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The PreView® Forward-Looking IVUS System is indicated for use to facilitate the intraluminal placement of guidewires in the peripheral vasculature prior to further percutaneous intervention and to support guidewires in accessing discrete regions of the peripheral vasculature, to assess vessel morphology, assess the position of the catheter tip within the vessel lumen, and to facilitate placement and exchanges of guidewires and other interventional devices compatible with 0.0 14" guidewire lumens. The Preview® Forward-Looking IVUS System is designed as an adjunct to conventional angiographic procedures to provide a forward-looking image of the vessel lumen and wall structures.

The PreView Forward-Looking IVUS System is not indicated for use for imaging with the exposed rotating tip inside a stent. This device is not indicated for use in coronary or cerebral vessels.

The PreView® Forward-Looking IVUS System consists of the PreView® catheter, PIMf, FL.IVUS Software and Volcano s5TM System. The PreView® Catheter is a single use disposable device with a disposable single use motor for rotation of the catheter. The catheter is 135cm in length and connects to a PIM (Patient Interface Module; PIMf) which contains the electronics. The PIMf translates the echo data and sends it to the Volcano s5TM System for display on the system monitor.

The Volcano PreView® Forward-Looking IVUS System is largely a hardware-based device. No specific acceptance criteria or a dedicated study proving performance against such criteria are explicitly detailed in the provided documentation. The FDA 510(k) summary focuses on demonstrating substantial equivalence to predicate devices through various technical verification and validation activities.

However, based on the information provided, we can infer how acceptance criteria are addressed:

1. Table of Acceptance Criteria and Reported Device Performance:

Since no explicit quantitative acceptance criteria are given, the "reported device performance" section focuses on the completion of required tests to ensure the device functions as intended and is compatible with the existing Volcano s5TM System.

2. Sample Size Used for the Test Set and the Data Provenance:

The document does not specify sample sizes for any test sets in the context of clinical or image-based performance evaluation. The listed tests (Software V&V, Packaging, Electrical Safety, EMC) are typically engineering validation tests that don't involve clinical "test sets" in the same way an AI algorithm would. Data provenance (country of origin, retrospective/prospective) is also not applicable or provided for these types of engineering tests.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts:

This information is not provided as the submission focuses on engineering and system compatibility, not on a clinical performance study requiring expert ground truth for image interpretation or diagnosis.

4. Adjudication Method for the Test Set:

This information is not provided and is not applicable given the nature of the validation tests mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC comparative effectiveness study was not conducted or reported in this 510(k) summary. The device's validation focuses on its technical functionality and compatibility with the existing system, not on a comparative study of human reader performance with or without AI assistance.

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

This device is not an AI algorithm. It is a medical imaging system. Therefore, a "standalone algorithm performance" study is not applicable. The device's primary function is to provide images for human interpretation.

7. The Type of Ground Truth Used:

For the engineering validation tests conducted (Software V&V, Packaging, Electrical Safety, EMC), ground truth is established through:

• Engineering specifications and standards: Compliance with established industry standards for electrical safety, EMC, and software quality.
• Functional requirements: Verification that the hardware and software components perform their designed functions correctly.

There is no mention of expert consensus, pathology, or outcomes data used as ground truth in this context, as these are not relevant to the types of tests reported.

8. The Sample Size for the Training Set:

This information is not applicable as the device is not an AI/machine learning system that requires a "training set."

9. How the Ground Truth for the Training Set Was Established:

This information is not applicable as the device is not an AI/machine learning system.

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