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The DioLite™ 532 is a semiconductor-based laser system which delivers 532 nm laser light intended to be used for the photocoagulation of vascular and pigmented skin lesions.

The DioLite 532 is a semiconductor-based dermatology laser system which delivers 532 nm laser light. The system delivers up to 3 Watts of power, in pulses of 1 to 100 milliseconds duration, at repetition rates up to 15 Hz, into treatment spots of 200 to 1400 microns diameter.

This 510(k) summary for the IRIDEX Corporation DioLite™ 532 does not contain information regarding objective acceptance criteria or a study designed to prove the device meets such criteria.

The document primarily focuses on establishing substantial equivalence to predicate devices based on technological characteristics and intended use. It describes the device's technical specifications and compares them to other legally marketed laser devices.

Therefore, I cannot provide the requested table, sample sizes, expert details, adjudication methods, MRMC study information, standalone performance, or ground truth details for an acceptance criteria study. This information is not present in the provided text.

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The intended use of this device is retinal photocoagulation and laser trabeculoplasty to be performed by the ophthalmologist.

The OcuLight GL is a semiconductor-based ophthalmic laser photocoagulator which delivers true continuous wave green laser light. It will only be used in conjunction with three fiber optically coupled delivery devices which have received prior FDA-premarket clearance: the IRIS Slit Lamp Adapter (K912918 for retinal photocoagulation and K913430 for laser trabeculoplasty), the IRIS EndoProbe (K894841), and the IRIS Laser Indirect Ophthalmoscope (K903288).

Here's an analysis of the provided text regarding acceptance criteria and supporting studies:

Based on the provided text, it is not possible to describe acceptance criteria or a study that proves the device meets specific acceptance criteria in the way a modern AI/ML device submission would. The document is a 510(k) summary for a medical device (OcuLight GL laser photocoagulator) from 1996, which predates advanced AI/ML algorithms and their associated rigorous validation frameworks.

The document focuses on demonstrating substantial equivalence to existing predicate devices, a common pathway for medical device clearance. This process typically involves showing that the new device has the same intended use, technological characteristics, and safety/effectiveness profile as legally marketed devices, rather than meeting specific performance thresholds against a defined ground truth.

Therefore, many of the requested data points (sample size for test set, data provenance, number of experts, adjudication method, MRMC studies, standalone performance, ground truth for training/test sets, training set sample size) are not applicable or mentioned in this type of 510(k) summary for a hardware-based laser device from that era.

Below is an attempt to structure the available information per your request, with significant caveats where information is missing or not relevant to the context of this device type and submission era.

Acceptance Criteria and Device Performance

Note: The acceptance criteria here are inferred from the 510(k) summary's focus on substantial equivalence. There are no explicit performance metrics (e.g., sensitivity, specificity, accuracy) defined or evaluated against a ground truth as would be expected for an AI/ML device.

Detailed Information (as far as available from the text):

1. 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 document does not describe a clinical study with a "test set" in the context of an AI/ML algorithm. The demonstration of substantial equivalence relies on comparing technical specifications and intended use with predicate devices, rather than a clinical trial with a defined patient cohort.

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

   • Not applicable/Not provided. No "test set" or ground truth establishment by experts for performance evaluation is described.

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

   • Not applicable/Not provided.

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. This is a hardware device for surgical procedures (laser photocoagulation), not an AI/ML diagnostic or assistive tool for human readers. Therefore, an MRMC study related to readers improving with AI assistance is not relevant or described.

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

   • Not applicable/No. This device is a laser system operated by a human ophthalmologist; there is no "algorithm only" performance to evaluate.

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

   • Not applicable. The concept of "ground truth" for evaluating an AI/ML algorithm's output is not relevant to this type of device submission. The efficacy and safety are deemed equivalent to predicate devices, which would have had their own clinical data or established safe use.

7. The sample size for the training set:

   • Not applicable/Not provided. This device does not involve a "training set" in the context of machine learning.

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

   • Not applicable/Not provided.

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The intended use of this device is transscleral retinal photocoagulation (TSRPC) for retinopexy.

The IRIS DioPexy Probe is a multiple-use fiber optic laser delivery device with integral optics, which terminates with a contact prism tip. It must be directly connected to a compatible IRIS OcuLight SL or SLx (810 nm-infrared) Photocoagulator. The prism tip is designed to deflect laser energy 90° from the axis of the shaft and be simultaneously act as a scleral depressor. The fiber optic cable is 3 meters (10 feet). The DioPexy Probe is shipped from the factory non-sterile in a hard plastic container. The device can be sterilized between each use in this container using Ethylene Oxide (EtO) gas in accordance with the user instructions.

Here's an analysis of the provided text regarding the DioPexy Probe, focusing on acceptance criteria and supporting studies:

It is important to note that the provided 510(k) summary does not contain explicit performance acceptance criteria (e.g., target accuracy, sensitivity, specificity values) or detailed study results proving the device meets such criteria. The document focuses on demonstrating substantial equivalence to predicate devices based on intended use and technological characteristics, rather than reporting on specific quantitative performance metrics from a dedicated clinical study as would be expected for a diagnostic or AI-driven device.

Therefore, many of the requested sections below will indicate "Not Provided" or "Not Applicable" based on the information given.

Acceptance Criteria and Study Analysis for the DioPexy Probe

1. Table of Acceptance Criteria and Reported Device Performance

No quantitative performance metrics (e.g., success rate of adhesion, complication rates) that would typically define "acceptance criteria" for a new medical device are explicitly provided in this 510(k) summary. The summary primarily focuses on establishing substantial equivalence based on the device's functional similarity and intended use to existing devices.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size (Test Set): Not provided. The 510(k) summary does not describe a specific clinical "test set" or study population beyond referencing general clinical practice for retinopexy.
• Data Provenance: Not provided. The summary discusses the general principles of retinopexy and existing devices but does not mention specific clinical data collected for the DioPexy Probe itself, let alone its provenance.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Number of Experts: Not provided.
• Qualifications of Experts: Not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/Not provided. No specific test set or clinical study requiring adjudication is 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

• MRMC Study: Not applicable. This document describes a laser delivery probe, not an AI-driven or diagnostic device. Therefore, no MRMC study or AI-assistance comparison was conducted or is relevant here.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Standalone Performance: Not applicable. This device is a surgical instrument that relies entirely on human operation and interpretation (the physician monitoring the burn). It is not an algorithm or an autonomous device.

7. The Type of Ground Truth Used

• Type of Ground Truth: Not explicitly defined in terms of a study. For the predicate devices and the DioPexy Probe, the "ground truth" of successful retinopexy would typically be clinical assessment of chorioretinal adhesion and retinal reattachment, observed by an ophthalmologist, potentially confirmed by imaging over time, and ultimately by positive patient outcomes (prevention of severe visual loss). However, this is discussed at a conceptual level of medical practice rather than as the outcome of a specific clinical trial reported in this document.

8. The Sample Size for the Training Set

• Sample Size (Training Set): Not applicable/Not provided. As this is not an AI/machine learning device, there is no "training set."

9. How the Ground Truth for the Training Set Was Established

• Ground Truth for Training Set: Not applicable. As this is not an AI/machine learning device, there is no "training set" or ground truth establishment for it in that context.

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