Pulsatility of an Intracavernous Aneurysm Demonstrated by Dynamic 320-detector Row CTA at High Temporal Resolution
Bibliographic record
Abstract
Studying the flow dynamics of intracranial aneurysms and the associated pulsatility of the aneurysm wall may help to risk-stratify unruptured aneurysms. Currently, in-vivo methods that visualize aneurysm wall movement at high temporal resolution are not yet fully established. We describe a patient with an intracavernous aneurysm in whom the area of increased aneurysm pulsatility as demonstrated by high-temporal resolution CTA was identical to the area of aneurysm growth on follow-up. A 35-year-old man presented with headaches and a sixth nerve palsy. CT including dynamic CTA demonstrated a pulsating intracavernous aneurysm. On follow-up one week later, the patient had developed hypesthesia in his V1 and V2 distribution and repeat imaging demonstrated aneurysm growth in the aneurysm part that demonstrated pulsatile movements on dynamic CTA. Stent-assisted coiling of the aneurysm was performed and led to clinical improvement. Dynamic CTA was performed using a 320-detector row CT following continuous rotational scanning during the administration of contrast with subsequent image reconstructions at 100 msec intervals. Dynamic CTA can demonstrate aneurysm pulsations that, as in the present case of a patient with a giant intracavernous aneurysm, were associated with aneurysm growth in the area of maximum pulsation. We hypothesize that this technique may predict aneurysm growth and may therefore be helpful in the non-invasive in vivo assessment of individual aneurysm features such as dome and bleb pulsations in both unruptured and ruptured aneurysms.
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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 | 0.000 | 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 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".