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The intraoral sensor is intended to convert x-ray photons into electronic impulses that may be stored, viewed and manipulated for diagnostic use by dentists.

The subject device SensorX device is an intraoral x-ray sensor for dental applications. It detects the x-rays and performs the image acquisition, digitizes the image and makes it available for the PC. The x-ray sensor is connected to the computer via the sensor cable, and if required, the USB extension. The x-ray sensor is equipped with protective cover sheaths (previously 510(k) cleared) and placed in the mouth of the patient. For patient comfort, the ergonomic design is based on human intraoral anatomy. SensorX enables high resolution with a minimum radiation dose. It is connected to a computer to produce an image almost instantaneously following exposure. The primary advantage of direct sensor systems such as SensorX, is the speed with which images are acquired. SensorX is activated via the imaging software VisionX (K192743) OR DBSWIN (K203287).

The provided document is a 510(k) Premarket Notification from DÜRR DENTAL SE for their device, SensorX. It primarily focuses on demonstrating substantial equivalence to a predicate device (DEXIS Titanium / KaVo IXS HD) rather than providing detailed acceptance criteria and a study proving the device meets those criteria in a traditional sense (e.g., a clinical trial with statistical endpoints).

Therefore, some of the requested information, particularly regarding specific performance metrics against pre-defined acceptance criteria, multi-reader multi-case studies, and detailed ground truth methodologies for a test set, is not explicitly present in this document. The document primarily relies on non-clinical data (i.e., technical specifications and compliance with standards) and a general statement about clinical images.

However, I can extract the available information as requested:

1. Table of Acceptance Criteria and Reported Device Performance

As specific, quantifiable acceptance criteria with corresponding performance results akin to a clinical trial are not presented in this 510(k) summary, I will infer the "acceptance criteria" from the technological characteristics compared to the predicate device, as substantial equivalence is the goal. The reported "device performance" will be the SensorX's specifications.

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

The document does not explicitly mention a "test set" in the context of an algorithm's performance with a specified sample size. Instead, it refers to "actual dental images were provided which showed excellent resolution and contrast" as part of the non-clinical data. The provenance of these images (e.g., country of origin, retrospective or prospective) is not specified.

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 in the document. The document states a "clinical evaluation was performed" and "actual dental images were provided," but it does not detail how ground truth was established for these images, nor the number or qualifications of any experts involved.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

The document does not mention any MRMC comparative effectiveness study. The SensorX is an intraoral x-ray sensor, not an AI-assisted diagnostic tool.

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

The SensorX device is a hardware component (an intraoral x-ray sensor) that captures images, not a standalone algorithm. Its performance is evaluated based on its technical specifications and image quality, not as an AI algorithm.

7. The Type of Ground Truth Used

The document states that "actual dental images were provided which showed excellent resolution and contrast." This implies an expert assessment of image quality, but the specific type of ground truth (e.g., expert consensus on specific pathologies, pathology reports, or patient outcomes data) is not detailed. Given the device's function as an imaging sensor, the ground truth would likely relate to image quality parameters such and resolution, contrast, and diagnostic interpretability by dentists, evaluated by experts.

8. The Sample Size for the Training Set

The document does not describe the use of a "training set" in the context of an AI algorithm, as the SensorX is a hardware device.

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

This is not applicable, as the document does not describe a training set for an AI algorithm.

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