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Myrian XP-Prostate option AI
Myrian XP-Prostate option AI
Intrasense by Guerbet
Myrian XP-Prostate option AI includes an AI developed by Guerbet. An AI algorithm to segment the prostate, performs rapid, reliable analysis, identify lesions and ensure patient follow-up. It enables automatic prostate segmentation and volume calculation, automatic calculation of PSA density, automatic detection of suspicious areas of PIRADS > 3 thanks to artificial intelligence.
**Currently only available through Myrian platform**
Information source:
Vendor
Last updated:
July 9, 2024
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
Myrian XP-Prostate option AI
Company
Intrasense by Guerbet
Subspeciality
Abdomen
Modality
MR
Disease targeted
Prostate cancer
Key-features
Prostate segmentation, prostate volume, highlighted suspicious areas
Suggested use
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion
After: diagnosis verification, Possible interaction with results
Technical Specifications
Data characteristics
Population
Male adult
Input
MRI, T2, DWI, DCE (optional)
Input format
DICOM
Output
Probability map, structured report with key images, volumes and risk score
Output format
DICOM
Technology
Integration
Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application
Deployment
Locally on dedicated hardware, Locally virtualized (virtual machine, docker)
Trigger for analysis
Automatically, right after the image acquisition
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)
Market
Market presence
On market since
04-2024
Distribution channels
Myrian
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription, One-time license fee
Based on
Number of users, Number of installations
Evidence
Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers