RevealAI-Lung

RevealDx

RevealAI™ is Computer Assisted Diagnostic (CADx) software that reveals patterns within images and across patients. The analytics generate scores for the current patient by comparing abnormalities to other patients that have confirmed diagnostics. RevealAI-Lung provides a Malignancy Similarity Index (mSI) from lung CT scans that aids risk assessment. Graphs are provided that help interpret how lung nodules from the current patient relate to confirmed malignant or benign nodules.

Information source: Vendor
Last updated: November 7, 2024

General Information

General
Product name	RevealAI-Lung
Company	RevealDx
Subspeciality	Chest
Modality	CT
Disease targeted	Lung cancer
Key-features	Nodule malignancy similarity score
Suggested use	During: interactive decision support (shows abnormalities/results only on demand)

Technical Specifications

Data characteristics
Population	Incidental nodules and those found during screening
Input	CT, 3D, contrast, non-contrast
Input format	DICOM
Output	Malignancy Similarity Index (mSI)
Output format	To be determined
Technology
Integration	Integration in standard reading environment (PACS)
Deployment	Locally on dedicated hardware, Cloud-based
Trigger for analysis	On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time	< 3 sec

Regulatory

Certification
CE	Certified, Class IIa , MDD
FDA	No or not yet
Intended Use Statements
Intended use (according to CE)	Design and manufacture of software intended as a decision aid for analysis of computed tomography (CT) scans of the lung for cancer diagnosis.

Market

Market presence
On market since	05-2021
Distribution channels	contextflow, Amplify SDK, Riverain Technologies
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)	2
Pricing
Pricing model	Pay-per-use, Subscription
Based on	Number of analyses

Evidence

Evidence
Peer reviewed papers on performance	Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT (read)
Non-peer reviewed papers on performance
Other relevant papers