AZmed
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Documentation ProvidedRegulatory Status Disclosed
Overview
AZmed’s Rayvolve is an AI-powered suite of tools designed to assist physicians in interpreting X-ray images. It is intended for use by radiologists and emergency physicians in various care settings, including emergency departments, orthopedic clinics, trauma centers, and university hospitals.
- What it does: Rayvolve offers modules for detecting fractures, dislocations, and joint effusions (AZtrauma), analyzing chest pathologies such as pneumothorax, pleural effusion, and cardiomegaly (AZchest), performing osteoarticular measurements (AZmeasure), and assessing pediatric bone age (AZboneage).
- Who it is for: The tool is for radiologists and emergency physicians, supporting both adult and pediatric patient populations (≥2 years for fracture detection).
- How it fits a clinical or practice workflow: Rayvolve integrates directly with existing Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS) without requiring additional clicks from physicians. It processes DICOM images and provides a second DICOM output with annotations, which can be reviewed within the radiologist’s existing worklist. The system can also prioritize urgent cases through AI-driven worklist triage.
- Notable capabilities: Rayvolve is designed for comprehensive detection and triage, with a processing time of less than one minute per exam. It supports input and output in DICOM format. The AZtrauma module is FDA-cleared for fracture, dislocation, and joint effusion detection in adults and pediatrics (≥2 years). AZchest is FDA-cleared for analysis and triage of thoracic abnormalities.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered fracture detection
- X-ray image analysis
- Integration with existing PACS
- CE-marked medical device
- Supports multiple anatomical regions
Use Cases
- Assisting radiologists in fracture detection
- Supporting emergency physicians in diagnosing fractures
- Improving diagnostic accuracy in high-volume settings
- Reducing missed fracture rates
What Physicians Need to Know
Evidence Base (guidelines, literature scope)
AZmed's Rayvolve AI Suite is built on deep learning algorithms trained with over 15 million annotated X-ray images. It is CE-marked as a Class IIa medical device in Europe and has received multiple FDA clearances in the US. The suite includes modules for detecting fractures, dislocations, and effusions (AZtrauma), thoracic pathologies (AZchest), automated musculoskeletal measurements (AZmeasure), and pediatric bone age assessment (AZboneage). AZchest detects pathologies such as consolidation, pleural effusion, pneumothorax, acute pulmonary edema, cardiomegaly, and pulmonary nodules.
Clinical Validation Studies
Rayvolve has undergone extensive clinical validation. A University Hospitals (UH) study, pivotal for its FDA approval, showed a 5.6% increase in diagnostic accuracy and a 27% decrease in interpretation time across all physicians using the tool. Sensitivity improved from 0.865 to 0.955 with AI assistance, and specificity from 0.826 to 0.831. In a multi-center study, AZtrauma achieved an AUC of 84.88% for overall fracture detection and ranked highest for dislocation detection. For pediatric fracture detection, a study with SimonMed Imaging involving 3,000 radiographs demonstrated 96% sensitivity and 86% specificity, with an AUC of 94%. A clinical validation study for AZchest showed a 35.81% reduction in reading time and a 15.94% increase in AUC with AI-assisted reading. NICE in the UK concluded in January 2025 that there was enough evidence to support the potential benefit of Rayvolve and other AI technologies for use in urgent care, with low clinical risk.
Alert Fatigue Management
The AI is designed to act as a 'second reader' for every X-ray, automatically surfacing urgent findings without the radiologist having to search for them. By triaging urgent cases and automating repetitive tasks, Rayvolve aims to reduce radiologist fatigue and allow them to focus on more complex cases. The system provides study-level outputs for worklist prioritization or triage.
Override Rate Data
While specific override rate data is not explicitly detailed, AZmed emphasizes that radiologists retain control over medical diagnoses and the AI is intended to augment, not replace, the radiologist's work. The company advocates for radical transparency, including embedding real-time, case-specific confidence scores and highlighting known failure modes (e.g., overlap with plaster casts or atypical pediatric ossification centers). They also suggest mandating structured justification fields in reporting systems whenever the radiologist overrides AI advice.
Differential Diagnosis Support
Rayvolve provides computer-aided detection and diagnosis by identifying and localizing abnormalities on standard X-rays. For musculoskeletal X-rays, AZtrauma detects fractures, dislocations, and effusions. For chest X-rays, AZchest detects and categorizes major cardiothoracic abnormalities like lung nodules, pneumothorax, pleural effusion, and cardiomegaly. This acts as a diagnostic assistant to improve accuracy and support diagnostic confidence.
Guideline Update Frequency
The CE framework emphasizes continuous monitoring and ongoing clinical evaluation, ensuring the product continues to perform in real-world use. AZmed makes its science public and issues feedback loops to ensure the system continues to support healthcare without biases or performance drift. Regulatory clearances, such as FDA 510(k) and CE marking, indicate adherence to established medical device regulations.
Clinical Workflow Integration
Rayvolve is designed for seamless integration into existing clinical workflows, directly connecting with PACS and RIS without requiring additional clicks from physicians. It operates alongside the clinical workflow, meaning the modality worklist is not blocked, and the original DICOM object is not modified. After analysis (typically less than 60 seconds), a second DICOM output with annotations is created and made available in the existing worklist. Rayvolve also offers RIS-integrated report prefill, sending structured findings directly into systems like EDL and Evolucare, reducing clerical data entry and report turnaround time.
Decision Audit Trail
AZmed emphasizes the importance of audit logs that capture every access and inference by all users, and that these logs should be exportable to the institution's privacy officer. This aligns with regulatory expectations around audit logging, such as those raised by the HIPAA Security Rule proposed revision. The system is designed to meet high audit standards.
Physician Tip
Leverage Rayvolve as an intelligent 'second opinion' to enhance diagnostic accuracy and reduce interpretation time, especially in high-volume or emergency settings. Pay attention to the AI's annotations and triage prioritization to efficiently manage your workload. Utilize the RIS-integrated report prefill feature to streamline documentation and maintain consistent reporting language. While the AI provides valuable support, always maintain clinical oversight and critically review its findings, particularly in complex cases or when the AI flags known limitations (e.g., casts).
Rayvolve seamlessly integrates with existing PACS and RIS environments, supporting DICOM standards for image input and output. It offers RIS-integrated report prefill with systems like EDL and Evolucare. Partnerships with providers like Fujifilm (Synapse PACS) and Radin Health further demonstrate its interoperability and commitment to fitting into diverse healthcare IT infrastructures.
Details
| Category | Clinical Decision Support & Reference, Radiology & Imaging AI |
| Pricing |
Contact for pricing
|
| Deployment | Cloud-based, On-premise |
| Mobile App | No |
| Data Export | Unknown |
| Languages | English, French |
| Training | Unknown |
| Target Size | Hospitals, Radiology groups, Emergency departments |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
Yes AI-estimated Rayvolve is FDA cleared (510(k)) for fracture detection in adult appendicular skeleton X-rays. |
| Integrations | |
| EHR | Not specified |
| Specialties | Emergency Medicine, Orthopedics, Radiology |
Social Proof
| Customers | unknown |
| Notable | unknown |
Support & Reliability
| Training Provided | Unknown |
Ratings & Reviews
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Press & Coverage
AZmed
AZmed Secures FDA 510(k) Clearance for Rayvolve in Pediatric Fracture Detection AI
AZmed's Rayvolve solution has received FDA 510(k) clearance for detecting fractures on pediatric X-rays, two years after its clearance for adult fracture detection. This milestone was supported by an independent study with SimonMed Imaging, demonstrating high sensitivity (96%) and specificity (86%) in a dataset of 3,000 pediatric radiographs.
2024-09
AZmed
AZmed receives its 6th FDA clearance, taking Rayvolve to eight FDA-cleared findings across MSK and chest X-rays
AZmed announced its 6th FDA clearance, with its AZchest AI tool now cleared to detect and localize pneumothorax, pleural effusion, consolidation, and increased cardiothoracic ratio on frontal chest radiographs. This brings the Rayvolve AI suite to eight FDA-cleared findings for both musculoskeletal and chest X-rays.
2026-09
AuntMinnie
AZmed nets FDA clearance for x-ray AI system
AZmed and Radin Health are expanding their partnership following AZmed's third FDA 510(k) clearance for the AZtrauma module of its Rayvolve AI Suite. This clearance extends coverage to include joint effusions and dislocations alongside fracture detection on X-rays in adult and pediatric patients aged two and older.
2026-05
AZmed
Rayvolve AI Suite now Available in Fujifilm Synapse PACS
Fujifilm has partnered with AZmed to integrate its complete Rayvolveu00ae AI Suite into Fujifilm's Synapse PACS, with the first implementation at AZ Sint-Blasius in Dendermonde, Belgium. The suite includes AZtrauma for fracture and dislocation identification, AZchest for thoracic pathologies, AZmeasure for automated musculoskeletal anatomy measurement, and AZboneage for skeletal maturity assessment.
2026-03
AZmed
AZmed and RADIN Health partner to bring AI radiology tools to U.S. hospitals, imaging centers, and radiology practices
AZmed and RADIN Health have formed a strategic distribution agreement to make AZmed's Rayvolveu00ae products, including AZtrauma for fracture detection and AZchest for thoracic abnormality analysis, available across RADIN's U.S. network. This partnership aims to improve workflow efficiency and diagnostic support in radiology.
2026-04
AZmed
NHS to use AI technology for faster, more accurate fracture detection
The National Institute for Health and Care Excellence (NICE) has recognized Rayvolve as a key AI technology for diagnosing bone fractures on X-rays across the NHS. The AI solution encompasses four verticals: AZtrauma, AZchest, AZmeasure, and AZboneage, aiming to improve patient outcomes by enhancing diagnostic efficacy and safety.
2024-10
AZmed
AZmed secures u20ac15 million to shape the future of medical imaging with AI
AZmed has secured u20ac15 million in Series A funding to accelerate its mission of shaping the future of medical imaging with AI by enhancing radiologists' workflows. The company plans to double its workforce and increase R&D investment to expand its medical imaging offerings.
2024-02
Diagnostics (via AZmed)
International multicenter validation of an expanded AI diagnostic system for 18 pathologies in thoracic and musculoskeletal radiography
A large-scale international multicenter study validated the performance of AZtrauma and AZchest, components of the Rayvolve AI Suite, across 18 thoracic and musculoskeletal findings on X-rays. The study, involving 21,581 X-rays from 52 medical centers across 20 countries, demonstrated high standalone performance for both expanded and historically validated diagnostic scopes.
2026-06
Videos
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Azmed Anthum 2025.
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Revu Scape
Rayvolve by AZmed - an AI-powered computer aided diagnosis tool for radiologist (French)
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AZMED PRIMA THEME
Azmed Healthcare
Frequently Asked Questions
AZmed's solution, Rayvolve, is designed to integrate seamlessly into your existing Picture Archiving and Communication System (PACS) workflow. It analyzes X-ray images in the background and provides a second read or highlights potential fractures directly within your viewing environment, aiming to reduce reading time and improve accuracy.
AZmed's Rayvolve has undergone rigorous clinical validation, demonstrating high sensitivity and specificity in detecting various types of fractures. Studies have shown it can assist physicians in reducing missed fracture rates and improving diagnostic confidence, often performing comparably to or exceeding the performance of a single human reader, especially in high-volume settings.
Yes, AZmed's Rayvolve is CE marked as a Class IIb medical device in Europe and has received FDA 510(k) clearance in the United States. This ensures it meets the necessary regulatory standards for safety and efficacy, allowing for its use as a clinical decision support tool in compliant healthcare settings.
While highly accurate, AZmed's AI is a decision support tool and not a substitute for clinical judgment. Limitations may include challenges with very subtle fractures, complex polytrauma cases, or images with significant artifacts. Physicians should always integrate AI findings with the full clinical picture, patient history, and their own expertise, especially in ambiguous cases.
AZmed typically offers flexible pricing models that can be adapted to the size and needs of the healthcare institution, ranging from per-study fees to subscription-based models. Specific details often depend on factors like annual imaging volume and desired integration depth, with tailored options available for both individual practices and larger hospital systems.
Several other AI solutions for fracture detection are emerging in the market. Key differentiators often include the specific types of fractures they are optimized to detect, their integration capabilities with various PACS systems, their regulatory clearances, and their performance metrics in different clinical settings. It's advisable to compare clinical validation data and integration pathways when evaluating alternatives.
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| Last Verified: 2026-07-03 | First Added: 2026-06-14