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Completed

NCT Number: NCT05594485

Retrospective Study of Carebot AI CXR Performance in Preclinical Practice

The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Carebot AI CXR is defined as a recommendation system (classification "prediction") based on computer-aided detection. The software can be used in a preclinical deployment at a selected site before interpretation (prioritization, display of all results and heatmaps) or after interpretation (verification of findings) of CXR images, and in accordance with the manufacturer's recommendations. Given this, a retrospective study is performed to test the clinical effectiveness on existing CXRs.

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Key information

Conditions

Artificial Intelligence Atelectasis Cardiomegaly Cardiovascular Diseases Consolidation Fracture Rib Fractures, Bone Heart Diseases Hilar Calcification Hypertrophy Infections Lung Cancer Lung Diseases Lung Neoplasms Neoplasms Neoplasms by Site Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Pleural Diseases Pleural Effusion Pneumonia Pneumothorax Pulmonary Atelectasis Pulmonary Edema Respiratory Tract Diseases Respiratory Tract Infections Respiratory Tract Neoplasms Rib Fractures Thoracic Injuries Thoracic Neoplasms Wounds and Injuries

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Nemocnice Havířov, p. o.

Havířov, 73601, Czechia

About this study

The performance of the trained and internally validated Carebot AI CXR software is tested on a set of 127 CXR images from target population. This is compared to common clinical practice, i.e., image assessment by a radiologist in a hospital. Patients may have a variety of findings; at this stage of the evaluation, an abnormal finding is considered to be an abnormality in any of the defined classes. False negative images incorrectly predicted by Carebot AI CXR software result in a clinical impact determination.

To collect the CXR data for retrospective study, investigators addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 pre-selected abnormalities. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Hospital patients who were referred for chest radiography between August 15 and 17, 2022.

Exclusion criteria

  • Pediatric CXR images (under 18 years of age)
  • Scans with technical problems (poor image quality, rotation)
  • Images in lateral projection

Treatment and study plan

Carebot AI CXR

Device

Carebot AI CXR is a deep learning-based software that assists radiologists in the interpretation of chest radiographs in posterior-anterior (PA) or anterior-posterior (AP) projections. The solution with artificial intelligence automatically detects abnormality based on visual patterns for the following findings: atelectasis, consolidation, cardiomegaly, mediastinal widening, pneumoperitoneum, pneumothorax, pulmonary edema, pulmonary lesion, bone fracture, hilar enlargement, subcutaneous emphysema, and pleural effusion.

Primary outcomes

  1. Primary objective

    Time frame: 20-10-2022

    Comparison of the accuracy of radiologist and Carebot AI CXR image assessment.

Secondary outcomes

  1. Secondary objective

    Time frame: 20-10-2022

    Comparison of the accuracy of radiologis with different experience vs. Carebot AI CXR. Weakness assessment of Carebot AI CXR.

Sponsors and collaborators

Lead sponsor

Carebot s.r.o.

Industry

Registry information

Official study title

Chest X-Ray Abnormality Detection Using Artificial Intelligence: Retrospective Study of Carebot AI CXR Performance in Preclinical Practice

Important dates

Study start
2022
Primary completion
2022
Study completion
2022
First posted
Oct 26, 2022
Registry last updated
Jul 13, 2023

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.

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