Skip to main content
OpenTrials
Completed

NCT Number: NCT06075836

AI Assisted Detection of Chest X-Rays

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.

Completed

Looking for future studies?

Notify Me

Key information

Conditions

Pulmonary Nodules, Solitary Atelectasis Bronchial Diseases Bronchiolitis Bronchiolitis Obliterans Bronchiolitis Obliterans Syndrome Bronchitis Cardiomegaly Cardiovascular Diseases Digestive System Diseases Fibrosis Fibrosis Lung Graft vs Host Disease Heart Diseases Hypertrophy Immune System Diseases Lung Diseases Lung Diseases, Interstitial Lung Diseases, Obstructive Lung Neoplasms Multiple Pulmonary Nodules Neoplasms Neoplasms by Site Organizing Pneumonia Pathologic Processes Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Peritoneal Diseases Pleural Diseases Pleural Effusion Pleural Effusions, Chronic Pneumoperitoneum Pneumothorax Pneumothorax; Acute Pulmonary Atelectasis Pulmonary Calcification Pulmonary Consolidation Pulmonary Fibrosis Pulmonary Nodules, Multiple Respiratory Tract Diseases Respiratory Tract Neoplasms Solitary Pulmonary Nodule Thoracic Neoplasms

Sex eligibility

All sexes

Study type

Observational

Primary location

Oxford University Hospitals NHS Foundation Trust

Oxford, Oxfordshire, OX3 9DU, United Kingdom

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • General radiologists/radiographers/physicians who review CXRs as part of their routine clinical practice

Exclusion criteria

  • Thoracic radiologists
  • Non-radiology physicians with previous formal postgraduate CXR reporting training.
  • Non-radiology physicians with previous career in radiology, respiratory medicine or thoracic surgery to registrar or consultant level

Treatment and study plan

Cases reading

Other

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.

Ground truthing

Other

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).

Primary outcomes

  1. Performance of AI algorithm: sensitivity

    Time frame: During 4 weeks of reading time

    Evaluation of the Lunit INSIGHT CXR algorithm will be performed comparing it to the reference standard in order to determine sensitivity.

  2. Performance of AI algorithm: specificity

    Time frame: During 4 weeks of reading time

    Evaluation of the Lunit INSIGHT CXR algorithm will be performed comparing it to the reference standard in order to determine specificity.

  3. Performance of AI algorithm: Area under the ROC Curve (AU ROC)

    Time frame: During 4 weeks of reading time

    Evaluation of the Lunit INSIGHT CXR algorithm will be performed comparing it to the reference standard. Continuous probability score from the algorithm will be utilized for the ROC analyses, while binary classification results with a predefined operating cut-off will be used for evaluation of sensitivity, specificity, positive predictive value, and negative predictive value.

  4. Performance of readers with and without AI assistance: Sensitivity

    Time frame: During 4 weeks of reading time

    The study will include two sessions (with and without AI overlay), with all 30 readers reviewing all 500 CXR cases each time separated by a washout period to mitigate recall bias. The cases will be randomised between the two reads and for every reader.

  5. Performance of readers with and without AI assistance: Specificity

    Time frame: During 4 weeks of reading time

    The study will include two sessions (with and without AI overlay), with all 30 readers reviewing all 500 CXR cases each time separated by a washout period to mitigate recall bias. The cases will be randomised between the two reads and for every reader.

  6. Performance of readers with and without AI assistance: Area under the ROC Curve (AU ROC)

    Time frame: During 4 weeks of reading time

    The study will include two sessions (with and without AI overlay), with all 30 readers reviewing all 500 CXR cases each time separated by a washout period to mitigate recall bias. The cases will be randomised between the two reads and for every reader.

  7. Reader speed with vs without AI assistance.

    Time frame: During 4 weeks of reading time

    Mean time taken to review a scan, with vs without AI assistance.

Sponsors and collaborators

Lead sponsor

Oxford University Hospitals NHS Trust

Other

Registry information

Official study title

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

Acronym: AID-CXR

Important dates

Study start
2023
Primary completion
2024
Study completion
2025
First posted
Oct 10, 2023
Registry last updated
Nov 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.