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The FLASH Mini Ostial System is indicated for balloon dilatation of the stenotic portion of a coronary artery or bypass graft for the purpose of improving myocardial perfusion. The FLASH Mini Ostial System is also indicated for the post delivery expansion of balloon expandable stents within the coronary vasculature.

The FLASH Mini Ostial System is a .014" guidewire-compatible, rapid exchange (RX) angioplasty balloon catheter with proximal anchoring and a working length of 135cm. The FLASH Mini Ostial System uses a dual balloon design that features a compliant anchoring balloon, which prevents distal migration of the balloon during angioplasty. The second semicompliant higher-pressure balloon allows for luminal dilatation of de novo lesions and post deployment stent expansion.

The provided text describes a 510(k) premarket notification for the FLASH Mini Ostial System, a PTCA Catheter. The document focuses on demonstrating substantial equivalence to a predicate device through performance data and biocompatibility testing. It does not include details about a study evaluating a device's performance against acceptance criteria using a test set, expert ground truth, or human readers, as would be common for AI/ML-based medical devices.

Therefore, many of the requested categories are not applicable to the information provided in this document.

Here's a breakdown of what can be extracted based on the provided text:

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

The document states: "All test results demonstrate that the FLASH Mini Ostial System meets the established product specifications." and "All test results demonstrated that the FLASH Mini Ostial System meets all predetermined design verification and validation acceptance criteria necessary to verify safe and consistent performance of the device for its Indications for Use."

However, the specific quantitative acceptance criteria (e.g., "Balloon Crossing Profile must be < X mm") and corresponding reported performance values are not explicitly listed in a table format within the provided text. Instead, a list of performance bench tests that were conducted is given.

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 in the document. The performance data described are in-vitro bench tests, not clinical studies with human participants or data sets.

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 is not applicable as the described tests are in-vitro bench tests, not requiring expert ground truth for interpretation of diagnostic images or clinical outcomes.

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

This is not applicable as the described tests are in-vitro bench tests, not requiring adjudication of diagnostic interpretations.

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 is not applicable. The device is a physical medical device (catheter), not an AI/ML diagnostic or assistive technology.

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

This is not applicable. The device is a physical medical device (catheter), not an AI/ML algorithm.

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

The "ground truth" for the performance tests would be the engineering specifications and physical measurements of the device components. For biocompatibility, it would be the established safety standards and laboratory test results. No expert consensus, pathology, or outcomes data are mentioned for establishing ground truth for these types of tests.

8. The sample size for the training set

This is not applicable. The document describes a physical medical device. There is no mention of a "training set" in the context of machine learning.

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

This is not applicable. There is no mention of a "training set" or its ground truth establishment in this document.

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