Added Value of High-Resolution MR Imaging in the Diagnosis of Vertebral Artery Dissection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The optimal imaging method for the diagnosis of VAD remains undefined. Our aim was to evaluate the added value of HR-MR imaging for the diagnosis of VAD. MATERIALS AND METHODS: We retrospectively extracted 35 consecutive patients suspected of having acute VAD who had the following: 1) a focal lumen abnormality of the VA on CE-MRA, 2) HR-MR imaging during the initial hospital stay, and 3) clinical and imaging follow-up within 6 months. Two neurologists classified patients as either VAD (group A) or non-VAD (group B) by reviewing all the available data at hospital discharge, except HR-MR imaging data. On HR-MR imaging, 2 radiologists searched for signs of acute VAD. The 2 classifications were compared. In case of discordance, CE-MRA follow-up and axial fat-suppressed T1WI, used to obtain supportive evidence for or against VAD, were considered as the standard of reference. RESULTS: In 4/18 patients in group A, HR-MR imaging did not demonstrate any signs of acute VAD and perivertebral signal-intensity changes were attributed to venous plexus, with an unchanged lumen on follow-up. In 4/17 patients in group B, HR-MRI demonstrated a mural hematoma, with lumen normalization on follow-up CE-MRA. CONCLUSIONS: Our results encourage the use of HR-MR imaging as a second-line diagnostic tool in the event of suspicion of acute VAD and doubtful findings on standard imaging.
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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