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The Pick Manipulator is a manual tool for aiding the procedural needs of the surgeon during ophthalmic surgery, such as tissue manipulation and membrane delamination.

Hand-held illuminated pick and membrane delamination instrument for ophthalmic surgery.

The Infinitech Bullet® Endo Illuminated Pick Manipulator is a manual tool intended for ophthalmic surgery, specifically for tissue manipulation and membrane delamination. The provided 510(k) summary does not include a detailed study proving the device meets specific acceptance criteria in terms of performance metrics like sensitivity, specificity, or any quantitative measure of effectiveness.

Instead, the submission focuses on demonstrating substantial equivalence to predicate devices based on device type, intended use, patient contact materials, and manufacturing/sterilization processes. The concept of "effectiveness" mentioned in the summary is broad and stated as: "The instrument is constructed of commonly used materials for ophthalmic surgical instruments and is configured in a common tool geometry." This implies that its effectiveness is assumed based on its similarity to existing, legally marketed devices.

Therefore, many of the requested details about acceptance criteria, study design, and performance metrics cannot be found in the provided document because the 510(k) pathway for this device did not require such a study to demonstrate performance against explicit acceptance criteria.

Below is the information that can be extracted from the provided text:

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

Based on the provided document, there are no explicit quantitative acceptance criteria or detailed performance metrics reported for the Infinitech Bullet® Endo Illuminated Pick Manipulator. The "effectiveness" is stated qualitatively by comparing it to predicate devices. The acceptance was based on "substantial equivalence" to predicate devices.

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. No clinical or performance study involving a test set with human or patient data is described in the provided document for the purpose of demonstrating device performance against specific metrics. The device's substantial equivalence was based on a comparison of its design and intended use to existing predicate devices.

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 ground truth establishment by experts for a test set is mentioned.

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

Not applicable. No adjudication method is mentioned as there was no test set in the context of device performance evaluation.

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 manual surgical instrument, not an AI-assisted diagnostic or therapeutic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is irrelevant to this submission.

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

Not applicable. This is a manual surgical instrument and does not involve an algorithm.

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

Not applicable. No ground truth in the context of performance evaluation was used or described.

8. The sample size for the training set

Not applicable. This is a manual surgical instrument; there is no training set involved in the context of machine learning or algorithm development.

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

Not applicable. As there is no training set mentioned, the establishment of ground truth for it is not relevant.

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The Multi-Spot Slit Lamp Laser Adapter has two functional modes available to the physician: a single spot mode and a Multi-Spot (4 spot) mode. When the a single spot mode is selected, the preexisting slit lamp laser apparatus is available for all treatment functions for which it was designed as a laser photocoagulator. The multi-spot mode is intended for use with "Green-Only" ine marcr bood me energy for panretinal photocoagulation in the treatment of proliferative retinopathy.

The multi-spot slit lamp laser adapter is a non-powered reusable optical system which, when connected between the laser fiber and the slit lamp 200m optics, generates four spots in a square pattern. Through a rotary mechanism the user can select between single or multiple spot patterns. The multi-spot laser adapter mechanically mimics the fiber cable and will not effect or deactivate any existing salety interlocks. The lens system of the multi-spot adapter provides a one-to-one image of the laser fiber, therefore the spot size indicator on the zoom lens systems is not effected. The selection of single or multiple spot patterns also applies to the aiming beam, this gives the user direct and unambiguous feedback on which mode is selected before treatment begins.

This document describes a 510(k) premarket notification for the Infinitech Multi-Spot™ Slit Lamp Laser Adapter. It focuses on demonstrating substantial equivalence to predicate devices rather than presenting a performance study with specific acceptance criteria. Therefore, most of the requested information regarding detailed study design and acceptance criteria is not present in the provided text.

Here is an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in terms of numerical performance metrics (e.g., sensitivity, specificity, accuracy, or other quantifiable measures used in clinical studies for diagnostic or treatment devices). Instead, it relies on demonstrating substantial equivalence to predicate devices. The "reported device performance" is described qualitatively in the "Efficacy" section and through the comparison chart.

2. Sample Size Used for the Test Set and Data Provenance
The document does not describe a "test set" in the context of a formal clinical performance study or data-driven evaluation. The assessment is based on the design and functionality of the device in comparison to existing predicate devices. Therefore, there is no sample size or data provenance information provided.

3. Number of Experts Used to Establish Ground Truth and Their Qualifications
This information is not provided as there was no study requiring expert-established ground truth in the context of a clinical performance evaluation. The substantial equivalence argument relies on comparing technical and functional characteristics.

4. Adjudication Method for the Test Set
This information is not provided as there was no formal test set or adjudication process described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance
This information is not applicable and not provided. The device is an optical accessory for a laser, not an AI or diagnostic imaging device that would involve human readers or AI assistance in interpretation.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
This information is not applicable and not provided. The device is a mechanical/optical accessory, not an algorithm. Its performance is intrinsically linked to its use by a human operator with a laser and slit lamp.

7. The Type of Ground Truth Used
This information is not provided as no explicit performance study requiring ground truth was described. The "ground truth" for this 510(k) submission is the functional and safety characteristics demonstrated to be substantially equivalent to predicates.

8. The Sample Size for the Training Set
This information is not provided as there was no AI model or learning algorithm requiring a training set.

9. How the Ground Truth for the Training Set was Established
This information is not provided as there was no AI model or learning algorithm requiring a training set and ground truth.

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