Aplio a550, Aplio a450, and Aplio a, Diagnostic Ultrasound System, Software V6.5
Canon Medical Systems Corporation • Radiology • 03/22/2022
Device Purpose
The Aplio a-series Diagnostic Ultrasound Systems, with Software V6.5, aim to enhance diagnostic capabilities across diverse clinical fields by integrating advanced multi-modal ultrasound imaging technologies and improved workflow solutions. This software iteration notably focuses on expanding quantitative imaging like Shear Wave Elastography and incorporating AI/ML for automated cardiac analysis, alongside specific enhancements for obstetric, liver, breast, and lung imaging.
Summary
The Aplio a550, Aplio a450, and Aplio a Diagnostic Ultrasound Systems, with Software V6.5, are mobile devices designed for visualizing human body structures and dynamic processes to aid in diagnosis across a wide spectrum of clinical applications. These applications include fetal, abdominal, intra-operative, pediatric, small organs, trans-vaginal, trans-rectal, cephalic, cardiac, vascular, transesophageal, musculo-skeletal, laparoscopic, and thoracic/pleural imaging. The systems utilize a variety of probes (flat linear, convex linear, sector array) operating at frequencies from approximately 2MHz to 20MHz and support numerous imaging modes such as B-mode, M-mode, Color Doppler, Pulsed Wave Doppler, Continuous Wave Doppler, Power Doppler, Shear Wave Elastography, Contrast Harmonic Imaging, and 3D/4D imaging. Software V6.5 introduces significant enhancements to existing functionalities, including improved network storage for raw data, secure DICOM data transfer via Tricefy Access, and expanded applications for Smart Body Mark (abdomen) and Shear Wave Elastography (SWE Hard). New presets for lung imaging, along with dedicated packages for liver and breast examinations, streamline workflow. Further refinements include SmartFetal2D for fetal heart analysis, MicroPure support in Reference mode, SWE integration in Smart Fusion, optimized OB 4D image quality, and improved OB measurement displays. The update also promotes the use of artificial intelligence and machine learning for automated contour tracing in cardiac functions like 2D Wall Motion Tracking and Auto Ejection Fraction, and expands marketing claims for liver analysis features (ATI, SWE) and MSK applications of SWE Hard based on published literature.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the 'Full-assist function' utilizing AI/ML in 2D Wall Motion Tracking and Auto Ejection Fraction compare in accuracy and efficiency to manual or semi-automated methods for left ventricular assessment?; What specific improvements in the 'SWE Hard' feature expand its upper limit and range, and what is the clinical impact of these expansions, particularly in musculoskeletal (MSK) applications referenced by publications?; Could you elaborate on the technical optimization of ROI sampling and filter application that led to improved Obstetric (OB) 4D image quality in Software V6.5?; What are the specific existing features bundled into the 'Liver Package Basic' and 'Breast Package,' and how do these packages enhance diagnostic workflow or utility for these specific examinations?; Regarding the 'Lung Preset,' what specific imaging parameters are optimized, and how does this preset improve the visualization or diagnostic capability for thoracic/pleural conditions compared to general ultrasound settings?
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, 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: SBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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