HeartFlow Analysis
HeartFlow, Inc. • Cardiovascular • 01/08/2021
Device Purpose
The HeartFlow Analysis is a software device that provides a non-invasive, quantitative functional evaluation of coronary artery disease by analyzing CT DICOM data. It achieves this by creating a patient-specific 3D model of the coronary arteries and employing advanced physiological simulation, including a "Gen3 Solver", to calculate FFRct and other hemodynamic parameters, thereby aiding clinicians in diagnosis and treatment strategy.
Summary
The HeartFlow Analysis is a non-invasive software medical device designed for the clinical quantitative and qualitative analysis of coronary artery disease in clinically stable symptomatic patients. It processes previously acquired Computed Tomography (CT) DICOM data to generate a 3D computer model of the patient's coronary arteries. Utilizing this model, the software performs physiological simulations to compute FFRct, a mathematically derived quantity representing fractional flow reserve, along with other simulated hemodynamic data such as blood flow, pressure, and velocity. These outputs, presented in graphic and text formats, are intended to aid qualified clinicians in the assessment and treatment planning of coronary artery disease. The device is intended to support the functional evaluation of coronary artery disease and is to be used by clinicians in conjunction with the patient's clinical history and other diagnostic information. Its core technology includes semi-automated extraction of anatomical data from CT images, centerline detection, lumen boundary determination, and the ability to modify the anatomical model. The FFRct v3 iteration employs a "Gen3 Solver" with updated calculations for total coronary baseline flow and flow distribution. Validation studies for the device included stress testing and repeatability testing, with evaluations performed using previously acquired diagnostic images from clinical trials, ensuring the device's acceptability for its intended use.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. What specific algorithmic changes in the "Gen3 Solver" differentiate its flow and distribution calculations from the "Gen2 Solver," and how do these changes impact the accuracy or clinical utility of FFRct values?; How does the exposure of interim calculations, such as mass and volume, in FFRct v3 enhance a clinician's ability to assess model accuracy or understand the basis of the FFRct computation?; What were the specific quantitative results from the stress testing and repeatability testing for FFRct v3, particularly concerning the performance of the Gen3 solver compared to its predicate?; Given that the software analyzes "static coronary CT images," what are the known limitations in simulating dynamic physiological conditions, such as maximal hyperemia or varying cardiac outputs, and how are these addressed or accounted for in the FFRct calculation?; How does the semi-automated tool for extraction of anatomic data handle challenging cases, such as significant calcification, motion artifacts, or complex bifurcations in CT images, and what is the typical inter-observer variability in the resulting FFRct values after clinician review and potential model modification?
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, 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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