INSPIRATION: Image-based aspiration catheter sizing in acute ischemic stroke
Stroke caused by a blocked blood vessel in the brain is a major medical emergency that requires fast and precise treatment. The INSPIRATION project brings together hospitals, academic researchers, and industry partners in a new public-private collaboration to improve stroke treatment outcomes. The project focuses on supporting doctors during thrombectomy procedures by developing a digital decision-support tool that helps them choose the most suitable aspiration catheter size for each individual patient, using information from routine CT scans.
Stroke is one of the leading causes of death and long-term disability worldwide. In the Netherlands alone, tens of thousands of people suffer a stroke each year, and many survivors require long-term care or admission to nursing homes. A key goal of stroke treatment is to reopen the blocked blood vessel in one attempt, known as first-pass recanalization, as this strongly improves recovery. However, current success rates remain moderate. Innovation is needed because doctors must choose from an increasing number of medical devices under extreme time pressure, and a suboptimal choice can reduce treatment success, increase complications, and raise healthcare costs.
INSPIRATION addresses this challenge by using advanced image analysis and artificial intelligence to extract relevant information from standard CT scans, such as blood vessel size, shape, and clot characteristics. By combining patient-specific anatomy with knowledge from large clinical databases, scientific literature, simulations, and laboratory testing, the project will identify risk factors for unsuccessful thrombectomy and translate them into practical recommendations. The result is an easy-to-use tool that supports clinicians in selecting the optimal aspiration catheter size for each patient.
The project will deliver validated AI-based image analysis algorithms, quantified risk profiles for thrombectomy failure, and a clinically tested decision-support platform. Together, these outcomes are expected to improve first-pass recanalization rates by 5–20%, reduce long-term disability, lower healthcare costs, and improve quality of life for patients and their families.
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