SurgicalAR
MEDIVIS, Inc. • Radiology • 05/13/2019
Device Purpose
SurgicalAR is a software platform that enhances surgical planning by transforming 2D CT/MR DICOM medical images into interactive 3D models, viewable on standard monitors or through an augmented reality head-mounted display. It employs image reconstruction, volume rendering, and MPR techniques to provide clinicians with advanced visualization tools for informational and non-primary diagnostic review, operable via traditional inputs or hand gestures in AR.
Summary
SurgicalAR is a software platform designed for clinicians to visualize medical images in three dimensions, facilitating surgical planning. It processes pre-acquired 2D medical images (CT/MR DICOM data) and reconstructs them into 3D models. These models can be viewed either on a traditional computer monitor or through an augmented reality (AR) interface using a stereoscopic, holographic head-mounted display (HMD). The software supports image review, manipulation, basic measurements, and advanced 3D visualization techniques such as Multi-Planar Reconstruction (MPR) and 3D volume rendering. Intended for qualified healthcare professionals like surgeons and radiologists, SurgicalAR can be operated using a mouse and keyboard, touchscreen, or hand gestures with an HMD. While standard viewing on monitors can be used for diagnostic purposes (excluding specific mammography image types and requiring appropriate displays), images viewed on an HMD or mobile device are strictly for informational purposes and not for primary diagnosis. The system is designed for use in operating rooms and office environments. Design verification and validation, including human factors testing through simulated use, were successfully completed, indicating the software meets its design requirements without introducing unacceptable risks. The software itself does not possess essential performance characteristics, as hardware failures do not directly cause harm.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. What specific surgical specialties or procedures are most likely to benefit from SurgicalAR's AR HMD visualization capabilities for planning, and what is the evidence supporting this?; How does the performance (e.g., latency, resolution, accuracy of 3D reconstruction) of SurgicalAR on consumer off-the-shelf HMDs compare to dedicated medical-grade visualization systems, especially regarding its utility for 'informational' surgical planning?; Given that HMD viewing is for 'informational purposes only,' what are the defined use cases and limitations for AR in the operating room or surgical planning environment to ensure it does not inadvertently influence diagnostic decisions?; What types of 'basic measurements' can be performed using SurgicalAR, and what is their validated accuracy, particularly when viewed in the AR environment versus a traditional 2D/3D monitor?; The document mentions 'hand gestures' for HMD interaction. What specific gestures are supported, and what usability testing was conducted to ensure their intuitiveness and reliability in a potentially sterile or high-stress surgical planning context?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement
Learn how Parasoft automates IEC 62304 compliance testing →Cybersecurity Evidence
Powered by SBOMator™Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.
Supply Chain BOM Evidence
Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.
Analysis:
• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.
• Evidence of SaaSBOM, HBOM, OBOM detected in AI-generated device summary.
• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.
• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.
• Not detected in AI-generated device summary: SBOM, ML-BOM, CBOM, VDR/VEX. These may be present in the full FDA submission.
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