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The LenSx Laser system is indicated for use:

• In the creation of corneal cuts/incisions (single-plane, multi-plane, and arcuate), anterior capsulotomy and laser phacofragmentation during cataract surgery. Each of these procedures may be performed either individually or consecutively during the same surgery.
• In the creation of corneal cuts/incisions (single-plane, multi-plane, and arcuate) during Implantable Collamer Lens (ICL) surgery.
• In the creation of a corneal flap in patients undergoing LASIK surgery or other treatment requiring initial lamellar resection of the cornea.
• In the creation of corneal pockets for placement/insertion of a corneal inlay device; and for creation of corneal tunnels for the placement of corneal rings.

The LenSx Laser system is an ophthalmic surgical laser which uses focused femtosecond laser pulses to create vapor bubbles which disrupts/separates tissue (photodisruption) within the lens capsule, crystalline lens, and the cornea. A computer-guided delivery system places the laser pulses in a pattern to produce an incision/cut.

The laser pulses are delivered through a sterile, disposable applanating lens and suction ring that contacts the cornea and fixes the eye with respect to the laser delivery system.

The interface between the laser and patient is the Patient Interface that connects to the delivery system which is docked to the patient's cornea. Two models of the Patient Interface accessory are offered for use with the LenSx Laser: the LenSx Laser Patient Interface and the LenSx Laser SoftFit Patient Interface. Both models consist of a sterile, disposable applanating lens and suction ring assembly. The LenSx Laser SoftFit Patient Interface also comes with a soft contact lens that is positioned against the external surface of the Patient Interface glass. For cataract procedures, the LenSx Laser SoftFit Patient Interface is used. The LenSx Laser Patient Interface is used for corneal, flap, tunnel, and pocket incisions. Refer to the Instructions for Use supplied with the LenSx Laser Patient Interface for preparation and application.

The LenSx Laser system is for prescription use and should only be operated by a trained physician. The LenSx Laser system is intended to be used within a clinic(s)/hospital(s)/surgical practice network.

Based on the provided FDA 510(k) Clearance Letter for the LenSx Laser System, this document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone study with detailed acceptance criteria and performance data for a new AI or novel diagnostic device.

The clearance is for a modified version of an existing device (LenSx Laser System) with software updates and an expanded indication for Implantable Collamer Lens (ICL) surgery. The general approach taken is to show that these modifications do not raise new questions of safety or efficacy and that the device remains substantially equivalent to its predicate. Therefore, the requested information regarding acceptance criteria and a study proving the device meets those criteria (especially in the context of an AI/diagnostic device) is not explicitly detailed in this 510(k) summary.

However, I can extract the relevant information presented, acknowledging that it's framed within the context of demonstrating substantial equivalence for a modified device, rather than a de novo clearance for a completely new technology with novel performance claims.

Here's an attempt to answer the questions based on the provided text, highlighting where the information is not applicable or not detailed in this type of submission:

Acceptance Criteria and Device Performance Study (as inferred from the 510(k) Summary)

The 510(k) summary indicates that the modifications to the LenSx Laser System are minor and do not introduce new safety or efficacy concerns. The "acceptance criteria" are implied by the successful completion of various non-clinical tests demonstrating that the device continues to meet its intended design specifications and functional requirements, performing as intended and being equivalent to the predicate. There are no specific numerical performance metrics provided in the summary that would typically be seen for a new diagnostic or AI device (e.g., sensitivity, specificity, accuracy against a gold standard).

Table of Acceptance Criteria and Reported Device Performance

Since this is a modification to an existing device, the "acceptance criteria" are generally about maintaining the performance and safety profiles of the predicate. The "reported device performance" refers to the successful completion of the tests.

Study Details (as applicable)

1. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size: Not specified in terms of clinical cases or patient data, as no animal or clinical testing was deemed necessary for this submission. The "test set" primarily refers to bench testing, software verification/validation, and regulatory compliance checks.
   • Data Provenance: Not applicable as no clinical or animal data was collected for this submission. The data provenance for compliance testing is internal Alcon laboratories.

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

   • Not applicable as this 510(k) submission does not rely on expert-adjudicated ground truth from a clinical test set. The ground truth for engineering and software tests is based on design specifications, recognized standards, and regulatory guidance. For clinical ground truth, the submission relies on the established safety and efficacy of the predicate device and the assessment that the modifications do not alter this.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable. There was no clinical test set requiring expert adjudication.

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:

   • No MRMC study was performed or required. The device is a surgical laser, not an AI-assisted diagnostic tool that would typically involve human readers.

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

   • Not applicable in the context of an AI algorithm. However, the device itself, including its software, undergoes standalone functional and safety testing as part of the "Non-Clinical Testing" detailed in Section 7.1, such as "Software verification and validation testing" and "Performance Testing." These tests ensure the device (algorithm and hardware) performs its functions correctly according to specifications, independent of operator interaction after initial surgical planning.

6. The type of ground truth used (expert concensus, pathology, outcomes data, etc):

   • For the non-clinical and software testing, the "ground truth" is defined by:
     • Engineering Specifications: The pre-defined technical and functional requirements for the laser system.
     • International and National Standards: Compliance with standards like IEC 60601 series, ANSI Z80.36-2021 for safety and performance.
     • FDA Guidance Documents: Compliance with FDA recommendations for software documentation and cybersecurity.
     • Predicate Device Performance: The established safety and effectiveness of the existing LenSx Laser System serves as the clinical benchmark.

7. The sample size for the training set:

   • Not applicable. This is not an AI/machine learning device that relies on a "training set" of data in the typical sense for a new diagnostic algorithm. The software modifications are deterministic or rule-based enhancements (e.g., embedded calculator, new cut patterns).

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

   • Not applicable for the same reason as above. If there were internal development/optimization processes for the new features (e.g., nomogram calculations), their accuracy and "ground truth" would be established through mathematical validation, simulation, and bench testing against known physical principles or desired outcomes, rather than a data-driven training set.

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