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HDI 1000 / HDI 1000A, an Intra-oral Imaging System, is used to collect dental x-rays photons and convert them into electronic impulses that may be stored, viewed, and manipulated for diagnostic use by dentists.

The HDI 1000 / HDI 1000A intra-oral imaging system is a device which acquires digital intra oral images. Direct digital systems acquire images with a solid-state sensor that is connected to a computer to produce an image almost instantaneously following exposure. The primary advantage of direct sensor systems is the speed with which images are acquired. The sensor is connected by a wire to an analog-to-digital converter box, which is connected to the computer. Images are produced within seconds of sensor exposure. The wire length from a direct sensor is about 3 meters and less. This wire plugs into an analogto-digital converter box. The converter box connects to the computer with a USB cable.

The provided text does not contain information about specific acceptance criteria or a study that proves the device meets those criteria with detailed performance metrics. The submission is a 510(k) summary for a digital dental intra-oral sensor (HDI 1000, HDI 1000A), which primarily focuses on demonstrating substantial equivalence to a predicate device.

The document states: "The indications for use, material, form factor, performance, and safety characteristics of HDI 1000 / HDI 1000A described in this 510(k) are the same as that of the predicate device, EzSensor of Rayence Co., Ltd." This indicates that the device is deemed acceptable because it performs similarly to an already approved device.

The "Summary for any testing in the submission" section mentions:

• Electrical, mechanical, environmental safety and performance testing according to standard IEC 60601-1: 2005 + CORR.1(2006) + CORR(2007).
• EMC testing conducted in accordance with standard IEC 60601-1-2:2007.
• Non-clinical & Clinical considerations according to FDA Guidance "Guidance for the Submissions of 510(k)'s for Solid State X-ray Imaging Devices" was performed.

It concludes that "All test results were satisfactory" and the device is "safe and effective and substantially equivalent to predicate device." However, specific quantitative acceptance criteria or detailed results from these tests are not provided in this summary.

Therefore, most of the requested information regarding detailed acceptance criteria, device performance, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness studies are not present in this 510(k) summary.

Here's a breakdown of what can be extracted and what is missing:

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

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

• Missing: The document does not specify any sample sizes for test sets or data provenance (e.g., country of origin, retrospective/prospective). The testing mentioned seems to be primarily engineering and regulatory compliance, not clinical performance studies with patient data to establish diagnostic accuracy.

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

• Missing: This information is not provided as there is no mention of a clinical study involving experts establishing ground truth for diagnostic accuracy.

4. Adjudication method for the test set

• Missing: Not applicable, as no clinical test set 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

• Missing: This is not an AI or CAD device. It's an imaging acquisition device. No MRMC study was conducted or is relevant based on the provided information.

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

• Missing: Not applicable. This is an imaging sensor, not an algorithm.

7. The type of ground truth used

• Missing: As no clinical performance study for diagnostic accuracy is described, there's no mention of ground truth established through expert consensus, pathology, or outcomes data. The "ground truth" for this device's acceptance is its ability to meet safety and performance standards (e.g., IEC standards) and demonstrate substantial equivalence to a predicate device.

8. The sample size for the training set

• Missing: Not applicable. This is an imaging sensor, not a machine learning model, so there is no "training set."

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

• Missing: Not applicable.

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