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· Selecta Duet LED or Digital Duet: Photodisruption of ocular tissue using light energy emitted by a Nd: Y AG laser, including discission of the posterior capsule of the eye (posterior capsulotomy) iridectorny, and selective laser trabeculoplasty.

· Selecta LED Trio or Digital Trio: Photodisruption of ocular tissue using light energy emitted by a Nd: Y AG laser, including discission of the posterior capsule of the eye (posterior capsulotomy) iridectorny, selective laser trabeculoplasty, and retinal photocoagulation.

The Selecta Duet LED and Digital Duet subject devices are each a fully integrated, highperformance diagnostic slit lamp and therapeutic laser delivery system. The diagnostic slit lamp is for examining the anterior segment of the eye, from the corneal epithelium to the posterior capsule. The integrated Nd:YAG Q-Switch laser module provides short pulses at the wavelength corresponding with the selected operating mode. Two modes are available: PD (YAG) mode: 1064 nm for photodisruption (PD) of ocular tissues in procedures such as posterior capsulotomy, iridotomy, and iridectomy, and SLT mode: 532 nm for Selective Laser Trabeculoplasty (SLT). The Selecta LED Trio and Digital Trio subject devices are each created by connecting the Selecta LED Duet and Digital Duet, respectively, to a compatible, FDA-cleared, Lumenis continuous 532 nm wavelength photocoagulator laser, via the LaserLink S. When the user connects the Duet to the LaserLink S, the Duet-part acts only as a Slit Lamp since the integrated Duet-laser is disabled and the laser in the external photocoagulator takes over. This combination adds the ability to perform retinal photocoagulation, as well as other indications cleared for the continuous 532 nm wavelength photocoagulator laser. The user disconnects the Duet from the LaserLink S for the system to perform as a Duet.

The provided text is an FDA 510(k) summary for the Lumenis Selecta Duet LED, Digital Duet, Selecta LED Trio, and Digital Trio Laser Systems. It describes the device, its intended use, and a comparison to a predicate device, concluding with performance testing.

However, the document does not contain the kind of detailed information about acceptance criteria, study design (sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance), or training set information that would be typically found in a clinical study report for an AI/ML-based medical device.

The "Performance Testing" section primarily refers to compliance with standards for medical electrical equipment and laser safety, and software verification. It states:

• "Evaluating the implemented changes using the same recognized standards that were used for the cleared devices" (listed standards like ANSI/AAMI ES60601-1, IEC 60601-1-2, IEC 60601-2-22, IEC 60825-1, ISO 15004-2, ISO 14971).
• "Software/Bench Testing" stating that "Lumenis developed and verified the software in accordance with a major level of concern described in the FDA 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices' and also per the IEC 62304:2006 and A1:2015 Medical Device Software - Software Life Cycle Processes standard." and "The software/bench tests conducted on the modifications confirmed that they met their requirements."

This document describes a device that is essentially a hardware update and software refresh of a previously cleared laser system, not a novel AI/ML diagnostic or assistive algorithm for which the requested detailed study information would be relevant. The changes are described as "primarily to be responsive to user feedback, upgrade to the latest user interface, or reflect a need to change a supplier or manufacturing contractor."

Therefore, I cannot extract the requested information from this document because it does not appear to describe a study proving an AI/ML device meets acceptance criteria through clinical performance metrics. The phrase "device meets the acceptance criteria" in this context refers to meeting engineering/safety/performance standards for a laser system, not the kind of AI/ML performance metrics typically seen for diagnostic algorithms.

In summary, based on the provided text, the requested information (performance study details for an AI/ML device) is not available. The document focuses on demonstrating substantial equivalence to a predicate device through adherence to recognized technical standards and software verification, rather than clinical performance trials of a new diagnostic AI/ML algorithm.

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