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The Cardeon® Aegis™ Catheter is intended to perfuse the aorta during open chest (sternotomy) procedures on cardiopulmonary bypass up to 6 hours.

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The provided text describes a 510(k) summary for the Cardeon® Aegis™ Catheter. It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a specific study report with performance metrics.

Here's an analysis of the information available, structured according to your request, with a necessary acknowledgement of missing data:

1. Table of Acceptance Criteria and Reported Device Performance

The submission for the Cardeon® Aegis™ Catheter does not explicitly state specific numerical acceptance criteria for performance. Instead, it relies on demonstrating "substantial equivalence" to predicate devices. The performance is assessed through "product testing" to show that the modified device "functions as safely and effectively as previously approved devices."

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

The document does not specify the sample size for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "product testing" without these specifics.

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

The submission does not mention the use of experts to establish ground truth for a test set in the context of this 510(k) summary. The evaluation appears to be based on engineering and biological testing, comparing the device against established performance characteristics of predicate devices, rather than an expert-driven assessment of diagnostic accuracy.

4. Adjudication Method for the Test Set

As no expert-based ground truth establishment is described, there is no mention of an adjudication method.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

No MRMC comparative effectiveness study is mentioned. This type of study is more common for diagnostic devices where human reader performance is a key metric. The Aegis Catheter is a surgical device, and its evaluation focuses on its physical and biological performance.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The concept of a "standalone" algorithm performance is not applicable here as the Aegis Catheter is a physical medical device, not an algorithm. The "Product Testing" mentioned would be considered the standalone performance evaluation of the device itself.

7. The Type of Ground Truth Used

The "ground truth" for the device's performance relies on engineering specifications, direct measurements of physical properties (e.g., flow rate), and biological compatibility testing to ensure it meets the requirements for its intended use and is comparable to predicate devices. It is not an "expert consensus," "pathology," or "outcomes data" in the typical sense for a diagnostic device. The ground truth essentially is that the device performs its intended mechanical and biological functions safely and effectively as demonstrated through testing.

8. The Sample Size for the Training Set

As this is a physical medical device and not an AI/ML algorithm that requires training data, there is no concept of a "training set" in this context.

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

Not applicable, as there is no training set for this device.

Summary of Device and Study Focus:

The K024058 submission for the Cardeon® Aegis™ Catheter is a 510(k) premarket notification. The primary goal of a 510(k) is to demonstrate substantial equivalence to a legally marketed predicate device. This typically involves showing that the new device has the same intended use, similar technological characteristics, and that any differences do not raise new questions of safety or effectiveness.

The "study" described is a series of "product testing" efforts, including biocompatibility, in vitro, and in vivo performance tests. These tests were conducted for both the original and modified Aegis devices to confirm that the modified device's performance aligns with the original and other marketed devices. The level of detail on specific test parameters, sample sizes, and quantitative results is typical for a 510(k) summary (i.e., often not fully elaborated in the public summary document). The FDA's decision to grant substantial equivalence indicates that the information provided (which would have been more detailed in the full submission, not just the summary) was sufficient to meet their requirements.

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The Cardeon® Aegis™ Catheter is intended to perfuse the aorta during open chest (sternotomy) procedures on cardiopulmonary bypass up to 6 hours.

Not Found

The provided text is a 510(k) summary for the Cardeon Aegis Catheter. This type of submission is for medical devices and focuses on demonstrating substantial equivalence to a predicate device, not on presenting detailed acceptance criteria and a human-readability study as would be typical for AI/ML device evaluations.

Therefore, most of the requested information regarding acceptance criteria, sample sizes for test and training sets, ground truth establishment, expert qualifications, adjudication methods, and MRMC studies is not available or applicable in this document. This document describes a traditional medical device (a catheter), not a software or AI/ML device, so the requested format does not align with the information provided.

However, I can extract the following based on the available text:

1. A table of acceptance criteria and the reported device performance: This information is not explicitly provided in the format of a table with specific performance metrics and acceptance criteria. The submission states that "Results of product testing demonstrated that the Aegis Catheter functions as safely and effectively as predicate devices." This is a general statement of performance rather than specific, quantifiable acceptance criteria.

2. Sample sizes used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable/not provided. The submission refers to "product testing," which included "biocompatibility, in vitro and/or in vivo performance." However, specific sample sizes, study methodologies (retrospective/prospective), or data provenance are not detailed as they would be for an AI/ML device's test set.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience): Not applicable/not provided. 'Ground truth' in the context of an AI/ML device typically refers to expert-labeled data. For a physical device like a catheter, performance is assessed through engineering tests and potentially animal or human clinical trials, where 'ground truth' doesn't fit the same paradigm.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable/not provided. This refers to consensus-building among experts for labeling data, which is not relevant for this type of device submission.

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 applicable/not provided. MRMC studies are specific to AI-assisted diagnostic or interpretive devices, which this catheter is not.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable/not provided. This refers to AI algorithm performance without human intervention, which is irrelevant for a physical medical device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. As mentioned, the concept of 'ground truth' in this context doesn't align with AI/ML device evaluation. The assessment of this catheter's safety and effectiveness would rely on engineering specifications, biocompatibility testing results, and comparison to predicate devices' established safety and performance profiles.

8. The sample size for the training set: Not applicable/not provided. This device is not an AI/ML model, so there is no "training set."

9. How the ground truth for the training set was established: Not applicable/not provided.

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