Trials / Completed

CompletedNCT06075836

AI Assisted Detection of Chest X-Rays

Utility of an AI-based CXR Interpretation Tool in Assisting Diagnostic Accuracy, Speed, and Confidence of Healthcare Professionals: a Study Using 500 Retrospectively Collected Inpatient and Emergency Department CXRs From Two UK Hospital Trusts

Status: Completed
Phase: —
Study type: Observational
Enrollment: 33 (actual)

Sponsor: Oxford University Hospitals NHS Trust · Academic / Other
Sex: All
Age: —
Healthy volunteers: Accepted

Summary

This study has been added as a sub study to the Simulation Training for Emergency Department Imaging 2 study (ClinicalTrials.gov ID NCT05427838). The Lunit INSIGHT CXR is a validation study that aims to assess the utility of an Artificial Intelligence-based (AI) chest X-ray (CXR) interpretation tool in assisting the diagnostic accuracy, speed, and confidence of a varied group of healthcare professionals. The study will be conducted using 500 retrospectively collected inpatient and emergency department CXRs from two United Kingdom (UK) hospital trusts. Two fellowship trained thoracic radiologists will independently review all studies to establish the ground truth reference standard. The Lunit INSIGHT CXR tool will be used to analyze each CXR, and its performance will be measured against the expert readers. The study will evaluate the utility of the algorithm in improving reader accuracy and confidence as measured by sensitivity, specificity, positive predictive value, and negative predictive value. The study will measure the performance of the algorithm against ten abnormal findings, including pulmonary nodules/mass, consolidation, pneumothorax, atelectasis, calcification, cardiomegaly, fibrosis, mediastinal widening, pleural effusion, and pneumoperitoneum. The study will involve readers from various clinical professional groups with and without the assistance of Lunit INSIGHT CXR. The study will provide evidence on the impact of AI algorithms in assisting healthcare professionals such as emergency medicine and general medicine physicians who regularly review images in their daily practice.

Conditions

Interventions

Type	Name	Description
OTHER	Cases reading	The reading will be done remotely via the Report and Image Quality Control site (www.RAIQC.com), an online platform allowing medical imaging viewing and reporting. Participants can work from any location, but the work must be done from a computer with internet access. For avoidance of doubt, the work cannot be performed from a phone or tablet. The project is divided into two phases and participants are required to complete both phases. The estimated total involvement in the project is up to 20-24 hours. Phase 1: Time allowed: 2 weeks \- Review 500 chest X-rays and express a clinical opinion through a structured reporting template (multiple choice, no open text required). Rest/washout period of 2 weeks. Phase 2 - Time allowed: 2 weeks \- Review 500 chest X-rays together with an AI report for each case and express your clinical opinion through the same structured reporting template used in Phase A.
OTHER	Ground truthing	Two consultant thoracic radiologists will independently review the images to establish the 'ground truth' findings on the CXRs, where a consensus is reached this will then be used as the reference standard. In the case of disagreement, a third senior thoracic radiologist's opinion (\>20 years experience) will undertake arbitration. A difficulty score will be assigned to each abnormality by the ground truthers using a 4-point Likert scale (1 being easy/obvious to 4 being hard/poorly visualised).

Timeline

Start date: 2023-10-31
Primary completion: 2024-10-31
Completion: 2025-06-01
First posted: 2023-10-10
Last updated: 2025-11-24

Locations

1 site across 1 country: United Kingdom

Source: ClinicalTrials.gov record NCT06075836. Inclusion in this directory is not an endorsement.