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The DEXIS / KaVo sensor is a USB-driven digital sensor which is intended to acquire dental intraoral radiographic images. The DEXIS / KaVo sensor shall be operated by healthcare professionals, who are educated and competent to perform the acquisition of dental intra-oral radiographs. The DEXIS / KaVo sensor can be used either in combination with special positioning devices to facilitate positioning and alignment with the x-ray beam or it may also be positioned by hand with the assistance of the patient.

The DEXIS Titanium, Kavo IXS HD (Size 1, Size 2) intraoral sensors are an indirect converting x-ray detector, e.g. incident x-rays are converted by a scintillating material into (visible) light, this light is coupled optically to a light detection imager based on CMOS technology. The design of the sensor assembly supports the automatic detection of the incident x-rays to generate digital images for dental intra oral applications. The DEXIS Titanium, Kavo IXS HD (Size 1, Size 2) intraoral sensors supports USB2.0 connectivity to personal computers using a dedicated electronic assembly and a sensor software driver.

The provided text describes the KaVo Dental Technologies, LLC DEXIS Titanium, KaVo IXS HD (Size 1, Size 2) intraoral sensors. It concludes that clinical performance data was not needed to characterize performance and establish substantial equivalence. Therefore, there is no information about specific acceptance criteria related to clinical performance or a study proving the device meets such criteria.

The document focuses on non-clinical test data and substantial equivalence to a predicate device (DEXIS Sensor - K090458). It states that substantial equivalence is based on a comparison of intended use, indications, technological characteristics, principle of operation, features, and non-clinical performance data.

Here's an overview of the non-clinical performance testing and device characteristics provided, which indirectly serve as acceptance criteria for regulatory clearance:

1. Table of Acceptance Criteria (Implied Non-Clinical) and Reported Device Performance:

Since clinical performance criteria are explicitly stated as "not needed," the acceptance criteria are derived from the performance bench testing and conformance to international standards for extraoral source X-ray systems. The reported device performance is presented in the comparison table with the predicate device and in the list of standards met.

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

The document states "Clinical data is not needed to characterize performance." Therefore, there is no test set of patient data described for clinical validation. The testing described is non-clinical bench testing. The provenance of the data is not specified beyond being "non-clinical test data."

3. Number of Experts Used to Establish Ground Truth and Qualifications:

Not applicable, as no clinical study with a test set requiring expert ground truth establishment was conducted. The assessment relied on engineering and scientific principles and adherence to recognized standards.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical study with a test set requiring adjudication was conducted.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No MRMC study was performed or cited, as clinical data was deemed unnecessary for substantial equivalence. Therefore, there is no information on the effect size of AI assistance on human readers.

6. Standalone Performance Study:

A standalone performance assessment was effectively done through the non-clinical bench testing, where the device's technical specifications and adherence to international standards were evaluated independently. However, this is not a standalone clinical performance study in the sense of an algorithm-only evaluation against ground truth in a clinical context.

7. Type of Ground Truth Used:

For the non-clinical testing, the "ground truth" was based on established engineering principles, reference standards (e.g., test phantoms for X-ray resolution if applicable, though not explicitly stated), and regulatory compliance requirements for medical devices. There was no clinical ground truth (e.g., pathology, outcomes data) used in this submission.

8. Sample Size for the Training Set:

Not applicable, as this device is a hardware sensor, not an AI/ML algorithm that requires a training set in the conventional sense.

9. How the Ground Truth for the Training Set Was Established:

Not applicable, as it is a hardware device and not an AI/ML algorithm that requires a training set.

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