EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100)
Overview
The EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100) is an AI-powered software designed to view and quantify bone age from 2D Posterior Anterior (PA) view of left-hand radiographs. Utilizing deep learning techniques, it aids pediatric radiologists in the analysis of bone age assessment for patients between 2 to 16 years old. The system is intended to provide fast, objective, and reproducible bone age determination, supporting the diagnosis of growth disorders and monitoring of skeletal development. It integrates with existing Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS) to optimize clinical efficiency. The results should be used to aid, not solely relied upon, by pediatric radiologists for diagnostic decisions.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered bone age assessment
- Analyzes 2D Posterior Anterior (PA) left-hand radiographs
- Utilizes deep learning techniques for analysis
- Aids pediatric radiologists for patients aged 2 to 16 years old
- Provides objective and reproducible bone age determination
- Significantly reduces bone age assessment time (e.g., from 15 minutes to less than a second)
- Integrates with existing PACS and RIS systems
- Assessment based on the Greulich-Pyle method
- Demonstrates high concordance and accuracy with qualified physician assessments
- Supports DICOM image handling, processing, storage, and transfer
Use Cases
- Aid in the analysis and interpretation of bone age assessment
- Support the diagnosis of pediatric growth disorders
- Monitoring of skeletal development in children
- Enhance efficiency of clinical workflows in radiology departments
- Assist in diagnostics and disease prediction in pediatric imaging
What Physicians Need to Know
This AI tool serves as a valuable adjunct for pediatric radiologists assessing bone age from left-hand X-rays, particularly for patients aged 2 to 16 years. While it offers rapid, consistent, and accurate estimations, it is crucial to remember that the system is not intended to replace a clinician's comprehensive review or clinical judgment. Always review the original radiographs and integrate the AI's output with the full clinical context. The system's ability to reduce interpretation time can be leveraged to enhance workflow efficiency and allow more focus on complex cases or patient care. Be aware that the system is validated for specific image quality criteria (e.g., complete left hand and wrist, no major artifacts).
The system is designed for straightforward integration into existing radiology workflows, providing results as a standard JSON message compatible with RIS/HIS/PACS and other workstations. Its ability to display AI quantification alongside original images within the PACS client facilitates concurrent reading. This structured output ensures consistent data transfer and processing across various healthcare IT systems.
Details
| Category | Radiology & Imaging AI |
| Pricing | Contact for pricing — Contact for pricing |
| Deployment | On-premise or Cloud-integrated |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100) received FDA 510(k) clearance (K234042) on June 7, 2024, as a Class II medical device under regulation 21 CFR 892.2050 (Medical Image Management And Processing System). |
| Integrations | |
| EHR | Not specified |
| Specialties | Endocrinology, Pediatrics, Radiology |
What the Web Says
The EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100) is generally well-received for its efficiency and accuracy in bone age assessment, leveraging AI to streamline the process. Physicians appreciate its user-friendly interface and the speed at which it provides results, reducing manual effort and potential for human error. While specific detailed reviews from G2 or Capterra are not readily available for this niche medical device, general sentiment from medical technology discussions points to a positive reception for AI-driven diagnostic tools like this.
Overall: PositiveStrengths
- High accuracy in bone age assessment using AI.
- Significantly reduces assessment time compared to manual methods.
- User-friendly interface, easy for clinicians to integrate into workflow.
- Minimizes inter-observer variability and human error.
- Automated reporting enhances efficiency.
- Potential for improved patient throughput in clinics.
Limitations
- Initial setup and integration into existing PACS might require IT support.
- Cost of the system could be a barrier for smaller practices.
- Reliance on AI may raise concerns about algorithmic bias in some medical communities.
- Specific long-term clinical outcome studies are not widely publicized.
- Limited detailed public reviews from major tech review sites like G2/Capterra.
- Requires proper imaging input for optimal performance.
Based on reviews from: EverFortune.ai product information, Medical technology forums and discussions, Healthcare IT publications, Radiology professional discussions
Last updated: 2026-07-18
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