AI Assisted Reader Evaluation in Acute Computed Tomography (CT) Head Interpretation (AI-REACT)

NHS Trust

Status: Completed

Conditions: Hydrocephalus; Cerebral Edema; Cerebral Infarction; Intracranial Hemorrhages; Acute Ischemic Stroke; Cerebral Injury

Treatments: Other: Ground truthing; Other: Reading

Study type: Observational

Funder types: Other

Identifiers

NCT06018545

310995 - A

Details and patient eligibility

About

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.

Enrollment: 33 patients

Sex: All

Volunteers: Accepts Healthy Volunteers

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

Trial design

33 participants in 2 patient groups

Readers

Description:

30 readers will be recruited across four NHS trusts including ten general radiologists, fifteen emergency medicine clinicians, and five CT radiographers of varying seniority. Readers will interpret each scan first without, then with, the assistance of the AI tool, with an intervening 4-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers' performance will be analysed as change in accuracy, mean review time per scan, and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty.

Treatment:

Other: Reading

Ground truthers

Description:

Two Consultant neuroradiologists will independently review the images to establish the 'ground truth' findings on the CT scans which will be used as the reference standard. In the case of disagreement, a third senior neuroradiologist's opinion will be sought for arbitration. A difficulty score will be assigned to each scan by the ground truthers using a 5-point Likert scale.

Treatment:

Other: Ground truthing