Novel approach in neurovascular navigation: Artiria Medical SmartGUIDE deflectable tip microwire
Bibliographic record
Abstract
Neurointerventionalists increasingly treat distal vascular targets with complex anatomy. Current guidewires require iterative hand shaping of the tip to navigate microcatheters and devices. Manual shaping often necessitates wire removal and reinsertion, risking wire damage, longer procedural times, increased vessel injury, and higher costs. The Artiria Medical SmartGUIDE 1 enables real time in situ tip deflection, allowing a single wire to reach a wide range of targets without manual reshaping. It can be locked in position to anchor microcatheters at branch points and prevent buckling or herniation, obviating the need for ancillary support devices, such as a balloon or metallic mesh. The wire can also shape and steer microcatheters on demand by torquing from within, potentially reducing risky maneuvers, such as looping within an aneurysm dome. We demonstrate the use of the deflectable Artiria Medical SmartGUIDE microwire in navigating through tortuous ophthalmic artery branches to perform preoperative embolization of highly vascular orbital tumor (video 1). We provide a comprehensive up to date comparison to other real-time steerable devices.2 3 4 5 6 7neurintsurg;jnis-2025-023947v1/V1F1V1Video 1-Artiria Medical SmartGUIDE 0.014'' Deflectable-Tip Microwire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".