Improving Stroke Care in North-Norway Through Artificial Intelligence

University Hospital of North Norway

Status: Enrolling

Conditions: Ischemic Stroke

Treatments: Device: AI software StrokeSens (Circle NVI)

Study type: Interventional

Funder types: Other

Identifiers

NCT05903898

2022/24698(REK)

Details and patient eligibility

About

Prospective observational multi-center intervention study. The study aims to evaluate whether an artificial intelligence (AI) support tool for radiological image processing (StrokeSens, Circle NVI) can accelerate decision making and increase detection rate in patients with an acute ischemic stroke caused by intracranial large vessel occlusion (LVO) or medium vessel occlusion (MeVO) in Northern Norway. Relevant outcomes will be compared between centres with and without available software during the study period.

Full description

This study aims to evaluate whether an AI support tool (StrokeSens, Circle NVI) can accelerate decision making and increase detection rate in patients with an acute ischemic stroke caused by intracranial large vessel occlusion (LVO) or medium vessel occlusion (MeVO) in Northern Norway. The software will be a decision support tool in addition to standard radiological services where image interpretation is done by a radiologist or resident in radiology. The AI-tool will be available in 5 of 10 primary hospitals in Northern Norway. The AI-software employed in this study can automatically evaluate the presence of ischemic changes in the vascular territory of the middle cerebral artery according to the Alberta Stroke Program Early CT Score (ASPECTS) and detect occlusions in the intracranial segment of the internal carotid artery and the proximal segments of the middle cerebral artery (MCA).

The main goal of this project is to evaluate if access to the AI-software:

Accelerates identification and handling of stroke patients harbouring an intracranial LVO. Leads to a higher detection rate of anterior circulation LVO and MeVO.

The secondary goal is to evaluate:

If AI software leads to a higher number of thrombectomy treated LVO and MeVo patients. If AI software may lead to improved patient outcomes.

Hypothesis: Implementation of AI-based image analysis software as a decision support tool for radiologists, reduces time from imaging to transfer request in patients harbouring LVO/MeVO, and increases detection rate of large and medium sized vessel intracranial occlusion compared to the present day practices in primary stroke centres within the health region.

All outcomes will be a compared between primary stroke centres with and without access to the AI-software and historical data from the same sites as collected prior to software implementation (2019-2022).

Enrollment: 1,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients with acute stroke symptoms admitted to a participating hospital within 24 hours of symptom onset

Exclusion criteria

• Patients not available for follow-up assessments (e.g. non-resident)

Trial design

Primary purpose: Diagnostic

Allocation: Non-Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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1,000 participants in 2 patient groups

Patients enrolled to a primary stroke center with access to AI-software image processing tool

Experimental group

Description:

Patients enrolled to a primary stroke center with access to AI-software image processing tool to aid the radiologist in LVO and MeVO detection.

Treatment:

Device: AI software StrokeSens (Circle NVI)

Patients enrolled to a primary stroke center without access to AI-software image processing tool

No Intervention group

Description:

Patients enrolled to a primary stroke center without access to AI-software image processing tool to aid the radiologist in LVO and MeVO detection (standard care).