KEROS

Incepto

KEROS is an artificial intelligence augmented radiology solution for knee MRI. It automatically analyzes the main anatomical structures of the knee and detects lesions of ligaments, menisci and cartilages.

Information source: Vendor
Last updated: Jan. 21, 2024

General Information

General
Product name	KEROS
Company	Incepto
Subspeciality	MSK
Modality	MR
Disease targeted	Meniscus and ligament tears, chondropathies
Key-features	Detect and characterize lesions of ligaments, menisci and cartilages
Suggested use	Before: flagging acute findings During: report suggestion After: diagnosis verification

Technical Specifications

Data characteristics
Population	Patient over 16 yo with no history of knee surgery
Input	2D, 3D, proton density fat saturation, T2 fat saturation
Input format	DICOM
Output	Pre-filled report including finding and location
Output format	PDF or DICOM Secondary Capture
Technology
Integration	Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform
Deployment	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	1 - 10 minutes

Regulatory

Certification
CE	Certified, Class IIa , MDR
FDA	No or not yet
Intended Use Statements
Intended use (according to CE)	KEROS is a software application based on artificial intelligence and intended to be used as a tool in knee MRI interpretation. Its usage is dedicated only to clinicians. KEROS should not be used alone to recommend medical care.

Market

Market presence
On market since	01-2021
Distribution channels	Incepto
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	Deep learning to detect anterior cruciate ligament tear on knee MRI: multi-continental external validation (read) Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation (read)
Non-peer reviewed papers on performance
Other relevant papers