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The WaveLight FS200 Laser System is an ophthalmic surgical laser indicated for use:

· In the creation of a corneal flap in patients undergoing LASIK surgery or treatment reguiring initial lamellar resection of the cornea.

· In patients undergoing surgery or other treatment requiring initial lamellar resection of the cornea to create tunnels for placement of corneal ring segments.

· In the creation of a lamellar cut/resection of the cornea for lamellar keratoplasty.

· In the creation of a penetrating cut/incision for penetrating keratoplasty and for corneal harvesting.

· In patients undergoing ophthalmic surgery or other treatment requiring arcuate cuts/incisions in the cornea.

· In patients undergoing ophthalmic surgery or other treatment requiring pocket cuts/incisions in the cornea.

The WaveLight® FS200 is a stationary scanning-spot femtosecond laser system used to support refractive surgery of the cornea as specified in the indications for use statement.

The provided text is a 510(k) summary for the WaveLight FS200 Laser System, which is an ophthalmic laser. It focuses on demonstrating substantial equivalence to predicate devices for new indications for use related to arcuate and pocket cuts/incisions in the cornea. It is not a study proving device meeting specific acceptance criteria in the context of an AI/algorithm-driven device with performance metrics like sensitivity, specificity, or AUC.

Therefore, many of the requested categories for a study proving device acceptance criteria (e.g., sample size, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable to this type of regulatory submission. This document describes a traditional medical device's non-clinical performance and a comparison to predicate devices, not an AI/ML device study.

However, I can extract the relevant information regarding performance testing and a high-level "acceptance criteria" through the lens of what this document does provide.

Here's the breakdown based on the document's content:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: The document states "Performance testing on pig eyes." It does not specify the number of pig eyes used.
• Data Provenance: The data is from "pig eyes," indicating an ex vivo or in vivo animal study, not human data. The country of origin is not specified. It is a non-clinical study, presumably prospective in design for the purpose of testing the device.

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

• Experts: Not applicable. This document describes non-clinical performance testing on animal tissue (pig eyes) to demonstrate the physical properties of the cuts. The "ground truth" would be objective measurements of the cuts themselves, not expert interpretation of images or clinical outcomes.

4. Adjudication method for the test set:

• Adjudication Method: Not applicable. As this is non-clinical testing of physical device output on animal tissue, an adjudication method for human interpretation is not relevant.

5. 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:

• MRMC Study: No, an MRMC study was not done. This device is an ophthalmic surgical laser, not an AI/ML-powered diagnostic or assistive tool for human interpretation.

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

• Standalone Performance: Not applicable in the context of an AI algorithm. The device is a standalone surgical laser. Its performance (accuracy, precision, quality of cuts) was assessed directly from its physical output.

7. The type of ground truth used:

• Ground Truth: For the non-clinical performance testing, the ground truth would be objective measurements of the arcuate and pocket cuts/incisions (e.g., dimensions, morphology, depth, width, curvature) produced by the laser on the pig eyes. The document states "accuracy, precision, and quality" were addressed, implying quantitative measurement of these physical parameters.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This summary describes a physical medical device, not an AI/ML algorithm that requires a training set. The device itself is "trained" through its engineering design and manufacturing processes.

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

• Training Set Ground Truth: Not applicable. As there is no AI/ML algorithm involved, there is no training set and therefore no ground truth establishment for a training set.

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The WaveLight® FS200 Laser System is an ophthalmic surgical laser indicated for use:

• · In the creation of a corneal flap in patients undergoing LASIK surgery or other surgery or treatment requiring initial lamellar resection of the cornea.
• · In patients undergoing surgery or other treatment requiring initial lamellar resection of the cornea to create tunnels for placement of corneal ring segments.
• · In the creation of a lamellar cut/resection of the cornea for lamellar keratoplasty.
• · In the creation of a penetrating cut/incision for penetrating keratoplasty and for corneal harvesting.

The WaveLight® FS200 Laser System is a stationary scanning-spot femtosecond laser system used in refractive surgery.

The provided text describes the WaveLight® FS200 Laser System and its clearance through the 510(k) pathway. However, the document does not contain a detailed study design with specific acceptance criteria, sample sizes for test and training sets, expert qualifications, or adjudication methods in the way one would typically expect for a modern AI/ML device submission.

The document primarily focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and performance in creating corneal cuts. The information provided is characteristic of a traditional medical device submission rather than one for an AI/ML diagnostic tool.

Here's an attempt to answer your questions based only on the information available in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative "acceptance criteria" for precise numerical metrics like accuracy, sensitivity, or specificity. Instead, it refers to "performance tests" that establish "equivalence" to predicate devices.

2. Sample size used for the test set and the data provenance

The document states: "Performance tests according to the FDA Guidance 'Keratome and Replacement Keratome Blades Premarket Notification [(510(k)] Submissions' were conducted to collect data on the accuracy, precision and quality of the cuts achieved with the WaveLight® FS200 Laser System."

• Test Set Sample Size: Not specified. The document does not provide a number for the test set.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

Not applicable/Not specified. The "ground truth" here would relate to direct measurements of the physical cuts, not expert interpretation of outputs. The document does not mention the use of experts in this context.

4. Adjudication method for the test set

Not applicable/Not specified. Given the nature of a laser system creating physical cuts, an adjudication method for expert consensus on images is not relevant to the described performance tests.

5. 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 is not an AI/ML device that assists human readers. It's a surgical instrument.

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

The device is a standalone surgical laser system. Its performance evaluation focuses on the quality of the cuts it creates.

7. The type of ground truth used

The "ground truth" would be objective measurements of the physical characteristics (accuracy, precision, quality) of the corneal cuts themselves, likely performed using metrology or other analytical techniques directly on the cut tissue, as described in the referenced FDA Guidance. The document doesn't explicitly detail the methodology, but for a keratom, ground truth typically involves physical measurements.

8. The sample size for the training set

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

9. How the ground truth for the training set was established

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

Summary Limitations:

The provided 510(k) summary is for a traditional surgical laser system, not an AI/ML driven device. Therefore, many of the questions related to AI/ML specific evaluation criteria (like training sets, expert consensus, MRMC studies, etc.) are not addressed in the document and are likely not relevant to its regulatory clearance. The performance testing for this device would have focused on engineering specifications, safety, and the physical outcomes of the laser's operation compared to known predicate devices or established standards.

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