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Dental Sensors, models NanoPix1 and NanoPix2 are intended to collect dental x-ray photons and convert them into electronic impulses that may be stored, viewed, and manipulated for diagnostic use by dentists. This device must only be used in hospital environments, clinics or dental offices by trained and qualified dental personnel, and not used in the oxygenrich environment. This device is suitable for providing dental radiography imaging for both adult and pediatric.

Dental Sensors, models NanoPix1 and NanoPix2, are feature 20um pixel pitch CMOS sensor with directly deposited CsI:Tl scintillator which ensures optimal resolution. An easy to use hi-speed direct USB interface enables a simple connection to a PC without need for an additional control box. The intra-oral software application makes it easy to acquire, enhance, analyze, view and share images from the sensor. The major function of NanoPix1 and NanoPix2 are to convert the X-ray to digital image, with the application of high resolution X-ray imaging. This detector is the key component of NanoPix system, enables to complete the digitalization of the medical X-ray imaging with the NanoPix software.

The provided text describes a 510(k) premarket notification for Dental Sensors NanoPix1 and NanoPix2. This documentation primarily focuses on establishing substantial equivalence to a predicate device (Digital Intraoral X-ray Imaging System, models Pluto0001X and Pluto0002X, K210312), rather than detailing an independent study to prove the device meets specific acceptance criteria in the way a de novo or PMA submission might.

Therefore, the information you're requesting regarding acceptance criteria, sample sizes, expert involvement, and ground truth establishment for a study proving the device performance is largely not present in the provided 510(k) summary.

However, I can extract the information that is available, including the performance characteristics that were compared to establish substantial equivalence.

Here's a breakdown of the available information:

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

Since this is a 510(k) for substantial equivalence, formal "acceptance criteria" for a specific study proving novel performance are not explicitly stated. Instead, the performance of the proposed devices (NanoPix1, NanoPix2) is compared to the predicate device (Pluto0001X, Pluto0002X) to demonstrate that they are technologically similar and perform equivalently. The "acceptance criteria" here implicitly align with matching or performing comparably to the predicate device.

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

The document states that "Non-clinical test data characterizes all performance aspects of the device based on well-established scientific and engineering principles". This typically refers to bench testing and physical measurements of the device's characteristics (like spatial resolution, MTF, signal-to-noise ratio, etc.). It does not mention a specific "test set" in terms of patient data or clinical images, nor does it detail sample sizes for such a set or data provenance.

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

This information is not provided. As no clinical test set is detailed, there's no mention of experts establishing ground truth for such a set.

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

This information is not provided, as no clinical test set is detailed.

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 MRMC study was reported or indicated. The submission is for a dental sensor (hardware plus basic image viewing software), not an AI-powered diagnostic tool. The software described is for image acquisition, enhancement, viewing, and reporting, not for automated diagnosis or assistance in a way that would require a comparative effectiveness study with human readers.

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

The device is a dental sensor and associated software for image viewing and manipulation. It is not an algorithm designed for standalone diagnostic performance. Thus, a standalone algorithm performance study is not applicable or mentioned.

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

For the non-clinical studies mentioned, the "ground truth" would be scientific and engineering measurements based on established standards for imaging device performance (e.g., direct measurement of spatial resolution, MTF, signal-to-noise ratio). There is no mention of clinical ground truth (like pathology or expert consensus on clinical images) as clinical studies were not deemed necessary for this 510(k) submission.

8. The sample size for the training set:

This information is not applicable and not provided. The device is an imaging sensor, not a machine learning model that requires a training set in the conventional sense. The "NanoPix software" mentioned performs image processing, viewing, and management functions, not AI-driven diagnostic tasks that would necessitate a large training dataset for model development.

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

This information is not applicable and not provided, as there is no mention of a training set for a machine learning model.

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