Prostate MR on syngo.via

Siemens Healthineers

**Currently only available with Siemens Healthineers' syngo.via**
Siemens Healthineers Prostate MR on syngo.via supports prostate MRI reading and reporting. By deploying artificial intelligence, Prostate MR assists in the interpretation of multiparametric Prostate MRI. The deep neural networks of Prostate MR are designed to aid the detection and classification of prostate lesions and generate a pre-populated report.
The product is not commercially available in some countries, e.g. the US. Due to regulatory reasons the future availability cannot be guaranteed. Please contact your local Siemens Healthineers organization for further details.
Product specifications Information source: Vendor
Last updated: June 10, 2021
Product name Prostate MR on syngo.via
Company Siemens Healthineers
Subspeciality Abdomen
Modality MR
Disease targeted Prostate cancer
Key-features Prostate gland segmentation and volumetric assessment, lesion candidate localization and classification, suspicion map highlighting the lesion candidates, pre-populated PI-RADS report
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion, concurrent reading aid
Data characteristics
Population Men with suspected cancer in treatment-naïve prostate glands
Input Transversal T2-weighted image, low and high b-value DWI
Input format DICOM
Output Prostate gland and lesion contours, suspicion heatmap, structured report with volumetrics, PSA density and classification
Integration Integration in Advanced Visualization and Post-Processing Platform
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker)
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc., In pre-processing
Processing time 3 - 10 seconds
Certified, Class IIa , MDD
No or not yet
Market presence
On market since 08-2020
Distribution channels syngo.via
Countries present (clinical, non-research use)
Paying clinical customers (institutes) >10
Research/test users (institutes) >10
Pricing model Subscription
Based on Number of analyses
Peer reviewed papers on performance

  • A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate: Results of a Multireader, Multicase Study. (read)

Non-peer reviewed papers on performance
Other relevant papers

  • False Positive Reduction using Multiscale Contextual Features for Prostate Cancer Detection in Multi-Parametric MRI Scans (read)