HeartFlow FFRct Analysis
HeartFlow, Inc. • Cardiovascular • 08/15/2019
Device Purpose
HeartFlow Analysis utilizes patient-specific coronary Computed Tomography Angiography data to create 3D models and simulate blood flow for the non-invasive functional assessment of coronary artery disease. By employing computational fluid dynamics to calculate FFRCT values and offering a planner feature for evaluating modified anatomies, the software provides clinicians with quantitative and qualitative insights to aid in the evaluation and assessment of coronary arteries.
Summary
HeartFlow Analysis is a coronary physiologic simulation software designed for the clinical quantitative and qualitative analysis of previously acquired Computed Tomography (CT) DICOM data. It is intended for use in clinically stable symptomatic patients diagnosed with or suspected of having coronary artery disease. The system generates a mathematically derived quantity known as FFRCT, which is computed from simulated pressure, velocity, and blood flow information obtained from a 3D computer model created from static coronary CT images. This FFRCT analysis supports the functional evaluation of coronary artery disease. The software constructs a patient-specific 3D anatomical model of the coronary arteries and applies principles of computational fluid dynamics (CFD) to simulate blood flow and calculate FFRCT values. These results, combining anatomical displays with functional information through graphics and text, are provided to qualified clinicians. A 'planner feature' allows users to explore combinations of the anatomic FFRCT model and an idealized model, running a reduced order CFD solution to further aid in the assessment. Clinicians are intended to use the HeartFlow FFRCT results in conjunction with clinical history, symptoms, other diagnostic tests, and their professional judgment to evaluate and assess coronary arteries, assisting in diagnosis and treatment planning.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. Regarding the 'planner feature,' how does the 'reduced order CFD solution' for combined anatomic and idealized models compare in accuracy and computational time to the full CFD solution on the original anatomic FFRct model?; What specific validation was performed to demonstrate that the 'Delta-solver' used with modified anatomies (combinations of anatomic and idealized models) produces FFRCT results equivalent to the standard FFRCT solver across diverse vessel and lesion morphologies?; How does the HeartFlow Analysis software handle variability in input cCTA image quality and acquisition parameters, and what is the quantified impact of such variability on the accuracy of the FFRCT values?; What are the underlying algorithms and assumptions used to generate the 'idealized model' from the patient-specific anatomic model in the planner feature, and how do these assumptions affect the predicted outcomes of virtual interventions?; Could you elaborate on the range of 'vessel and lesion morphologies' tested during the software validation, particularly for the planner feature, and what were the performance metrics in complex scenarios such as bifurcations or tandem lesions?
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 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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