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The LightMed TruScan 577 Laser System is intended for use in the treatment of ocular pathology in the posterior segment; Retinal photocoagulation, panretinal photocoagulation, focal photocoagulation and grid photocoagulation for vascular and structure abnormalities of the retina and choroid including:

• 1. Proliferative and Severe and very severe nonproliferative diabetic retinopathy
• 2. Clinically Significant Macular edema
• 3. Choroidal neovascularization
• 4. Branch and central retinal vein occlusion
• 5. The treatment of choroidal neovascularization associated with wet age-related macular degeneration
• 6. Lattice degeneration
• 7. Retinal tears and detachments

LightMed TruScan 577 is an integrated system consisting of Laser Console utilizing a 577nm Optically Pumped Semiconductor (OPSL; solid state) laser cavity, TruScan integrated Slit Lamp technology controlled via a LCD touch panel and wheel chair accessible ophthalmic instrument table.
The TruScan module which is integrated Slitlamp with safety filter as Laser Delivery System, employs a traditional single spot treatment laser, as well as a semi-automated pattern generation method employing short 577mm laser pulse durations of typically 10ms; range of spot size from 50um to 400µm in a continuous adjustment.
The LightMed TruScan 577 Laser System is comprised of the following functional components:

• LCD touch panel
• Laser Console ●
• Ophthalmic Instrument table
• TruScan integrated CSO Slitlamp (K992836)

The provided text describes a 510(k) premarket notification for the LightMed TruScan 577 Laser System, focusing on its substantial equivalence to a predicate device. The document does not contain information about a study proving the device meets acceptance criteria in the context of an AI/ML device evaluating images or data for diagnostic purposes, nor does it present acceptance criteria and reported device performance in the format of a table as requested for such a study.

Instead, this document focuses on demonstrating that the LightMed TruScan 577 Laser System, a medical device for ophthalmic photocoagulation, is substantially equivalent to a legally marketed predicate device (PASCAL Streamline 577). The "performance data" referred to in Section VII are primarily bench testing, electrical safety, EMC, and software verification/validation, which are typical for traditional medical device clearances, not for AI/ML performance evaluation against a dataset with ground truth.

Therefore, most of the information requested in your prompt regarding acceptance criteria, sample sizes for test/training sets, expert adjudication methods, MRMC studies, standalone performance, and ground truth types cannot be extracted from this document because it describes a different type of medical device and regulatory submission.

Here's an analysis of what can be inferred or is explicitly stated:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. The document does not define acceptance criteria and reported performance in the context of diagnostic accuracy, sensitivity, specificity, etc., against a ground truth dataset, as would be relevant for an AI/ML device. The performance data discussed are related to the device's physical and electrical functioning, not its ability to interpret medical images or data.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not applicable/Not provided. No test set of patient data (e.g., images, clinical records) is described. The "test set" in this context refers to the device itself undergoing various engineering and safety tests.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable/Not provided. No ground truth for a test set of medical data is discussed.

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

• Not applicable/Not provided. No adjudication of medical data for ground truth is discussed.

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/Not provided. This is a laser system, not an AI/ML diagnostic aid for human readers. No MRMC study is mentioned.

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

• Not applicable/Not provided. This device is a treatment laser, operated by a human ophthalmologist. There is no "algorithm only" performance concept relevant here.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Not applicable/Not provided. No ground truth for medical data is discussed. The "ground truth" for this device would be its adherence to engineering specifications and safety standards.

8. The sample size for the training set

• Not applicable/Not provided. No training set of medical data for an AI/ML algorithm is discussed.

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

• Not applicable/Not provided. No training set of medical data for an AI/ML algorithm is discussed.

Summary of relevant information from the document:

• Device Type: Ophthalmic Laser (LightMed TruScan 577 Laser System).
• Purpose: Treatment of ocular pathology in the posterior segment (e.g., retinal photocoagulation for diabetic retinopathy, macular edema, choroidal neovascularization).
• Regulatory Pathway: 510(k) premarket notification, demonstrating substantial equivalence.
• Predicate Device: PASCAL Streamline 577 (K111108).
• Performance Data Provided:
  • Bench Testing (Finished Product final assembly quality inspection, System Adjustment, Calibration and Testing for Laser console and TruScan laser delivery unit).
  • Electrical safety and electromagnetic compatibility (EMC) testing, complying with IEC 60601-1, IEC 60601-2-22, IEC 60825-1, and IEC 60601-1-2 standards.
  • Software Verification and Validation Testing, considering the software as a "major" level of concern.
• Conclusion: The non-clinical data (bench testing, electrical safety, EMC, software V&V) supported the safety and intended performance, demonstrating comparability to the predicate device.

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