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Syngo Carbon Enterprise Access (VA40A)

Siemens Healthcare GmbH • Radiology • 05/23/2024

510(k)IEC 62304 Class B§524B Cyber Device
FDA Summary PDF

Device Purpose

Syngo Carbon Enterprise Access (VA40A) is a software-only medical device operating on a client-server architecture, designed as an enterprise-wide web application for the display and rendering of diverse medical data, including DICOM, non-DICOM, and clinical documents, to support diagnostic review by trained professionals within healthcare institutions. It utilizes standard IT hardware and network protocols, offering image manipulation and measurement tools, while being contraindicated for primary diagnosis in mammography, pathology, and on mobile devices in the USA.

Summary

Syngo Carbon Enterprise Access (VA40A) is a software-only medical device designed for installation on common IT hardware, functioning as an enterprise-wide web application. Its primary role is to enable trained medical professionals to display and render a variety of medical data, including DICOM images, non-DICOM files, multimedia data, and clinical documents, thereby facilitating image and result distribution for diagnostic purposes within healthcare institutions. The system connects to medical devices via standardized generic interfaces but does not control or alter their functions, focusing on providing access and viewing capabilities. The device operates on a client-server architecture, supporting standard network protocols like TCP/IP and communication protocols such as DICOM (2016a) and non-DICOM objects. It incorporates image display algorithms including MPR, MIP, MinIP View, AVG, and MED, along with measurement and evaluation tools like distance, pixel lens, angle, and polygon annotation. It is important to note that Syngo Carbon Enterprise Access is not intended for the diagnosis of digital mammography images or digital pathology reading, nor for diagnostic use on mobile devices within the United States. Furthermore, it is not meant to be used as the sole basis for clinical decisions. The device's safety and effectiveness were established through non-clinical verification and validation testing, conforming to relevant standards such as ISO 14971 and IEC 62304.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

Medical Image ViewingDICOMWeb-based AccessEnterprise DistributionClient-Server ArchitectureImage RenderingNon-DICOM DataClinical Document DisplayDiagnostic SupportSoftware Only Device

Device Metadata

Submission Number
K240294
Company
Siemens Healthcare GmbH
Panel
Radiology
Product Code
N/A
Data Type
Images
Clinical Function
Assessment
AI Function
Analysis
AI Subclass
quantification/feature localization

Relevant Clinical Questions

  • Q1. How do the newly added image display algorithms 'AVG' and 'MED' in Syngo Carbon Enterprise Access VA40A enhance diagnostic capabilities compared to the predicate's 'Physician Access' component, and for which specific medical data types are they most beneficial?; Given the contraindication against diagnostic use on mobile devices in the USA, what are the specific technical limitations or image fidelity concerns, and how does this align with the capabilities of the supported iPadOS and Safari browser versions?; What are the specific mechanisms and protocols Syngo Carbon Enterprise Access employs for ensuring seamless and secure enterprise-wide data access and distribution across diverse IT infrastructures and network configurations?; Could you elaborate on the performance implications, such as loading times and rendering speeds, when handling large or complex DICOM/non-DICOM datasets, especially when accessed via different supported web browsers (Chrome, Edge, Firefox, Safari)?; While the device does not offer CAD functionalities, how does its architecture support or hinder potential future integrations with third-party AI or advanced image analysis tools within an enterprise setting?

Risk Classification

ESL Analysis
FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Qualifies as a cyber device under §524B (post-Dec 2023, networked)

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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.

Cyber Score20/100
SBOM Evidence⚠ Not in summary - likely in full submission per §524B
Cyber Risk Assessment⚠ Not in summary - likely in full submission per §524B
Postmarket Plan⚠ Not in summary - likely in full submission per §524B
§524B ApplicableYes

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials
- Not detected
ML-BOMMachine Learning Bill of Materials(algorithm, dataset, annotation)
✓ Detected
SaaSBOMSoftware-as-a-Service Bill of Materials(server, network, infrastructure)
✓ Detected
HBOMHardware Bill of Materials(hardware)
✓ Detected
CBOMCryptography Bill of Materials
- Not detected
VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange
- Not detected
OBOMOperations Bill of Materials(configuration)
✓ Detected

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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Syngo Carbon Enterprise Access (VA40A) - Siemens Healthcare GmbH | ESL FDA AI Device Intelligence