signal 3 with nidal volume 3.13 cm 3 (CI 2.70–3.56) p = .00. Conclusion Post-SRS AVM draining veins shows a stepwise regression of the SWI signal grades which can be reliably used as a surrogate to monitor the reduction of AV shunting.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".