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PASCAL® Synthesis™ TwinStar™ Ophthalmic Scanning Laser System is intended for use to perform single-spot photocoagulation in the posterior segment (retina, choroid) and in the anterior segment (iris, trabecular meshwork) as well as pattern-scanning photocoagulation in the non-macular retina of the eye. Single-spot delivery may be performed using a slit lamp biomicroscope or an indirect ophthalmoscope. Pattern delivery may be performed using a slit lamp biomicroscope.

PASCAL® Synthesis™ TwinStar™ is an ophthalmic scanning laser system. The system can perform single shot photocoagulation as is performed conventionally. At the physician's discretion, the system provides for a single laser spot treatment or the option of using a selectable pattern of delivering multiple laser spots simultaneously. Pattern scanning allows the physician to enhanced efficiency and reduced patient discomfort.

The PASCAL Synthesis™ Laser System (parent product to the PASCAL Synthesis Twinstar™) included 532 nm/577 nm wavelengths and was cleared via K123542. The subject device for this submission is a line extension named PASCAL Synthesis Twinstar and will include 577 nm/638 nm laser wavelengths.

The provided document is a 510(k) summary for the PASCAL® Synthesis™ TwinStar™ Ophthalmic Scanning Laser System. It focuses on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria and proving performance against them in the way an AI/ML device submission would.

Therefore, many of the requested points, especially those related to acceptance criteria, specific performance metrics (like sensitivity, specificity, F1 score), sample sizes for test/training sets with ground truth, expert adjudication, or MRMC studies for AI devices, are not present in this document.

This device is a physical laser system, not an AI/ML diagnostic tool. The "performance" discussed relates to its physical characteristics and biological effects on animal tissue, not its ability to interpret medical data or assist human readers.

However, I can extract information relevant to the study that was done to support the device and map it to the closest possible aspects of your request.

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

No explicit acceptance criteria in the form of numerical performance targets (e.g., sensitivity > X%) are stated. The study's conclusion of "similarity" is the implicit acceptance.

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

• Sample Size for Animal Study (Test Set): Not explicitly stated as a number of animals or eyes, but the study refers to "rabbit retinae" and "single-eye comparative cases." The common practice for such studies usually involves a small number of animals (e.g., 3-5 rabbits).
• Data Provenance: The study was "in vivo" (live animal) and "prior to euthanasia," implying a prospective experimental design. Country of origin is not specified, but the sponsor is based in Livermore, CA, USA.

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)

• The ground truth (lesion morphology and size) was established by "ophthalmoscopic evaluation, fundus photos, and SD-OCT measurements."
• The number and qualifications of experts interpreting these evaluations are not specified in the document. It is implied these were performed by qualified personnel involved in the animal study.

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

• No explicit adjudication method is described. The assessment likely involved expert interpretation of the ophthalmoscopic, fundus photo, and SD-OCT data, but details on how consensus or adjudication was achieved are not provided.

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

• No, an MRMC comparative effectiveness study was not done. This device is a laser surgical instrument, not an AI diagnostic tool that assists human readers.

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

• Not applicable. This is a laser device, not an algorithm. The "standalone" performance here refers to the device's ability to create comparable lesions to the predicate, irrespective of human interpretation beyond setting parameters and performing the procedure.

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

• The ground truth was based on in-vivo assessments using:
  • Ophthalmoscopic evaluation
  • Fundus photos
  • SD-OCT measurements
• It primarily focused on lesion morphology and size immediately post-treatment in animal models.

8. The sample size for the training set

• Not applicable. This device is a laser system and does not involve AI/ML requiring a training set. The "study" described is an animal performance test, not an AI model training or validation.

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

• Not applicable, as there is no training set for an AI/ML model for this device.

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