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Quantum Perfusion Blood Oxygenator with Integrated AF and Sensor VT200-C1U and Quantum Perfusion Blood Oxygenator with Integrated AF and Sensor VT160-C1U are diffusion membrane oxygenators, designed to provide gas exchange during cardiac surgery requiring cardiopulmonary bypass, to measure blood pressure and temperature during the procedure. The integrated arterial filter provides additional protection against air and solid emboli. The devices are limited to 6 hours of use.

Quantum Perfusion Blood Oxygenator with Integrated AF VT200-C2U and Quantum Perfusion Blood Oxygenator with Integrated AF VT160-C2U are diffusion membrane oxygenators, designed to provide gas exchange during cardiac surgery requiring cardiopulmonary bypass and to measure temperature during the procedure. The integrated arterial filter provides additional protection against air and solid emboli. The devices are limited to 6 hours of use.

Devices are intended for adult patients.

Quantum Perfusion Blood Oxygenator devices (acronym VT-C) consist of an oxygenator with an integrated arterial filter.

The Quantum Perfusion Blood Oxygenator device is designed to provide gas exchange during cardiac surgical procedures requiring cardiopulmonary bypass for a maximum duration of 6 hours.

The device has microporous hollow fibers, made of Polypropylene (PP) and with high gas permeability, that allow gas exchange. The integrated arterial filter provides additional protection against air and solid emboli.

Blood enters the oxygenator through the blood inlet connector, flows through a blood chamber, touching the outer surface of a hollow fiber membrane, exits the oxygenator with the desired level of gas exchange.

The device is non-toxic, non-pyrogenic, sterilized by ethylene oxide and packaged in a single box.

All the device surfaces in contact with a phosphorylcholine-based biocompatible coating.

The provided text describes a 510(k) premarket notification for a medical device, the "Quantum Perfusion Blood Oxygenator," and its various models. This document focuses on demonstrating substantial equivalence to existing predicate devices, rather than proving that the device meets specific numeric acceptance criteria for performance in an AI/data science context.

Therefore, the information required to answer your specific questions about AI/ML acceptance criteria and a study proving those criteria (such as sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details, etc.) is not present in this document.

The document states:

• "No clinical data have been included in the current Traditional 510(k) submission to support substantial equivalence to legally marketed predicate devices."
• "No animal studies have been performed except for mandatory biocompatibility tests..."

Instead, the submission relies on non-clinical bench testing to demonstrate performance and safety characteristics, comparing them to the properties of the predicate devices. The non-clinical tests listed are related to the physical and functional aspects of the oxygenator itself (e.g., priming volume, pressure drop, gas transfer, mechanical integrity, etc.), not the performance of an AI algorithm.

Here's what can be extracted, albeit not directly answering your AI/ML specific questions:

1. A table of acceptance criteria and the reported device performance:
* The document implies acceptance criteria by stating "All testing passed by meeting the established requirements set for the devices." However, the specific numerical acceptance criteria for each non-clinical test are not explicitly detailed in this summary. Instead, it refers to standards like ISO 7199 and FDA Guidance for Cardiopulmonary Bypass Oxygenators.
* The "reported device performance" are implied to have met these unspecified criteria, but no quantitative results for these tests are presented in this summary.

2. Sample sizes used for the test set and the data provenance:
* Not applicable/Not provided. The document describes non-clinical bench testing, not a clinical study with a test set of patient data for an AI/ML algorithm.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
* Not applicable/Not provided, as there is no mention of an AI/ML algorithm requiring expert ground truth for its performance evaluation.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
* Not applicable/Not provided.

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. No AI component is described or evaluated in this medical device submission.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
* Not applicable/Not provided.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc):
* Not applicable/Not provided for an AI/ML context. The "ground truth" for the non-clinical tests would be the established engineering and biological standards and measurements.

8. The sample size for the training set:
* Not applicable/Not provided. No AI/ML model training is described.

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

In summary: This document is a regulatory submission for a physical medical device (blood oxygenator) seeking substantial equivalence based on its physical and functional characteristics and non-clinical bench testing. It does not involve AI or machine learning, and therefore the information you requested regarding AI/ML model evaluation is not present.

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