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Jupiter PTA Catheters are designed for dilating stenotic lesions in peripheral arteries (renal, popliteal, infra popliteal, femoral, and illio femoral) and are also intended to treat obstructive lesions of native or synthetic arteriovenous dialysis fistulae.

Jupiter PTA Catheters are similar in design, construction, indications for use, and performance characteristics as compared to commercially available PTA Catheters.

This document is a 510(k) premarket notification for Jupiter PTA Catheters and does not contain the type of acceptance criteria and study information typically found for AI/ML-driven medical devices.

The provided text focuses on demonstrating substantial equivalence to predicate devices for a physical medical device (a catheter), not on the performance of a diagnostic algorithm or AI system. Therefore, I cannot extract the requested information regarding acceptance criteria, device performance metrics, sample sizes, ground truth establishment, or expert involvement as these concepts are not applicable to the content provided.

Specifically, the document discusses:

• General Provisions: Common and proprietary names of the device.
• Predicate Devices: Lists similar catheters from Cordis and Medi Tech.
• Classification: Class II device.
• Performance Standards: States that FDA performance standards have not been established under Section 514 of the Food, Drug and Cosmetic Act. This explicitly indicates that there are no predefined performance criteria from the FDA for this device discussed in the document.
• Intended Use and Device Description: Explains what the catheter is used for.
• Biocompatibility: Refers to previous testing on K955886 and compliance with ISO Standard 10993, but this relates to material safety, not diagnostic performance.
• Summary of Substantial Equivalence: Asserts similarity in design, construction, indications for use, and performance characteristics to commercially available PTA Catheters.

To answer your request, if this were an AI/ML device submission, I would expect to see sections detailing:

• Acceptance Criteria/Performance Targets: Specific metrics like sensitivity, specificity, AUC, F1-score, or agreement rates.
• Clinical Study Design: Information on how the device's performance was evaluated, including reader studies, standalone studies, etc.
• Dataset Details: Size, provenance, and characteristics of training and test sets.
• Ground Truth: How the definitive diagnosis or outcome was established (e.g., pathology, clinical follow-up, expert consensus).
• Expert Review: Number and qualifications of experts involved in establishing ground truth or reading studies.

Since these elements are absent in the provided text, I cannot fulfill your request as formulated for evaluating an AI/ML medical device.

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