E-065 MRA vs DSA in the follow-up imaging of endovascularly treated intracranial aneurysms, a meta analysis
Bibliographic record
Abstract
Introduction Endovascular treatment of intracranial aneurysms has evolved significantly, and includes coil occlusion, with or without stent-assistance, as well as parent-vessel reconstruction using flow-diverting stents. Treated aneurysms must be followed over time to ensure durable occlusion, as more than 20% of endovascularly treated aneurysms have recurrence, with up to 9% requiring re-treatment. While digital subtraction angiography (DSA) remains the gold standard, magnetic resonance angiography (MRA) has been utilized in the follow-up of endovascularly treated cerebral aneurysms as it is a non-invasive technique. Two different MRA techniques have traditionally been utilized: time-of-flight (TOF), and contrast-enhanced (CE) MRA. We systematically reviewed the literature comparing MRA techniques to DSA for the follow-up of aneurysms undergoing endovascular treatment. Methods Comprehensive searches utilizing the Embase, PubMed, and Cochrane databases were performed, and updated to December, 2017. Acquired studies were screened for appropriateness for inclusion in the meta-analysis. We included studies that compared an MRA technique with DSA for follow-up of aneurysms treated with endovascular means, and provided sufficient data for comparative evaluation of occlusion status. Studies were graded on methodological quality using the GRADE criteria. Data were analysed using the Meta-DiSc software. Pooled sensitivity and specificity, with 95% confidence intervals (CI) were calculated using aneurysm occlusion status as defined by the Raymond-Roy occlusion grading scale. Aneurysms were classified as either being occluded, having residual neck filling, or residual dome filling. Subgroup analyses for study design (prospective vs retrospective), study quality (GRADE assessment), type of treatment, DSA technique, and MRI magnet strength, were performed. Results The literature search yielded 1575 unique titles. Seventy-five titles were included in a full-text review, and after application of inclusion criteria, 40 studies were included in the meta-analysis. The GRADE assessment showed that the studies were of a good quality overall, with 22 studies (54%) scoring 4, 15 (37%) scoring 3, 3 (7%) scoring 2, while 1 (2%) study scored 1. For TOF-MRA, sensitivity and specificity of all aneurysms undergoing endovascular therapy were 0.89 (95% CI: 0.86–0.9) and 0.94 (0.93–0.95), respectively. For CE-MRA, the sensitivity and specificity were 0.91 (0.88–0.94) and 0.96 (0.94–0.97), respectively. Treatment modality subgroup analysis was performed using a coiling group and a group containing all studies with intracranial stent use. For aneurysms with intracranial stent placement, sensitivity and specificity were 0.92 and 0.98 respectively for TOF-MRA, and 0.94 and 0.99 for CE-MRA. Retrospective studies had higher sensitivity and specificity when compared to prospective studies (TOF: 0.93/0.97 vs 0.83/0.92; CE: 0.93/0.99 vs 0.87/0.92, respectively). Subgroup analyses did not reveal significant differences in the sensitivity and specificity of MRA techniques with respect to 2D vs 3D DSA, or MRA magnet strength. Conclusions MRA remains a reliable modality for the follow-up of aneurysms treated using endovascular means. Adjunctive use of intracranial stents does not significantly impede the diagnostic reliability of MRA techniques for detection of residual aneurysms. While most aneurysms can safely be followed using MRA techniques, patient and aneurysm-specific factors must be taken into account when planning follow-up for treated intracranial aneurysms. Disclosures S. Ahmed: None. X. Zheng: None. M. Kelly: 2; C; Penumbra, Medtronic. J. Mocco: 2; C; Rebound Medical, Endostream, Synchron, Cerebrotech. 4; C; Apama, The Stroke Project, Endostream, Synchron, Cerebrotech, NeurVana, NeuroTechnology Investors. R. De Leacy: 1; C; Asahi Intec, Medtronic. 2; C; Penumbra, Siemens.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.054 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".