AMRA Profiler
AMRA Medical AB • Radiology • 12/06/2018
Device Purpose
The AMRA Profiler is a medical software application that processes magnetic resonance imaging data to provide quantitative assessments of fat and muscle. It utilizes DICOM-compliant images and Region of Interest tools to measure parameters like liver fat fraction, T2*, and muscle volume, thereby assisting clinicians in diagnosis.
Summary
The AMRA Profiler is a software application designed as a magnetic resonance diagnostic tool for the non-invasive evaluation of fat and muscle. It operates by processing DICOM 3.0 compliant magnetic resonance image datasets acquired from compatible MR systems, facilitating the generation, display, and review of 2D medical image data, focusing on internal body structures including the liver. The AMRA Profiler incorporates quantification tools, such as Region of Interest (ROI) placements, to assess specific image regions and quantify liver tissue characteristics, including fat fraction in the liver, T2*, and muscle volume. These images and derived physical parameters, when interpreted by a trained clinician, are intended to yield information that may assist in diagnosis.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. What specific compatible MR Systems are validated for use with the AMRA Profiler, and are there any variations in performance or accuracy across different systems?; How does the AMRA Profiler's algorithm for quantifying liver fat fraction and T2* compare in accuracy and precision to other established methods or gold standards?; What is the range of muscle volume measurements the AMRA Profiler can reliably quantify, and are there specific muscle groups it is optimized for?; What level of training is required for a clinician to proficiently use the AMRA Profiler and accurately interpret its output for diagnostic assistance?; Are there any known limitations or patient characteristics that might affect the AMRA Profiler's performance in quantifying fat, muscle, or liver parameters?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (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 ML-BOM 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, SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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