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EUROSTARS-EUROSTARS

E!1826 AI quantification of wake-up stroke

Alternative title: E!1826 AI-kvantifisering av wake-up stroke

Awarded: NOK 1.9 mill.

Wake-up stroke - when a patient awakens with stroke symptoms - affects around 25% of stroke patients. The treatment options (thrombectomy and thrombolysis) have high efficacy for stroke, but it can only be administered within a specific time window (<4.5h-6h) after the first symptoms. For wake-up stroke the difficulty lies in assessing when the symptoms started. Currently, there are no automated tools to both analyze brain MRI scans and select wake-up stroke patients for treatment. Therefore, clinicians still rely on subjective visual assessments and time-consuming calculations. This represents uncertainties and delayed decisions, resulting in the exclusion of many patients from potential life-saving treatments We aim to develop an AI-based software solution to automatically identify wake-up stroke patients eligible for thrombectomy/thrombolysis treatment and predict treatment outcomes. The AI tool will analyze, in real-time, MRI brain scans, and more specifically ischemic brain lesions, while patients are being examined, and will automatically quantify different parameters essential for quick, robust and correct treatment decision for wake-up stroke patients.

Wake-up stroke - when a patient awakens with stroke symptoms - affects around 25% of stroke patients. The treatment options (thrombectomy and thrombolysis) have high efficacy for stroke, but it can only be administered within a specific time window (<4.5h-6h) after the first symptoms. For wake-up stroke the difficulty lies in assessing when the symptoms started. Currently, there are no automated tools to both analyze brain MRI scans and select wake-up stroke patients for treatment. Therefore, clinicians still rely on subjective visual assessments and time-consuming calculations. This represents uncertainties and delayed decisions, resulting in the exclusion of many patients from potential life-saving treatments We aim to develop an AI-based software solution to automatically identify wake-up stroke patients eligible for thrombectomy/thrombolysis treatment and predict treatment outcomes. The AI tool will analyze, in real-time, MRI brain scans, and more specifically ischemic brain lesions, while patients are being examined, and will automatically quantify different parameters essential for quick, robust and correct treatment decision for wake-up stroke patients.

Funding scheme:

EUROSTARS-EUROSTARS