ChestEye Quality

Oxipit

ChestEye Quality is an automatic Quality Assurance (QA) chest X-ray solution. It automatically double-reads all chest x-rays, by analyzing radiologists' reports and comparing them with AI analysis of the studies. If ChestEye Quality identifies possible False Negative (FN) made by radiologists, it highlights the cases for the final review for the radiologists. ChestEye Quality goal is to improve the reporting accuracy of the radiologist and act as a safety net to avoid any possible FN for the radiologists.

Information source: Vendor
Last updated: September 4, 2024

General Information

General
Product name	ChestEye Quality
Company	Oxipit
Subspeciality	Chest
Modality	X-ray
Disease targeted	Algorithms supports 75 different pathologies
Key-features	Quality assurance, identifying missed clinical significant findings
Suggested use	After: diagnosis verification

Technical Specifications

Data characteristics
Population	Patients over 18 years old
Input	PA or PA + LAT Digital Chest X Ray
Input format	DICOM
Output	List of possible False Negatives made by radiologists
Output format	DICOM SR or HL7 message
Technology
Integration	Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform
Deployment	Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis	Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time	3 - 10 seconds

Regulatory

Certification
CE	Certified, Class IIa , MDD
FDA	No or not yet
Intended Use Statements
Intended use (according to CE)	ChestEye Quality is a quality assurance tool combining artificial intelligence with human radiologists. The product works in two steps. Firstly, the artificial intelligence software reads final radiologists' reports and corresponding CXR images. It identifies potential reporting errors made by the reporting radiologists, by comparing the radiologist's report with the internal results of ChestEye Quality. The software then flags the cases for Oxipit radiologists to review. The second step is for the Oxipit radiologist to double-check the cases, which were automatically flagged by the solution, to identify any cases with a high probability of a missed finding. Identified cases are then sent to the hospital's radiologists via email or via integration in the PACS/RIS/HIS systems. It's the hospital's radiologists' decision if any action (such as adding an addendum to/modifying the radiological report) should be taken. Using the tool prospectively enables the radiology department to identify the most common mistakes, call for extra attention, or provide additional training to mitigate the risk of missed pathologies.

Market

Market presence
On market since	09-2021
Distribution channels	Alma AI MARKETPLACE, BLackford, Sectra Amplifier Store, CARPL.ai
Countries present (clinical, non-research use)	9
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model	Pay-per-use, Subscription
Based on	Number of installations, Number of analyses

Evidence

Evidence
Peer reviewed papers on performance	Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software (read) Real‑world testing of an artificial intelligence algorithm for the analysis of chest X‑rays in primary care settings (read) Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation (read) Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction (read)
Non-peer reviewed papers on performance
Other relevant papers