MATRIX

The MATRIX project, part of the PP CONTRAST programme, aims to develop a machine learning approach to predict thrombus composition from CT and CT angiography (CTA) imaging. Preprocedural insight into thrombus characteristics enables more personalised device selection. This may improve recanaliSation success and patient outcomes.

Acute ischaemic stroke is caused by the occlusion of a cerebral artery by a thrombus. Thrombus composition varies in the relative proportions of red blood cells, fibrin, and platelets. Fibrin-rich thrombi are generally more compact and resistant to treatment, whereas red blood cell–rich thrombi are typically softer and easier to retrieve. Endovascular thrombectomy (EVT) is the standard treatment for large vessel occlusions, but its success depends in part on thrombus composition. In particular, achieving first-pass recanalisation is strongly associated with improved clinical outcomes, yet remains challenging for certain thrombus types. Currently, no reliable non-invasive method exists to determine thrombus composition prior to intervention, limiting the ability to tailor treatment strategies. 

PP CONTRAST - Health~Holland

In Public-Private CONTRAST (COllaboration for Novel Technologies foR Acute STroke), funded by Health~Holland, Erasmus MC, Amsterdam UMC and TU Delft (on behalf of the CONTRAST consortium and Technical Universities) together with private partners will develop innovative approaches for the diagnosis, characterisation, and treatment of patients with a stroke, by developing and implementing novel technologies, such as AI and advanced digital twins.

Stroke is a significant societal problem: one out of four in the Netherlands will get a stroke, leading to large societal and healthcare costs. Stroke is the most frequent cause of remaining disability in adults. The well-known phrase 'Time is brain' emphasises the benefit of swift treatment for the patient, the healthcare system, and society: Starting treatment one hour earlier leads to an average reduction of healthcare expenditures of €18,000 per patient.

PP CONTRAST develops technologies for improving and expediting the diagnosis, such as detection of an intracranial bleeding in the ambulance, and characterising blood vessel occlusions based on imaging data before treatment. By allowing the improved selection of treatment devices based on patient-specific vessel structures, automated multi-modal analysis of images during the intervention, and patient-specific blood pressure regulation, as well as patient-specific treatment simulation on digital twin platforms, PP CONTRAST contributes to improving treatment of stroke patients resulting in better outcomes.

brings together multiple innovative projects under the shared vision of improving stroke care. With strong public-private partnerships at the core, this initiative connects researchers, industry partners, and stakeholders to accelerate technological breakthroughs that impact stroke care.