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AI-Rad Companion Chest X-ray
AI-Rad Companion Chest X-ray
Siemens Healthineers
The AI-Rad Companion Chest X-ray automatically characterizes radiographic findings for a valid chest scan in the lung and pleura. It works like a second or third reader to support radiologists in differential diagnosis and clinical decision-making. It is capable of detecting pneumothorax, pulmonary lesions (nodules, masses, and granuloma), actelectasis, consolidation and pleural effusion. The DL algorithms automatically detect the tip of the endotracheal tube and carina. The distance will be computed and notifies when the distance between an endotracheal tube tip and the carina is above or below the configured threshold.
Information source:
Vendor
Last updated:
June 30, 2024
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
AI-Rad Companion Chest X-ray
Company
Siemens Healthineers
Subspeciality
Chest
Modality
X-ray
Disease targeted
Pulmonary lesions, pleural effusion, pneumothorax, consolidation, atelectasis, diseases or clinical condition which requires ventilation
Key-features
Identifying and highlighting findings, atelectasis, pleural effusion, pulmonary lesions, pneumothorax, consolidation, measuring distance tracheal tube and carina, notification with an alert
Suggested use
During: perception aid (prompting all abnormalities/results/heatmaps)
Technical Specifications
Data characteristics
Population
All upright chest X-rays (PA view) and bedside thorax (AP)
Input
Chest/Thorax X-ray, Viewing position: posterior-anterior an anterior-posterior (for limited findings)
Input format
DICOM
Output
Image annotations, Report table of suspected findings with AI confidence score
Output format
DICOM SC, DICOM GSPS, DICOM SR (TID 5000 format)
Technology
Integration
Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment
Hybrid solution
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
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class IIb
, MDR
FDA
No or not yet
Intended Use Statements
Intended use (according to CE)
AI-Rad Companion Chest X-ray is a diagnostic aid for the assessment of the presence of prespecified radiographic findings to be used by qualified medical professionals who are credentialed by their medical institutions to review chest radiographs. AI-Rad Companion Chest X-ray identifies and highlights the prespecified radiographic findings. It is intended to be used concurrently with original images before making a final determination on a case. AI-Rad Companion Chest X-ray is indicated for patients aged 22 years and above. AI-Rad Companion Chest X-ray supports in the assessment of chest radiographs acquired in clinical settings such as routine check-up, in-patient departments, clinical outpatient departments and disease screening. AI-Rad Companion Chest X-ray should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is not intended to replace the review and reporting of the chest radiograph image by a qualified medical professional.
Market
Market presence
On market since
09-2020
Distribution channels
Teamplay Digital Health Platform
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription
Based on
Number of analyses
Evidence
Evidence
Peer reviewed papers on performance
Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction
(read)
Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion
(read)
Evaluation of the clinical performance of an AI-based application for the automated analysis of chest X-rays
(read)
An Artificial Intelligence–Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study
(read)
Non-peer reviewed papers on performance
Other relevant papers