YSIO X.pree
Siemens Medical Solutions • Radiology • 05/21/2024
Device Purpose
The YSIO X.pree is an advanced stationary digital X-ray system engineered for comprehensive anatomical visualization, utilizing a modular design with specific X-ray generation and detection components, including newly introduced wireless detectors and AI-driven collimation. Its methodology centers on converting X-ray patterns into high-quality digital images via the syngo XR platform to support diverse diagnostic needs, with recent updates enhancing automated imaging processes and detector options, which have been clinically validated for performance and image acceptability.
Summary
The YSIO X.pree is a stationary digital radiography X-ray system designed by Siemens Medical Solutions USA, Inc. to visualize anatomical structures throughout the human body, including the skull, chest, abdomen, and extremities. Its primary purpose is to generate X-ray images that support medical professionals in making diagnostic and therapeutic decisions for pediatric, adult, and bariatric patients, including emergency applications, but excluding mammography. The system features a modular design, allowing configurations with components such as a ceiling-mounted X-ray tube (OPTITOP 150/40/80/HC-100), Bucky wall stand, Bucky table, an X-ray generator (Polydoros R80 65/80 kW), and a variety of portable wireless and fixed integrated detectors to suit diverse clinical requirements. This iteration of the YSIO X.pree (VA20) introduces specific enhancements over its predicate, including an updated camera model within the collimator, a new 'Auto Long-Leg/Full-Spine' auto-collimation function which incorporates an algorithm from the Multix Impact reference device, and the addition of two new wireless detectors (Trixell pixium 3543EZ3 “X.wi-D 35” and Trixell pixium 4343EZ3 “X.wi-D 43”). The system operates on the syngo XR digital imaging platform, featuring Windows 10, myExam IQ for image processing, AI-based auto cropping, and CARE technology for radiation exposure reduction. Clinical validation through a Customer Use Test in Germany confirmed the system's performance, usability, and image quality, noting that images from the new detectors were fully acceptable for radiographic use and that the system met its intended clinical needs.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the new camera model in the YSIO X.pree collimator specifically improve patient positioning accuracy or reduce setup time compared to the previous model?; What are the quantitative differences in image quality (e.g., DQE, MTF) or dose efficiency for the new Trixell pixium 3543EZ3 and 4343EZ3 wireless detectors compared to existing detectors in the YSIO X.pree line?; Can you provide data on the accuracy and consistency of the 'Auto Long-Leg/Full-Spine' collimation feature across various patient anatomies and its impact on minimizing radiation exposure outside the region of interest?; What were the key findings from the Customer Use Test regarding the integration of the Multix Impact algorithm for auto-collimation, particularly concerning ease of use and perceived benefits by the clinical users?; Beyond general acceptability, what specific aspects of image quality from the new wireless detectors were evaluated in the Customer Use Test, and how did they perform in challenging diagnostic scenarios (e.g., bariatric patients, subtle pathologies)?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Qualifies as a cyber device under §524B (post-Dec 2023, networked)
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 ML-BOM, SaaSBOM, HBOM, OBOM detected in AI-generated device summary.
• SBOM not mentioned in AI-generated device summary. Under §524B (effective Oct 2023), cyber devices must provide a SBOM.
• 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: SBOM, CBOM, VDR/VEX. These may be present in the full FDA submission.
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