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CardIQ Analysis III is a CT image analysis software package, which allows the visualization of 2D and 3D medical image data of the heart derived from DICOM 3.0 compliant CT scans for the purpose of cardiovascular disease assessment. It provides functionally for 2D/3D rendering, assessment of calcified and non-calcified plaque to determine the densities of the plaque within a coronary artery, ventricular function of the heart, and measurement tools to detect coronary artery stenosis. This product can be used to aid a trained physician for to process, render, review, archive, print and visualizing cardiac anatomy and coronary vessels. CardIQ Analysis III will run on the AW workstation, scanner operator console and PACS system.

CardIO Analysis III is a post processing software option that can be used in the analysis of CT angiographic images to display structures of the heart in a MIP, reformat or volume rendering view. When the heart is displayed the software has the ability to measure the diameter of the vessel or hounsfield units within a coronary arteries to determine the size of a vessel or plaque density within a vessel. Functional parameters of the heart can also be determined when images of end systole and end diastole are present. Diarneters, densities, functional parameters and images can all be printed to reports or saved to the AW workstation. It is a software option for the GE family of LightSpeed multi-slice CT scanners.

The provided text for K041267 describes a device called CardIQ Analysis III, a post-processing software option for analyzing CT angiographic images of the heart. However, it does not include specific information regarding acceptance criteria, a dedicated study proving device performance against those criteria, or details such as sample sizes, ground truth establishment, expert qualifications, or comparative effectiveness studies.

The document primarily focuses on establishing substantial equivalence to previously cleared predicate devices (CardIQ Analysis II and CardIQ Function) based on functional features and safety. It states that "The CardIQ Analysis III does not result in any new potential safety risks and performs as well as devices currently on the market." This suggests that the primary "proof" of meeting acceptance criteria for this 510(k) submission relies on the established performance and safety of its predicate devices, rather than a new, detailed performance study with explicit acceptance criteria.

Therefore, many of the requested details cannot be extracted from the provided text.

Here's a breakdown of what can be inferred or directly stated, and what is missing:

1. Table of acceptance criteria and reported device performance:
   • Acceptance Criteria: Not explicitly stated in terms of quantitative metrics (e.g., sensitivity, specificity, accuracy, measurement error). The "acceptance criteria" here implicitly refer to demonstrating equivalence in functionality and safety to predicate devices.
   • Reported Device Performance: No quantitative performance metrics are provided for CardIQ Analysis III itself. The performance is stated to be "as well as devices currently on the market," referring to its predicates.

2. Sample size used for the test set and the data provenance:

   • Sample size: Not specified.
   • Data provenance: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not specified.

4. Adjudication method for the test set:

   • Not specified.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • Not mentioned. The document focuses on the device's standalone features as a visualization and analysis tool, not on its impact on human reader performance in an MRMC study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • The device is a standalone software package for analysis and visualization. However, no specific "standalone performance study" with quantitative metrics is described beyond the assertion that it performs "as well as" its predicates. The device's "performance" is inherently linked to its ability to process, render, and display data for a "trained physician," making the "human-in-the-loop" an integral part of its intended use.

7. The type of ground truth used:

   • Not specified. Given the nature of the device (analysis and visualization features consistent with predicates), an explicit "ground truth" for a performance study is not detailed in this submission. Its equivalence to predicates likely implies the functionality was deemed acceptable based on engineering verification and validation against specified requirements derived from the predicate devices, rather than a clinical ground truth study.

8. The sample size for the training set:

   • Not applicable as this is a 2004 510(k) for a software update to an existing product line. It details post-processing software, not a machine learning or AI algorithm that would typically require a "training set" in the modern sense. The term "training set" for AI/ML algorithms is not relevant to this historical submission for a traditional software device.

9. How the ground truth for the training set was established:

   • Not applicable (see point 8).

Summary of Study Information Provided:

The provided document does not describe a specific clinical or performance study for CardIQ Analysis III with defined acceptance criteria. Instead, the submission relies on demonstrating substantial equivalence to existing predicate devices (CardIQ Analysis II, K020796; and CardIQ Function, K013422). The "study" implicitly involves a comparison of the functional features and safety considerations with those of the predicate devices. The conclusion that "CardIQ Analysis III does not result in any new potential safety risks and performs as well as devices currently on the market" serves as the proof for meeting the implied "acceptance criteria" of equivalence. The underlying data and studies for the predicate devices would have established their performance, which is then extrapolated to the new device through the equivalence claim.

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