Acute Ischemic Stroke Clinical Trial
— AI-REACTOfficial title:
AI Assisted Reader Evaluation in Acute CT Head Interpretation
Verified date | June 2024 |
Source | Oxford University Hospitals NHS Trust |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
This study has been added as a sub study to the Simulation Training for Emergency Department Imaging 2 study (ClinicalTrials.gov ID NCT05427838). The purpose of the study is to assess the impact of an Artificial Intelligence (AI) tool called qER 2.0 EU on the performance of readers, including general radiologists, emergency medicine clinicians, and radiographers, in interpreting non-contrast CT head scans. The study aims to evaluate the changes in accuracy, review time, and diagnostic confidence when using the AI tool. It also seeks to provide evidence on the diagnostic performance of the AI tool and its potential to improve efficiency and patient care in the context of the National Health Service (NHS). The study will use a dataset of 150 CT head scans, including both control cases and abnormal cases with specific abnormalities. The results of this study will inform larger follow-up studies in real-life Emergency Department (ED) settings.
Status | Active, not recruiting |
Enrollment | 33 |
Est. completion date | June 1, 2025 |
Est. primary completion date | September 1, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | N/A and older |
Eligibility | Inclusion Criteria: - Radiologists/Radiographers/ED clinicians who review CT head scans as part of their clinical practice Exclusion Criteria: - Neuroradiologists. - Non-radiologist groups: Clinicians with previous formal postgraduate CT reporting training - Emergency Medicine group: Clinicians with previous career in radiology/neurosurgery to registrar level |
Country | Name | City | State |
---|---|---|---|
United Kingdom | NHS Greater Glasgow and Clyde | Glasgow | |
United Kingdom | Guy's & St Thomas NHS Foundation Trust | London | |
United Kingdom | Northumbria Healthcare NHS Foundation Trust | Newcastle Upon Tyne | |
United Kingdom | Oxford University Hospitals NHS Foundation Trust | Oxford | Oxfordshire |
Lead Sponsor | Collaborator |
---|---|
Oxford University Hospitals NHS Trust |
United Kingdom,
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* Note: There are 21 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Reader performance: Sensitivity, specificity, comparative between with and without AI assistance. | Reader performance will be evaluated as sensitivity, specificity, with and without AI assistance. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | Reader performance: Positive and negative predictive value, comparative between with and without AI assistance. | Reader performance will be evaluated as Positive Predictive Value (PPV) and negative predictive value (NPV), with and without AI assistance. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | Reader performance: Area Under Receiver Operating Characteristic Curve (AUROC), comparative between with and without AI assistance. | Reader performance will be evaluated as Area Under Receiver Operating Characteristic Curve (AUROC), with and without AI assistance. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | Reader speed: Mean time taken to review a scan, with versus without AI assistance. | Reader speed will be evaluated as the man time taken to review a scan, using time unite of seconds. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | Reader confidence: Self-reported diagnostic confidence on a 10 point visual analogue scale, with vs without AI assistance. | On the reading platform (RAIQC), one of the questions asks the level of confidence that the participant has in their diagnostic opinion. The question offers a scale of 1 to 10, where 1 is not confident, and 10 is highly confident. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | qER (AI algorithm) performance: Sensitivity and specificity | qER performance will be evaluated as sensitivity, specificity. | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | qER (AI algorithm) performance: Positive and negative predictive value. | qER performance will be evaluated as Positive Predictive Value (PPV) and negative predictive value (NPV). | During 6 weeks, which is the period for reading or reviewing the cases/scans. | |
Primary | qER (AI algorithm) performance: Area Under Receiver Operating Characteristic Curve (AUROC). | qER performance will be evaluated as Area Under Receiver Operating Characteristic Curve (AUROC) | During 6 weeks, which is the period for reading or reviewing the cases/scans. |
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