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The RotaFlow Centrifugal Pump is indicated as a component of the extracorporeal circuit for pumping liquid matter e.g. blood and can be used in conjunction with the RotaFlow Console. The utilization period of this device is restricted to six hours. The device is not designed or intended for use except as indicated.

The RotaFlow Centrifugal Pump is a non-occlusive pump. The pump has a spinning rotor with flow channels which imparts rotary motion to incoming liquid, directing it through a spiral housing to the outflow port.

This submission (K090515) is for a medical device called the MAQUET RotaFlow Centrifugal Pump with Softline Coating. It's important to note that this 510(k) summary does not contain acceptance criteria or a study proving the device meets those criteria in the way you've outlined for AI/software-driven devices.

This is a premarket notification for a Class III physical medical device (a centrifugal pump for cardiopulmonary bypass). The submission focuses on demonstrating substantial equivalence to existing legally marketed predicate devices, not on showing performance against specific, quantifiable acceptance criteria typically associated with software or AI performance.

Therefore, many of your specific questions are not applicable to the information provided in this 510(k) summary. I will address the relevant sections and explain why others cannot be answered from the provided text.

1. A table of acceptance criteria and the reported device performance

This information is not provided in the 510(k) summary for K090515. For physical devices like this, the "performance" demonstrated for substantial equivalence typically involves engineering tests (e.g., flow rates, pressure handling, durability, biocompatibility) rather than quantifiable metrics like sensitivity or specificity seen in diagnostic AI. The summary states that "Performance" was evaluated, but it does not present specific criteria or results in a table.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided. As this is a physical device, "test sets" in the context of data points for algorithm evaluation are not relevant here. The evaluation would involve physical prototypes or manufactured units of the pump.

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)

This information is not provided and is not applicable to a physical medical device submission like this. Ground truth, in the context of expert consensus, is typically for diagnostic interpretation, not for evaluating the mechanical function of a pump.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided and is not applicable.

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

This information is not provided and is not applicable. This type of study relates to the performance of diagnostic AI with human readers, not a physical pump.

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

This information is not provided and is not applicable. There is no algorithm discussed for diagnostic or interpretative purposes in this submission.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not provided and is not applicable in the way you've described. For a physical pump, "ground truth" might refer to engineering specifications, validated test methods for flow, pressure, material integrity, and biocompatibility standards. The submission highlights that "Integrity", "Performance", "Biocompatibility", and "Sterility" were evaluated, implying various testing methodologies were used, but details are not given.

8. The sample size for the training set

This information is not provided and is not applicable. There is no training set for an AI/ML algorithm in this submission.

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

This information is not provided and is not applicable.

Summary of Relevant Information from the K090515 Submission:

• Device Name: RotaFlow Centrifugal Pump with Softline Coating
• Submission Type: 510(k) Premarket Notification
• Purpose of Study/Evaluation: To demonstrate substantial equivalence to legally marketed predicate devices.
• Predicate Devices:
  • RotaFlow Centrifugal Pump with BIOLINE Coating (K080470) - for the pump design and function.
  • QUADROX-i Adult microporous membrane Oxygenator with and without integrated Arterial Filter with Softline Coating (K082117) - for the Softline Coating material.
• Key Differences from Predicate: The only stated difference from the primary predicate is the coating (Softline instead of BIOLINE). The Softline coating itself is identical to a coating already approved in another predicate device.
• Evaluated Areas (for demonstrating substantial equivalence):
  • Integrity
  • Performance
  • Biocompatibility
  • Sterility
• Conclusion: The data demonstrated that the RotaFlow Centrifugal Pump with Softline Coating is substantially equivalent to the named predicate devices.

In essence, this 510(k) is for a manufacturing change (a new coating) on an already cleared device, leveraging the prior approval of both the pump design and the specific coating material on other devices. It does not involve AI or software development that would require the kind of performance metrics and study designs you've detailed.

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