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The SL3™ is intended to be used for oral soft tissue surgery, including: biopsies, hemostatic assistance; treatment of apthous ulcers; frenectomy; gingival incision and excision; gingivectomy; gingivoplasty; incising and draining of abscesses; operculectomy; removal of fibromas; soft-tissue crown lengthening; sulcular debridement (removal of diseased or inflamed soft tissue in the periodontal pocket) and tissue retraction for impressions.

The SL3 laser is to provide the ability to perform intraoral soft tissue dental, general, oral maxilla-facial and cosmetic surgery. The SL3 laser is intended for ablating, incising, vaporizing and coagulation of soft tissues using a contact fiber optic delivery system.

The device will be used in the following areas: general and cosmetic dentistry, otolaryngology, arthroscopy, gastroenterology, general surgery, dermatology & plastic surgery, genecology, urology, opthamology and pulmonary surgery. The following are the oralpharngeal indications for use for which the device will be marketed:

-Excision and Incision Biopsies
-Hemostatic assistance
-Treatment of Apthous Ulcers
-Frenectomy
-Frenotomy
-Gingival Incision and Excision
-Gingivectomy
-Gingivoplasty
-Incising and Draining of Abscesses
-Operculectomy
-Oral Papillectomy
-Removal of Fibromas
-Soft Tissue Crown Lengthening
-Sulcular Debridement (removal of diseased or inflamed soft tissue in the periodontal pocket)
-Tissue retraction for Impression
-Vestibuloplasty
-Light activation of bleaching materials for teeth whitening
-Laser-assisted bleaching/whitening of teeth

The SL3™ is a Class IV soft-tissue diode laser that can be used for a wide variety of soft-tissue procedures. This device uses a Gallium, Aluminum, Arsenic (GaAIAS) diode for the active medium, producing laser energy at 810 nanometer wavelength. Laser technology has been steadily evolving, allowing doctors to provide less invasive treatment for many dental procedures, both preventative and restorative. The SL3™ is designed to be compact, portable, reliable and user friendly. It provides the practitioner with a versatile instrument for applications ranging from excisions to vaporization of tissues. The diode laser energy is delivered through optical fiber in the hand piece to the removable fiber tips. The system may be utilized for a wide variety of surgical and cosmetic procedures.

This document is a 510(k) Pre-market Notification for a medical device called SL3, a surgical laser system. It focuses on establishing substantial equivalence to previously cleared devices rather than primarily presenting a study to prove performance against acceptance criteria in the traditional sense of a clinical trial for diagnostic accuracy or treatment efficacy.

Therefore, many of the requested categories for a study proving device performance (like sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details) are not applicable or not explicitly detailed in this type of regulatory submission.

The acceptance criteria here are implicitly related to the technical specifications and safety profile being substantially equivalent to the predicate devices. The "study" proving this is essentially the comparison table and the demonstration that the SL3 meets similar performance characteristics and safety standards as the predicate devices.

Here's the information parsed from the document based on your request, with explanations for what is not applicable to this type of submission:

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

For a 510(k) submission, "acceptance criteria" are not typically formal performance metrics in the way they would be for a diagnostic AI study. Instead, they are implicit in the substantial equivalence comparison - meaning the new device must perform comparably to the predicate devices and meet relevant safety and essential performance standards. The "reported device performance" is largely represented by its technical specifications.

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: This is a 510(k) pre-market notification for a laser device, not an AI or diagnostic device requiring a "test set" in the context of clinical performance data. The submission relies on technical comparisons and safety data, not a patient-level data set.

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: No "test set" or "ground truth" in this context as described for diagnostic or AI systems. The "ground truth" for a laser device would relate to engineering specifications, safety standards, and pre-clinical testing, which are performed by engineers and regulatory experts, not typically by medical experts establishing diagnostic ground truth from patient data.

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

• Not Applicable: No test set requiring annotation adjudication.

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 a surgical laser device; MRMC studies are used for diagnostic imaging systems, not for comparing human performance with and without a surgical instrument like a laser.

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

• Not Applicable: This device is a surgical instrument intended for human operation, not a standalone algorithm.

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

• Type of Ground Truth: For this device, the "ground truth" is primarily based on engineering specifications, recognized national and international safety standards (e.g., laser safety standards), and the established performance and safety profiles of the predicate devices. Compliance with these technical and safety standards, along with successful pre-clinical testing (which would include electrical safety, EMC, laser emission measurements, etc.), forms the basis of "proof." There is no patient-level "ground truth" in the diagnostic sense.

8. The sample size for the training set

• Not Applicable: No "training set" as this is not an AI or machine learning device. Device development involves engineering design, prototyping, and testing, not data-driven training.

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

• Not Applicable: No training set.

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The GILRAS Slit Lamp is an AC-power slit lamp biomicroscope intended for use in eye examination of the anterior eye segment, from the cornea epithelium to the posterior capsule. It is used to aid in the diagnosis of diseases or trauma which affect the structural properties of the anterior eye segments.

The GILRAS Slit Lamp is an AC-power slit lamp biomicroscope intended for use in eye examination. There are 3 models GR-SL36, GR-SL54, and GR-SL72. These models differ only in the supplied accessories. All models have the same operating characteristics and intended use.

The provided document is a 510(k) premarket notification for the GILRAS Slit Lamp, which is a medical device. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than on providing performance data from a clinical study with acceptance criteria.

Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving the device meets those criteria, as it relates to clinical performance metrics like sensitivity, specificity, etc.

Instead, the document demonstrates substantial equivalence through a technological comparison and compliance with recognized standards.

Here's a breakdown of what the document does provide in relation to your request, and why it doesn't fit the typical "acceptance criteria and study" format you've outlined:

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

• Acceptance Criteria: Not explicitly defined in terms of clinical performance (e.g., accuracy metrics). Instead, the "acceptance criteria" are implied by manufacturing specifications and compliance with recognized safety standards (ISO 10939:2007 and IEC 60601-1) and similarity of technological characteristics to the predicate device.

• Reported Device Performance: The document provides a detailed comparison of theGILRAS Slit Lamp's technological characteristics against its predicate device, the 66 Vision-Tech YZ Slit Lamp. This comparison table effectively is the "performance" data in the context of this 510(k) submission, showing how the new device matches or is similar to the predicate.

  Feature	GILRAS Slit Lamp (Reported Performance)
  Intended Use	AC-power slit lamp biomicroscope intended for use in eye examination of the anterior eye segment, from the cornea epithelium to the posterior capsule. It is used to aid in the diagnosis of diseases or trauma which affect the structural properties of the anterior eye segments.
  Method of Operation	AC-powered
  Exposure Parameters	50000 Lux Maximum, Continuously adjustable from 0 to 50000 Lux
  Maximum temperature of Parts Held by Operator	30°C
  Eyepiece Power	12.5X
  Total Magnification	GR-SL36 - 10X, 16X, 25X; GR-SL54 - 6X, 10X, 16X, 25X, 40X; GR-SL72 - 10X, 16X, 25X
  Stereo Angle	13°
  Diopter Adjustment	-6D to +6D
  Pupillary Adjustment	55mm to 78.5mm
  Slit Width	Continuous from 14mm to 0mm (at 14mm slit becomes a circle)
  Slit Length	Continuous from 14mm to 0mm (at 14mm, slit becomes a circle)
  Slit Angle	0 to 180 degree with horizontal scanning capability
  Aperture Diameters	14, 8, 5, 3, 0.5, and 0.2mm
  Filters	Heat-absorbing, Neutral Density, Cobalt Blue, and Red-Free
  Slit Inclination	5°, 10°, 15°, and 20°
  Illumination Lamp	6V, 20W halogen lamp
  Fixation Target	Green LED
  Brightness Controls	Continuously adjustable from 0 to 50000 Lux
  Patient Contact Materials	Chin-rest paper, Forehead-rest - Polytetrafluoroethylene

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

• Not applicable. This document describes a comparison of device specifications, not a clinical study involving patient data.

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

• Not applicable. No ground truth established from experts for a test set. The "ground truth" here is essentially the predicate device's established technological characteristics and compliance with standards.

4. Adjudication method for the test set:

• Not applicable. No test set or adjudication process described.

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 device is a basic optical instrument (slit lamp), not an AI-powered diagnostic tool. No MRMC study was conducted or described.

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

• Not applicable. This is a hardware medical device, not an algorithm.

7. The type of ground truth used:

• For the purpose of this 510(k), the "ground truth" or benchmark is the legally marketed predicate device (66 Vision-Tech YZ Slit Lamp) and recognized industry standards (ISO 10939:2007 and IEC 60601-1). The entire submission hinges on demonstrating that the GILRAS Slit Lamp is "substantially equivalent" to this predicate and meets these standards.

8. The sample size for the training set:

• Not applicable. No training set for an algorithm is mentioned or relevant to this device submission.

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

• Not applicable. No training set.

Conclusion:

The K080776 document demonstrates the GILRAS Slit Lamp's "acceptance criteria" by showing its adherence to safety standards and its substantial equivalence in technological characteristics to a predicate device. It does not involve performance studies with clinical acceptance criteria, sample sizes, expert ground truth, or AI-related metrics as typically outlined in your request.

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