Optimizing Acute Ischemic Stroke Diagnostics Using Artificial Intelligence

NCT05652933 | Unknown

• 1 other identifier: 282961
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 3

Brief Summary

Prospective observational multi-center study with the aim to organise and simplify the care pathway through a pragmatic approach to acute stroke imaging powered by cutting edge advances in image processing and artificial intelligence.

Conditions

Stroke, Acute

Outcome Measures

Primary Outcomes (1)

• Time from the start of CT scan of patients at the local hospital to radiological diagnosis in acute stroke patients with large and medium vessel occlusion in periods with the use of AI software compared to periods with standard care.

  Minutes

  Day 0

Secondary Outcomes (6)

• Time from the start of CT scan of patients at the local hospital to start of thrombectomy in patients identified with large and medium vessel occlusion in periods with the use of AI software compared to periods with standard care.

  Day 0

• Time from symptom onset to start of thrombectomy in patients identified with LVO large and medium vessel occlusion in periods with the use of AI software compared with proportion of patients identified with LVO and MeVO diagnosed by standard care.

  Day 0

• Proportion of patients identified with large and medium vessel occlusion in periods with the use of AI software compared with proportion of patients identified with large and medium vessel occlusion diagnosed by standard care.

  Day 0

• Proportion of patients treated with thrombectomy in large and medium vessel occlusion in periods with the use of AI software compared with proportion of patients identified with large and medium vessel occlusion diagnosed by standard care.

  Day 0

• Functional outcome at 90 days after EVT in stroke patients who had their initial radiological diagnosis using AI-based image analysis tools compared to stroke patients diagnosed by standard care.

  90 days

Interventions

Software for identifying vessel occlusion, infarct volume and penumbra DIAGNOSTIC_TEST

Assessment of the AI tool software

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients admitted with acute ischemic stroke at participating hospitals

You may qualify if:

• Patients with ischemic stroke.
• All stroke severities and vascular distributions are eligible.

You may not qualify if:

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

Sponsors & Collaborators

• Oslo University Hospital: lead
• Vestre Viken Hospital Trust: collaborator
• University Hospital of North Norway: collaborator
• University of Calgary: collaborator

Study Sites (3)

Vestre Viken Hospital Trust

Drammen, Norway

RECRUITING

Oslo University Hospital

Oslo, Norway

RECRUITING

Østfold Hospital Trust

Sarpsborg, Norway

RECRUITING

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 3 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Coordinating Investigator

Study Record Dates

• First Submitted: February 22, 2022
• First Posted: December 15, 2022
• Study Start: December 10, 2021
• Primary Completion: March 15, 2025
• Study Completion: December 31, 2025
• Last Updated: October 17, 2023

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share

Locations

NO (3)