A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on behalf of the Stakeholder Taskforce for AI-assisted Robotic Thrombectomy (START)

2026-03-30

AI Summary

This study addresses the time-sensitive nature and geographic disparities in treating large-vessel occlusion stroke by proposing a systematic validation framework for AI-assisted robotic thrombectomy. Integrating expertise from neurointervention, robotics, data science, and health policy, the research employs a Delphi method and expert consensus workshops to formally define, for the first time, the roles and fidelity requirements of four-tiered testing platforms—in silico, in vitro, ex vivo, and in vivo—and to distinguish between technical navigation performance and clinical outcome as dual validity metrics. The project culminates in an authoritative position statement that delineates critical elements and safety validation priorities across developmental stages, thereby establishing a standardized pathway for the clinical translation of AI-enhanced thrombectomy robots.

Abstract

While we are making progress in overcoming infectious diseases and cancer; one of the major medical challenges of the mid-21st century will be the rising prevalence of stroke. Large vessels occlusions are especially debilitating, yet effective treatment (needed within hours to achieve best outcomes) remains limited due to geography. One solution for improving timely access to mechanical thrombectomy in geographically diverse populations is the deployment of robotic surgical systems. Artificial intelligence (AI) assistance may enable the upskilling of operators in this emerging therapeutic delivery approach. Our aim was to establish consensus frameworks for developing and validating AI-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 four essential testbed environments each had distinct validation roles. Realism requirements vary: simpler testbeds should include realistic vessel anatomy compatible with guidewire and catheter use, while standard testbeds should incorporate deformable vessels. More advanced testbeds should include blood flow, pulsatility, and disease features. There are two macro-classes of effectiveness metrics: one for in silico, in vitro, and ex vivo stages focusing on technical navigation, and another for in vivo stages, focused on clinical outcomes. Patient safety is central to this technology's development. One requisite patient safety task needed now is to correlate in vitro measurements to in vivo complications.

Problem

• mechanical thrombectomy
• AI-assisted robotics
• effectiveness metrics
• endovascular models
• stroke treatment accessibility

Innovation

• AI-assisted robotics
• mechanical thrombectomy
• validation frameworks
• effectiveness metrics
• testbed standardization