qMSK

Qure.ai
qMSK is a deep-learning based X-Ray interpretation and labeling software. It screens radiographs of 15 anatomies (clavicle, ribs, shoulder, humerus, elbow, forearm, wrist, hand/fingers, hip, pelvis, femur, knee, tibia-fibula, ankle, foot/toe) for signs of fractures. The output is an additional DICOM with a summary of AI findings and a bounding box drawn around the suspected site of fracture, if any.
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Information source: Vendor
Last updated: Jan. 4, 2024

General Information

General
Product name qMSK
Company Qure.ai
Subspeciality MSK
Modality X-ray
Disease targeted Fractures of appendicular skeleton and ribs
Key-features Fracture detection with bounding box
Suggested use Before: flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion

Technical Specifications

Data characteristics
Population MSK X-Rays of specified anatomies belonging to adult patients (18+)
Input Any radiographic view of the specified anatomies
Input format DICOM
Output Bounding boxes, binary tagging of scan into fracture positive/negative, worklist prioritisation
Output format DICOM, pdf/free text report, SR report
Technology
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), 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 10 - 60 seconds

Regulatory

Certification
CE
Certified, Class IIb , MDR
FDA No or not yet
Intended Use Statements
Intended use (according to CE) Standalone computer aided detection (CAD) and notification medical device software for musculoskeletal X-ray analysis and reporting.

Market

Market presence
On market since 01-2023
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model Pay-per-use, Subscription
Based on Number of installations

Evidence

Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers