A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on Behalf of the Stakeholder Taskforce for Artificial Intelligence–Assisted Robotic Thrombectomy (START)

Although we are making progress in overcoming infectious diseases and cancer, one of the major medical challenges of the mid-21st century will be the increasing prevalence of stroke. Occlusions in large vessels are especially debilitating, yet effective treatment—needed within hours to achieve best outcomes—remains limited because of geographic accessibility. One solution for improving timely access to mechanical thrombectomy in geographically diverse populations is the widespread deployment of robotic surgical systems. Artificial intelligence assistance may enable the safe and effective upskilling of operators in this emerging therapeutic delivery approach. Our aim was to establish consensus frameworks for developing and validating artificial intelligence–assisted robots for thrombectomy. Objectives included standardizing effectiveness metrics and defining reference testbeds across in silico, in vitro, ex vivo, and in vivo environments. To achieve this, we convened experts in neurointervention, robotics, data science, health economics, policy, statistics, and patient advocacy. Consensus was built through an incubator day, a Delphi process, and a final position statement. We identified that the 4 essential testbed environments each had distinct validation roles. Realism requirements vary: simpler testbeds should include realistic vessel anatomy compatible with guidewire and catheter use, whereas standard testbeds should incorporate deformable vessels. More advanced testbeds should include blood flow, pulsatility, and disease features, such as atheromatous plaques. There are 2 macroclasses of effectiveness metrics: one for in silico, in vitro, and ex vivo stages focusing on technical navigation (eg, path-following error), and another for in vivo stages, focused on clinical outcomes (eg, modified treatment in cerebral infarction scores). Patient safety is central, and not a barrier, to this technology's development. One requisite patient safety task needed now is to correlate in vitro measurements to in vivo complications.

Contributors

Harry Robertshaw, Anna Barnes, Phil Blakelock, Raphael Blanc, Robert Crossley, Rebecca Fahrig, Ameer E Hassan, Benjamin Jackson, Lennart Karstensen, Neelam Kaur, Markus Kowarschik, Jeremy Lynch, Franziska Mathis-Ullrich, Dwight Meglan, Vitor Mendes Pereira, Mouloud Ourak, Matteo Pantano, S M Hadi Sadati, Alice Taylor-Gee, Tom Vercauteren, Phil White, Alejandro Granados, Thomas C Booth, START

Publication

Journal: Journal of the American Heart Association
Volume: 15
Issue: 7
Pages: -
Year: 2026
DOI: https://doi.org/10.1161/JAHA.125.044931

Further Study Information

Current Stage: Completed
Date:
Funding source(s): This work was supported by the MRC IAA 2021 Kings College London (MR/X502923/1) and the Wellcome EPSRC Centre for Medical Engineering at King's College London (203?148/Z/16/Z).


Health Area

Disease Category: Neurology

Disease Name: Ischemic stroke

Target Population

Age Range: 0 - 100

Sex: Either

Nature of Intervention: Surgery

Stakeholders Involved

- Academic research representatives
- Clinical experts
- Patient/ support group representatives
- Pharmaceutical industry representatives

Study Type

- Recommendations made

Method(s)

- Delphi process

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