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The CROSSER® System is indicated in coronary arteries to facilitate the intra-luminal placement of conventional guidewires beyond chronic total occlusions.

The CROSSER® System consists of a re-usable electronic Generator, Foot Switch, high-frequency Transducer, and single-use CROSSER 14 Over the Wire Catheter.

The CROSSER Catheter is connected to the electronic Generator through the Transducer. The Foot Switch is used to activate the system. The Generator and Transducer convert AC power into high frequency mechanical vibrations which are propagated through a Nitinol core wire to the Stainless steel tip of the CROSSER Catheter. The main body of the catheter is constructed from Pebax and a hydrophilic coating which covers the distal end of the catheter.

The provided text describes a medical device, the FlowCardia CROSSER 14 Over the Wire Catheter, and its 510(k) submission for demonstrating substantial equivalence to a predicate device. However, it does not describe an AI/ML-driven device or a study involving AI for diagnostic or predictive purposes. Therefore, most of the requested information regarding AI acceptance criteria, training/test sets, expert ground truth, MRMC studies, or standalone algorithm performance is not applicable based on the provided text.

The document primarily focuses on physical testing and substantial equivalence to a physical predicate device, not an AI algorithm.

Here's a breakdown of the information that can be extracted from the provided text, and where the requested information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text generally states that the device met acceptance criteria, but it does not detail specific quantitative acceptance criteria or their corresponding performance results in a tabular format as would be typical for an AI/ML device. Instead, it lists functional tests and a general conclusion of similarity to the predicate device.

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

• Test Set Sample Size: Not applicable. This document describes physical device testing, not a dataset for an AI/ML model. The tests listed (Tensile Strength, Torque Strength, etc.) would involve a sample of physical catheters, but the exact number for each test is not specified.
• Data Provenance: Not applicable. This is not a study using clinical data or images. The "data" comes from bench testing of the physical device.

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

Not applicable. Ground truth as typically defined for AI/ML studies (e.g., expert consensus on medical images) is not relevant here. The "ground truth" for the physical tests would be established by engineering specifications and industry standards.

4. Adjudication method for the test set

Not applicable. This is not a study requiring adjudication of expert opinions or classifications.

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. This document does not describe an AI device or a study involving human readers.

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

Not applicable. This document is about a physical medical device, not an algorithm.

7. The type of ground truth used

For the physical tests, the "ground truth" would be engineering specifications, established testing protocols, and comparison to the predicate device's measured performance in similar tests.
(e.g., "Tensile Strength" would be measured by a machine to a specified breaking point).

8. The sample size for the training set

Not applicable. There is no AI/ML training set in this context.

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

Not applicable. There is no AI/ML training set in this context.

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