Skip to content
Home » Aim


Neurological diseases are amongst the most challenging and expensive diseases around us. Strokes are by far the most significant and expensive for society. In the last decades, there was momentous progress in the understanding and treatment of stroke. This led to the introduction of the most effective novel treatments in the whole field of medicine. Firstly, the thrombectomy for intracranial large vessel occlusion stroke and secondly, endovascular treatment of intracranial aneurysms (IAs).

However, we might hit a block regarding treatment advancement, as large parts of previous improvements are based on:

(1) treatment on a population level as the results of clinical trials, and

(2) decades of research with animal models.

Although they are valuable approaches, they do not cover the patient-specific and multifaceted aspects of stroke (e.g., comorbidities, multi-organ involvement, the initiation of the stroke, the subacute progression of the diseases). But these are required to advance the field of stroke prevention, diagnosis, treatment, and monitoring, and improve patient care. Medical professionals currently lack patient-specific decision-making tools and well-established models that can accurately assist in the diagnosis and stratification of stroke patients for tailored treatments and device choice.

Personalised computational modelling provides a viable, promising, and clinically required approach to improve patient management. On top of that, personalised computational modelling will address other (clinical) needs regarding stroke. For example, fragmented knowledge from different medical specialties, evidence obtained in selected populations in protected environments, simplistic mono-organ disease models, and interdependencies between factors that are now considered independent.