Long-Term Prospective Follow-Up of Intracranial Aneurysms Treated with Endovascular Coiling Using Contrast-Enhanced MR Angiography
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Catheter angiography has been the criterion standard for follow-up evaluation of coiled intracranial aneurysms. In our center, CE-MRA has been used to evaluate aneurysm recanalization. Our aim was to investigate the feasibility and usefulness of a CE-MRA protocol for following patients with intracranial aneurysms treated with endovascular coiling. MATERIALS AND METHODS: From September 2003 to December 2006, 134 aneurysms were treated by endovascular coiling in 124 patients by using detachable coils. These patients were followed with CE-MRA at 3 months, 15 months, and 3 and 5 years. MRAs were analyzed by 2 interventional neuroradiologists. Findings were assigned to 3 categories: complete obliteration (class 1), residual neck (class 2), and residual aneurysm (class 3). RESULTS: Initially, CE-MRA demonstrated 67 (50%) complete obliterations (class 1), 57 (41.79%) residual necks (class 2), and 8 (5.97%) residual aneurysms (class 3). No patient experienced rebleed during the follow-up period. A total of 214 patient-years of follow-up were obtained (range, 0-53 months). Two (1.49%) patients died after the follow-up, and 11 (8.21%) patients were lost to follow-up. On follow-up, 76 (56.72%) patients showed stable results. Fifty-six (41.79%) aneurysms showed change in their obliteration pattern. Of these 56, 47 demonstrated recanalization and 9 (6.72%) showed further obliteration. Most of the aneurysms that showed change in their obliteration remained stable on follow-up. Only 11 (8.21% of the total and 23.4% of those who showed recanalization) patients underwent recoiling or clipping. CONCLUSIONS: CE-MRA can be used in routine practice to follow-up aneurysm recanalization noninvasively. CE-MRA permits close-interval follow-up and may show more filling of the aneurysm neck or sac than DSA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".