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The MP-1 MICRO PERIMETER is indicated for use as :

• Color retinography .
• Fixation examiner ●
• Fundus-related microperimetry .
• Visual rehabilitation. .

The Nidek Technologies Srl MP-1 MICRO PERIMETER is an instrument for the diagnosis of retinal diseases. It is able to capture infrared live sequences and color images of the patient retina through CCD cameras and at the same time to project light stimuli on the retina in those retinal positions chosen by the operator.
The MP-1 MICRO PERIMETER is supplied with Xenon light and Halogen light sources suitable for performing the above described examinations.
The system includes also a suitable Insulation transformer, a LCD S-VGA Monitor and an IBM Personal Computer, which incorporates the dedicated NAVIS software (with Windows 2000 operative system).

The provided text describes the MP-1 Micro Perimeter and its substantial equivalence to a predicate device, but it does not contain information about specific acceptance criteria or a study proving that the device meets those criteria with performance metrics. The document is a 510(k) premarket notification summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting detailed performance studies against pre-defined acceptance criteria.

However, based on the provided text, here's what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in the provided text. The document asserts that the device "meets all specified requirements" without detailing what those requirements are or providing specific numerical targets for performance.
• Reported Device Performance: Not numerically reported in the provided text. The document broadly states that "The performance data indicate that the modified MP-1 MICRO PERIMETER device meets all specified requirements, and is substantially equivalent to the predicate device." No specific metrics (e.g., sensitivity, specificity, accuracy, precision for different examinations) are given.

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

• Test Set Sample Size: Not specified in the provided text.
• Data Provenance: Not specified in the provided text (e.g., country of origin, retrospective/prospective).

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

• Not specified in the provided text.

4. Adjudication method for the test set:

• Not specified in the provided text.

5. Multi Reader Multi Case (MRMC) comparative effectiveness study:

• No, an MRMC comparative effectiveness study is not mentioned. The document focuses on demonstrating substantial equivalence of the device itself (MP-1 MICRO PERIMETER) to predicate devices, not on comparing human reader performance with and without AI assistance.

6. Standalone (algorithm only without human-in-the-loop performance) study:

• Yes, implicitly. The claim of "performance data indicate that the modified MP-1 MICRO PERIMETER device meets all specified requirements" implies that the device's technical specifications and functions (e.g., ability to capture images, project stimuli, record answers, compensate for eye movements, generate sensitivity maps) were tested and found to perform as intended. However, details of these tests (like specific metrics, methodologies, or data used) are not provided. The device itself is an instrument, not an AI algorithm that produces a diagnostic output for human review in the same way modern AI systems do. Its 'standalone' performance refers to its ability to accurately execute its functions (image capture, stimulus projection, etc.).

7. Type of ground truth used:

• Not specified in the provided text. For a device like this, ground truth would likely be based on:
  • Clinical observation/diagnosis: For evaluating the relevance and accuracy of the generated sensitivity maps or fixation information against a patient's actual condition.
  • Known physical properties/measurements: For validating the accuracy of stimulus projection or image capture.

8. Sample size for the training set:

• Not applicable/Not specified. This device pre-dates the widespread use of deep learning AI, so a "training set" in the modern sense (for an AI algorithm) is not relevant to this submission. If there were calibration or development data, it is not mentioned.

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

• Not applicable/Not specified (as per point 8).

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