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This product is intended for use in the percutaneous introduction of catheters. Not for use in the coronary arteries or intracranial vessels.

The ASAHI Silverway consists of a one-piece core wire and a coil assembly that extends the entire length of the device. The coil assembly consists of an inner coil and an outer coil, soldered to the core wire. In addition, coatings are applied on the surface of the ASAHI Silverway. The distal and proximal sections are coated with silicone. The intermediate section is coated with hydrophilic coating. The ASAHI Silverway has a nominal outer diameter of 0.89mm (0.035in) and is available in various lengths from 150cm to 300cm and tip shapes.

This document describes the premarket notification (510(k)) for the ASAHI® Silverway® guidewire. The acceptance criteria and study details are focused on non-clinical performance given the type of device and the 510(k) pathway, which establishes substantial equivalence rather than independent safety and effectiveness.

Here's a breakdown of the requested information based on the provided text:

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

The document states that the ASAHI Silverway "met all acceptance criteria" and "performed similarly to the predicate devices." While specific numerical acceptance criteria (e.g., minimum tensile strength in Newtons, maximum torque to twist in degrees) are not explicitly listed in the public summary, the general categories of tests performed indicate the areas for which acceptance criteria would have been established.

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

• Sample Size: The document does not explicitly state the specific number of units tested for each non-clinical test. It generally refers to "non-clinical laboratory testing."
• Data Provenance: The tests were "non-clinical laboratory testing" presumably conducted by or for ASAHI INTECC CO., LTD. Given the company's address (Japan), the testing was likely performed in Japan or by a qualified lab contracted by them. The studies are by nature prospective in that new guidewires were manufactured and then tested according to predefined protocols.

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

This section is not applicable to this type of regulatory submission. For a guidewire, "ground truth" is typically defined by engineering specifications, material properties, and performance benchmarks established through industry standards (e.g., ISO, ASTM) and comparison to predicate devices, rather than expert human interpretation of complex data (like medical images).

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

Not applicable. As this is non-clinical laboratory testing against pre-defined engineering and material standards, there is no need for expert adjudication in the way it might be applied to, for example, classifying medical images. Test results are objective measurements.

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 device is a medical guidewire, not an AI/imaging device. Therefore, no MRMC study or AI assistance evaluation would be relevant or expected.

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

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

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

The "ground truth" for this device's performance is based on:

• Engineering specifications and design requirements: Did the device meet its designed dimensions, material properties, and functional characteristics?
• International standards: Adherence to relevant ISO (e.g., ISO 11070 for catheter guidewires, ISO 10993 for biocompatibility) and ASTM standards.
• Performance of predicate devices: Substantial equivalence is demonstrated by performing "similarly to the predicate devices." The predicates themselves would have established a benchmark for acceptable performance.

8. The sample size for the training set

Not applicable. This is a physical medical device, not a machine learning model, so there is no training set in the AI sense. The "training" in manufacturing comes from process validation and quality control, but not a data-driven model training.

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

Not applicable for the same reason as point 8.

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