syngo.via MI Workflows, syngo MBF
Siemens Medical Solutions USA, Inc. • Radiology • 11/18/2020
Device Purpose
syngo.via MI Workflows VB50A is an advanced image processing software suite designed to enhance diagnostic and treatment planning capabilities by providing tools for multi-modal medical image viewing, manipulation, quantification, and comparison, particularly in oncology, cardiology, and neurology. The system employs specialized modules like Scenium and syngo MBF, along with newly introduced automated and quantitative features, to improve workflow efficiency and the precision of functional and anatomical assessments derived from PET, SPECT, CT, and MR imaging.
Summary
syngo.via MI Workflows VB50A is a software-only medical device designed for advanced medical image processing. It enables healthcare professionals to view, manipulate, quantify, analyze, and compare medical images from single or multiple modalities, including positron emission tomography (PET), nuclear medicine (NM), computed tomography (CT), and magnetic resonance (MR). The software supports diverse clinical applications in oncology, cardiology, neurology, and organ function assessment, and its outputs can also aid in radiotherapy treatment planning, operating on the Siemens syngo.via software platform. The system incorporates specialized components such as Scenium for neurological image analysis—assisting in the visual evaluation, assessment and quantification of pathologies like dementia, movement disorders (e.g., Parkinson’s), and seizure analysis (e.g., Epilepsy) through database comparison, striatal and cortical analysis, and subtraction workflows—and syngo MBF for cardiology, providing quantitative myocardial blood flow measurements from dynamic PET images (Rubidium-PET and Ammonia-PET). Key modifications in version VB50A include new features such as Auto Lung 3D, Dynamic Summing, automatic layouts, normalization by rate-pressure product for cardiac studies, cardiac masking, updates to third-party software, and a new normals database for FDOPA in neurology, all aimed at improving image processing accuracy, quantitative analysis, and overall usability for clinicians.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the 'Auto Lung 3D' feature specifically improve upon previous lung segmentation or analysis methods within the syngo.via MI Workflows?; What is the clinical impact of 'Normalization by Rate-Pressure Product' in syngo MBF, and how does it refine myocardial blood flow quantification compared to methods without this normalization?; Can the 'Normals Database for FDOPA' within the Scenium module be expanded or customized for different patient populations or specific research cohorts beyond its initial implementation?; What validation methodologies were employed to confirm the accuracy and reliability of the new automated quantification features, such as 'Automatic Layouts' and 'Auto Ranges'?; How does the 'harmonization of SUV (PET) across different PET systems' feature technically account for inherent variabilities in scanner calibration, acquisition protocols, and reconstruction algorithms to ensure consistent quantitative results?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class C (software safety classification); Authorized before §524B enforcement
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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, SaaSBOM 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: HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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