QIR-MR is a clinical decision support software for the diagnosis, treatment, prevention, or mitigation of cardiovascular conditions. It allows quantitative analyses of cardiovascular Magnetic Resonance (MR) images.
Product specifications Information source: Vendor
Last updated: March 1, 2022
Product name QIR-MR
Company CASIS - CArdiac Simulation & Imaging Software
Subspeciality Cardiac
Modality MR
Disease targeted Myocardial infarction, Myocarditis, Hypertrophic cardiomyopathy, Dilated cardiomyopathy, Amyloidosis, Fabry disease, Sarcoïdosis, Aortic aneurysm, Iron overload. coronary artery disease, Aortic, mitral and tricuspid valve diseases, stress-induced cardiomyopathy (Tako-Tsubo syndrom)
Key-features Automatic segmentation, volume quantification and length measurement of the heart chambers, strain quantification, pathological volumes detection and quantification, blood flow/velocities quantification, semi-quantification of the myocardial perfusion
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion
After: diagnosis verification
Data characteristics
Population All adult patients qualified for an MR exam
Input MR sequences, 2D, 2D+t, cine images, delayed enhancement images (phase-contrast images, first pass dynamic images), aorta images, mapping images (T1,T2,T2*), multi frame
Input format DICOM
Output Table of quantified values, analysis report, segmentation overlay, assessment of pathology presence
Output format CSV, PDF, DICOM SR, HTML, HL7
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform
Deployment Locally on dedicated hardware
Trigger for analysis On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 10 seconds - 10 minutes ( depends on the type of study)
Certified, Class IIa , MDD
No or not yet
Market presence
On market since 06-2018
Distribution channels artificial-insight.io
Countries present (clinical, non-research use) 18 countries
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Pay-per-use, Subscription, One-time license fee
Based on Number of users, Number of installations, Number of analyses
Peer reviewed papers on performance

  • Automatic deep learning-based myocardial infarction segmentation from delayed enhancement MRI (read)

  • Cardiac MRI Segmentation with Strong Anatomical Guarantee (read)

Non-peer reviewed papers on performance N/A
Other relevant papers N/A