O-arm O2 Imaging System
Medtronic Navigation, Inc • Radiology • 06/21/2024
Device Purpose
The O-arm™ O2 Imaging System is a mobile cone-beam CT device designed for intraoperative 2D and 3D visualization of bony anatomy and metallic implants, supporting image-guided surgery. Its 4.3.0 software iteration enhances this capability through specialized algorithms for metal artifact reduction (KCMAR), extended multi-volume 3D scanning (3DLS), and machine learning-based dose reduction (SSD) for spinal procedures, all validated for clinical utility and safety.
Summary
The O-arm™ O2 Imaging System is a mobile X-ray system designed to provide clinicians with both 2D and 3D intraoperative imaging for adult and pediatric patients weighing 60 lbs or more and having an abdominal thickness greater than 16 cm. Its primary utility lies in visualizing anatomic structures and objects with high X-ray attenuation, such as bony anatomy and metallic implants, and it is compatible with image-guided surgery systems. The system employs cone-beam computed tomography (CBCT) technology, utilizing a 360-degree rotating X-ray source and a 40x30 cm flat-panel detector to acquire images, which are then reconstructed into 3D volumes. It consists of an Image Acquisition System (IAS) and a Mobile View Station (MVS) and supports various imaging modes, including 2D fluoroscopy, 2D stitched radiography (Long Film), and 3D imaging with different fields of view and protocols. The latest iteration, featuring software version 4.3.0, introduces significant enhancements aimed at improving image quality and reducing radiation dose. Key new features include Medtronic Implant Resolution (MIR/KCMAR), an algorithm that uses the known geometry of supported Medtronic implants to reduce metal artifacts and enhance implant visibility. Another addition is the 3D Long Scan (3DLS), which enables the acquisition of auto-registered 3D scans over an extended length (up to approximately 43.8 cm), particularly for spinal applications, integrating with navigation systems. Finally, Spine Smart Dose (SSD) leverages machine learning to denoise images acquired with fewer projections, achieving approximately a 70% dose reduction for spinal 3D imaging while maintaining clinical equivalence to standard dose images. Performance testing, including cadaver studies and phantom tests, demonstrated the clinical utility, image quality, and safety of these new features, with KCMAR showing statistically better image quality around metallic implants and SSD providing clinically equivalent images at significantly lower radiation doses.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the Medtronic Implant Resolution (MIR/KCMAR) algorithm's performance vary with different types, sizes, and materials of Medtronic implants not explicitly detailed in the supported list?; What is the quantifiable impact of the Spine Smart Dose (SSD) feature on specific diagnostic tasks in spinal surgery, beyond general clinical equivalence, particularly for subtle pathologies?; For the 3D Long Scan (3DLS) feature, what is the registration accuracy between the multiple auto-registered 3D scans, and how might this influence its utility in complex multi-level spinal procedures?; Given the machine learning basis of the Spine Smart Dose (SSD) denoising algorithm, what is the diversity and size of the training dataset used, and how does the system ensure generalizability across varying patient anatomies and pathologies not represented in the training data?; What are the specific image quality metrics (e.g., spatial resolution, contrast-to-noise ratio) for the Spine Smart Dose (SSD) images compared to standard dose images, and how do these metrics correlate with the observed clinical equivalence?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Post-§524B but no clear network capability detected
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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 SBOM, ML-BOM detected in AI-generated device summary.
• Cybersecurity risk assessment not referenced in AI-generated device summary. FDA cybersecurity guidance (2023) expects this for cyber devices.
• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.
• Not detected in AI-generated device summary: SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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