RBfracture

Radiobotics
RBfracture is an automated tool to diagnose fractures on x-ray.
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Information source: Vendor
Last updated: December 4, 2024

General Information

General
Product name RBfracture
Company Radiobotics
Subspeciality MSK
Modality X-ray
Disease targeted Fractures across the appendicular skeleton, ribs and pelvis
Key-features Fracture detection
Suggested use Before: adapting worklist order, flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand)

Technical Specifications

Data characteristics
Population Adult patients with suspicion of fractures, pediatrics patients >2yrs old.
Input 2D X-ray
Input format DICOM
Output Bounding box detection of fracture or doubtful fracture, lipohemarthrosis, or effusion; and a color-coded summary box
Output format DICOM secondary capture
Technology
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
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 IIa , MDR
FDA No or not yet
Intended Use Statements
Intended use (according to CE) RBfracture is a computer-assisted detection and diagnosis software device to assist healthcare professionals in reviewing trauma skeletal radiographs.

Market

Market presence
On market since 06-2022
Distribution channels Eureka Clinical AI, ImageBiopsy Lab (DACH), Sectra Amplifier, Blackford, deepcOS, K2Ai
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model Pay-per-use, Subscription, One-time license fee
Based on Number of analyses

Evidence

Evidence
Peer reviewed papers on performance

  • Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits (read)

  • Improving traumatic fracture detection on radiographs with artificial intelligence support: a multi-reader study (read)
Non-peer reviewed papers on performance

  • RBfracture brochure and evidence (read)

  • Case study: Performance audit at Kettering General Hospital (read)
Other relevant papers