Feasibility of robot-assisted neuroendovascular procedures
Bibliographic record
Abstract
OBJECTIVE: Geographic factors prevent equitable access to urgent advanced neuroendovascular treatments. Robotic technologies may enable remote endovascular procedures in the future. The authors performed a translational, benchtop-to-clinical study to evaluate the in vitro and clinical feasibility of the CorPath GRX Robotic System for robot-assisted endovascular neurointerventional procedures. METHODS: A series of bench studies was conducted using patient-specific 3D-printed models to test the system's compatibility with standard neurointerventional devices, including microcatheters, microwires, coils, intrasaccular devices, and stents. Optimal baseline setups for various procedures were determined. The models were further used to rehearse clinical cases. Subsequent to these investigations, a prospective series of 6 patients was treated using robotic assistance for complex, wide-necked intracranial saccular aneurysms between November 2019 and February 2020. The technical success, incidence of periprocedural complications, and need for conversion to manual procedures were evaluated. RESULTS: The ideal robotic setup for treatment of both anterior and posterior circulation aneurysms was determined to consist of an 80-cm guide catheter with a 115-cm-long intermediate catheter, a microcatheter between 150 and 170 cm in length, and a microwire with a minimum length of 300 cm. All coils, intrasaccular devices, and stents tested were compatible with the system and could be advanced or retracted safely and placed accurately. All 6 clinical procedures were technically successful, with all intracranial steps being performed robotically with no conversions to manual intervention or failures of the robotic system. There were no procedure-related complications or adverse clinical outcomes. CONCLUSIONS: This study demonstrates the feasibility of robot-assisted neurointerventional procedures. The authors' results represent an important step toward enabling remote neuroendovascular care and geographic equalization of advanced endovascular treatments through so-called telestroke intervention.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".