Comparison of Multidetector CT Angiography and MR Imaging of Cervical Artery Dissection
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Conventional angiography has been historically considered the gold standard for the diagnosis of cervical artery dissection, but MR imaging/MR angiography (MRA) and CT/CT angiography (CTA) are commonly used noninvasive alternatives. The goal of this study was to compare the ability of multidetector CT/CTA and MR imaging/MRA to detect common imaging findings of dissection. MATERIALS AND METHODS: Patients in the data base of our Stroke Center between 2003 and 2007 with dissections who had CT/CTA and MR imaging/MRA on initial work-up were reviewed retrospectively. Two neuroradiologists evaluated the images for associated findings of dissection, including acute ischemic stroke, luminal narrowing, vessel irregularity, wall thickening/hematoma, pseudoaneurysm, and intimal flap. The readers also subjectively rated each vessel on the basis of whether the imaging findings were more clearly displayed with CT/CTA or MR imaging/MRA or were equally apparent. RESULTS: Eighteen patients with 25 dissected vessels (15 internal carotid arteries [ICA] and 10 vertebral arteries [VA]) met the inclusion criteria. CT/CTA identified more intimal flaps, pseudoaneurysms, and high-grade stenoses than MR imaging/MRA. CT/CTA was preferred for diagnosis in 13 vessels (5 ICA, 8 VA), whereas MR imaging/MRA was preferred in 1 vessel (ICA). The 2 techniques were deemed equal in the remaining 11 vessels (9 ICA, 2 VA). A significant preference for CT/CTA was noted for VA dissections (P < .05), but not for ICA dissections. CONCLUSION: Multidetector CT/CTA visualized more features of cervical artery dissection than MR imaging/MRA. CT/CTA was subjectively favored for vertebral dissection, whereas there was no technique preference for ICA dissection. In many cases, MR imaging/MRA provided complementary or confirmatory information, particularly given its better depiction of ischemic complications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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