contextflow ADVANCE Chest CT

contextflow

contextflow ADVANCE Chest CT is a 3D image-based search engine (currently it looks for 19 disease patterns in lung CTs). It identifies and matches relevant, visually-similar disease patterns to aid in diagnosis. By marking a region of interest in the image, contextflow ADVANCE Chest CT returns reference cases and associated knowledge and medical literature relevant for differential diagnosis. It integrates directly into the following PACS: Agfa, Medigration, Philips, Sectra.

Product specifications

Information source: Vendor
Last updated: March 16, 2023

General
Product name	contextflow ADVANCE Chest CT
Company	contextflow
Subspeciality	Chest
Modality	CT
Disease targeted	Airway wall thickening, atelectasis, bronchiectasis, bulla, consolidation, cyst, effusion, emphysema, ground-glass opacity, honeycoming, incidental pulmonary embolism (iPE), mass, mosaic attenuation pattern, nodular pattern, nodule, pneumothorax, pulmonary cavity, reticular pattern, tree-in-bud
Key-features	Content-based image retrieval, pattern classification, lung anomaly detection
Suggested use	During: interactive decision support (shows abnormalities/results only on demand)
Data characteristics
Population	CT scans in which lung-specific image patterns should be identified and interpreted
Input	3D chest CT scans of the lungs
Input format	DICOM
Output	Visually-similar and expert-labeled images, lung anomaly overlays, classification of selected image regions
Output format	Interactive user-interface, web-application
Technology
Integration	Integration in standard reading environment (PACS)
Deployment	Locally virtualized (virtual machine, docker), Hybrid solution
Trigger for analysis	Automatically, right after the image acquisition
Processing time	> 10 minutes
Certification
CE	Certified, Class IIa , MDR
FDA	No or not yet
Market presence
On market since	10-2019
Distribution channels	Sectra Amplifier Store, Wellbeing Software, Alma HEALTH PLATFORM, Alphatron, Osimis
Countries present (clinical, non-research use)	N/A
Paying clinical customers (institutes)	N/A
Research/test users (institutes)	10+
Pricing
Pricing model	Pay-per-use, Subscription
Based on	Number of analyses
Evidence
Peer reviewed papers on performance	Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease (read)
Non-peer reviewed papers on performance	N/A
Other relevant papers	N/A