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CardIQ Flow is an aiding tool for the clinicians to perform analysis of stationary, dynamic, or gated cardiac position emission tomography (PET) images. The measurements include perfusion, end-diastolic volumes, stroke volume, ejection fraction, myocardial mass, and transient ischemic dilatation. Also included is a feature that enables clinicians to visualize reformatted data and make a comparison between stress and rest series. Software is indicated for determining regional and global absolute rest and stress myocardial perfusion in cc/min/g, Coronary Flow Reserve and their combination into the Coronary (CFC) Map in patients with suspected or known coronary artery disease (CAD) in order to assist clinical interpretation of PET perfusion images by quantification of their severty. It is intended for use by trained professionals, such as nuclear medicine or nuclear cardiology physicians, or cardiologists with appropriate training. The clinician remains ultimately responsible for the final assessment and diagnosis based on standard practices, clinical judgment and interpretation of cardiac images or quantitative data.

The basis for this submission is the introduction of a new software device, CardIQ Flow which integrates the functionalities of the predicate devices HeartSee and FullCard Analysis for the display and analysis of Cardiac PET images. It is built within the framework of the Volume Viewer (K041521) 3D platform, intended to aid clinicians in assessing the myocardial perfusion, myocardial perfusion, myocardial blood flow and wall motion. It is used for the evaluation of patients with known or suspected coronary artery or ischemic heart disease.

This application can be used for:

· Reformatting axial data to the standard axis of the heart. Axial data may have been reconstructed using iterative or FBP algorithms with scatter and attenuation correction, if available.

• Analyzing the myocardial perfusion by the Vertical Long Axis (VLA), Horizontal Long Axis (HLA) and Short Axis (SA) obliques generated from the selected input data.

· Comparing myocardial perfusion in rest and stress studies as well as metabolism in viability studies.

• · Viewing wall motions via synchronized gated beating slices.
• · Investigating the entire left ventricle in one 2D Polar Plot that displays all short axis slices.
• · Comparing myocardial perfusion of corrected and uncorrected datasets.

· Calculation and evaluation of Myocardial Blood Flow (MBF), Coronary Flow Reserve (CFR), and Coronary Flow Capacity (CFC).

· Printing a report designed for referring physicians.

Here's a breakdown of the acceptance criteria and study information for CardIQ Flow based on the provided document:

1. Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria for device performance. Instead, it focuses on the device performing "substantially equivalent" to its predicates and successfully completing design control activities. The technological comparison table highlights similarities in workflow and measurements.

2. Sample Size Used for the Test Set and Data Provenance:

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "performance testing (Verification, Validation)" but does not provide details about the datasets used in these tests.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

The document does not provide information on the number of experts used or their qualifications for establishing ground truth for any test sets.

4. Adjudication Method for the Test Set:

The document does not specify any adjudication method used for the test set.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it quantify any effect size of human readers improving with AI vs. without AI assistance. The focus is on demonstrating substantial equivalence to existing devices, not on comparing performance with and without AI assistance for human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

The document implies a standalone performance assessment through "performance testing (Verification, Validation)" and by stating the device "performs substantially equivalent to the predicate devices." The nature of the comparison to predicates (HeartSee and FullCard Analysis, which are also software tools for analysis) suggests that CardIQ Flow's computational and analytical outputs were directly compared. However, it does not explicitly detail a dedicated "standalone" study separate from human interaction, but rather the software's ability to produce quantitative measurements and visualizations.

7. Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for performance testing (e.g., expert consensus, pathology, outcomes data). Given the device's function in quantifying myocardial perfusion and other cardiac parameters based on PET images, it's highly probable that ground truth would involve comparisons to established clinical methods, potentially expert interpretation, or potentially phantom studies for validation of quantitative accuracy. However, this is not detailed.

8. Sample Size for the Training Set:

The document does not provide information on the sample size used for the training set.

9. How the Ground Truth for the Training Set Was Established:

The document does not provide information on how the ground truth for the training set was established.

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