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The iScience Surgical Ophthalmic Microcannula is indicated for fluid infusion and aspiration, as well as illumination, during surgery.

The iScience Surgical Ophthalmic Microcannula, or iTRACK, is a flexible microcannula designed to allow atraumatic cannulation of spaces in the eye such as the anterior chamber and posterior segment, for infusion and aspiration of fluids during surgery, including saline and viscoelastics. The microcannula incorporates an optical fiber to allow transmission of light to the microcannula tip for surgical illumination and guidance.

This document is for an Ophthalmic Microcannula, a physical surgical device, and not an AI/ML powered device. Therefore, the questions related to AI/ML specific criteria (such as acceptance criteria, study details, ground truth, sample sizes for training/test sets, MRMC studies, etc.) are not applicable here.

The document primarily focuses on demonstrating substantial equivalence to legally marketed predicate devices through:

1. Device Description: Outlining the design and function of the iScience Surgical Ophthalmic Microcannula (iTRACK).
2. Indication for Use: Stating its purpose for fluid infusion and aspiration, and illumination during surgery.
3. Predicate Devices: Identifying existing devices it claims substantial equivalence to (American Medical Devices Endolight, Syntec True Light, Micron Surgical Weiss Retinal Cannula).
4. Technological Characteristics: Asserting that its intended use and technological features do not differ from predicate devices, using similar materials and methods of operation.
5. Performance Data (Non-AI/ML): Mentioning conformance to standards for sterilization, shelf-life, and packaging integrity (e.g., ANSI/AAMI/ISO 11137-1994, ANSI/AAMI/ISO 10993, ANSI/AAMI/ISO 11607-1997). This "performance data" refers to compliance with manufacturing and safety standards, not AI model performance.
6. Conclusion: Stating that due to meeting stated standards and similar technological characteristics to predicate devices, it is substantially equivalent, safe, and effective.

Since the device is not an AI/ML product, it does not have "acceptance criteria" or a "study that proves the device meets the acceptance criteria" in the way an AI/ML model would to demonstrate diagnostic accuracy or clinical effectiveness. Instead, acceptance is based on demonstrating substantial equivalence to existing, legally marketed devices, and adherence to relevant safety and manufacturing standards for medical devices.

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