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The NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheters are designed for use in the evaluation of vascular morphology in blood vessels of the coronary and peripheral vasculature by providing a cross-sectional image of such vessels. This device is not currently indicated for use in cerebral vessels.

The NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheter is designed for use as an adjunct to conventional angiographic procedures to provide an image of the vessel lumen and wall structures.

The NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheter incorporates a cylindrical ultrasound transducer array. The array radiates acoustic energy into the surrounding tissue and detects the subsequent echoes. The information from the echoes is used to generate real-time images of the coronary and peripheral vessels.

The NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheter utilizes an internal lumen that allows the catheter to track over the 0.014" (0.36 mm) guide wire exits from the guide wire lumen approximately 24 cm proximal to the catheter is introduced percutaneously or via surgical cutdown into the vascular system.

Three 1 mm-long radiopaque markers are incorporated on the internal lumen positioned 10 mm apart from distal edge to distal edge, starting 10 mm from the proximal edge of the scanner marker tube normally visible under fluoroscopy.

The Eagle Eye catheter may only be used with the Volcano s5 Series or CORE Series of Systems Operator's Manual. This catheter will not operate if connected to any other imaging system.

A hydrophilic coating is applied externally to a distal portion of the catheter.

The provided document describes the FDA 510(k) clearance for the NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheter. The document details the device, its intended use, and the testing conducted to demonstrate substantial equivalence to predicate devices.

However, the information provided does not include acceptance criteria or a study directly proving the device meets specific performance metrics in terms of diagnostic accuracy or clinical effectiveness in the way a typical AI/ML medical device would. This is because the device described is an intravascular ultrasound (IVUS) catheter, which is a hardware device used to acquire images, not an algorithm that interprets images or makes diagnoses.

The "studies" mentioned are primarily bench and laboratory testing to demonstrate the functionality, safety, and effectiveness of the reprocessed catheter, ensuring it performs identically to a new, original catheter. These tests focus on aspects like cleaning, sterilization, mechanical characteristics, system compatibility, and biocompatibility, which are typical for reprocessed medical devices.

Therefore, many of the requested categories (like sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance of an algorithm, and training set details) are not applicable to this type of device and its regulatory submission.

Here's a breakdown based on the available information, with explanations for why certain categories are not present:

Acceptance Criteria and Device Performance (Based on available information)

Study Details and Data Provenance (Not Applicable in the typical sense for an AI/ML device)

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

   • Not applicable for diagnostic performance as an algorithm. The "test set" here refers to the actual reprocessed catheters undergoing quality control. The document does not specify exact numbers of catheters tested for each validation section, but states "bench and laboratory testing was conducted," implying a sufficient sample size for these validation types. Data provenance is internal to Northeast Scientific, Inc.'s reprocessing and testing procedures.

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

   • Not applicable. Ground truth for a diagnostic algorithm is not generally established in this context. The "ground truth" for these tests would be established by validated test methods, reference standards, and specifications (e.g., a specific tensile strength, a certain level of microbial reduction, or successful image acquisition when connected to a compatible system). These are typically verified by qualified engineers and technicians, not clinical experts for diagnostic accuracy.

3. Adjudication method for the test set:

   • Not applicable. Not a diagnostic study requiring expert adjudication. Test results are compared against predetermined specifications and validated methods.

4. 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 an IVUS catheter, not an AI or imaging interpretation algorithm. Therefore, no MRMC study, AI assistance performance, or human reader improvement metric is relevant.

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

   • Not applicable. This is a hardware device; there is no standalone algorithm performance to evaluate.

6. The type of ground truth used:

   • The "ground truth" for the reprocessed catheter's performance is its functional equivalence to the original, new device and compliance with established performance specifications. This is demonstrated through various engineering, mechanical, material, and biological tests (e.g., cleaning efficacy, tensile strength, sterility, biocompatibility standards), not clinical diagnostic ground truth like pathology or outcomes data.

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML algorithm that requires a training set.

8. How the ground truth for the training set was established:

   • Not applicable. No training set is involved.

In summary: The submission for the NES Reprocessed Eagle Eye Platinum RX Digital IVUS Catheter focuses on demonstrating that the reprocessed device is as safe and effective as the original predicate device through rigorous bench and laboratory testing. The criteria and studies are designed to prove manufacturing and functional equivalence of a reprocessed medical device, rather than the diagnostic interpretive performance of an AI/ML system.

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