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PreXion3D Excelsior is intended to produce two dimensional digital panoranic and cephalometric images, and three dimensional digital x-ray images of the maxillofacial, and ENT (Ear, Nose and Throat) region at the direction of healthcare professionals as diagnostic support for adult and pediatric patients.

Cephalometric imaging also includes the hand wrist to obtain carpus innages for growth and maturity assessment.

PreXion3D Excelsior consists of a scanner, which is used for generating X-ray and detecting image data, and a Console, which is used for operating the scanner and managing the data. The scan data acquired by the scanner will be transferred to the Console. PreXion3D Excelsior Image Analysis System will then perform the image analysis (2D/3D) or image edition (creating cross-section diagram, etc.), and output the image to a printer.

During scanning, X-rays are generated from the x-ray tube head mounted in the arm of the scanner and the x-rays passing through a patient are then detected by the flat panel detector of the scanner under the control of the firmware inside and the console software installed on the qualified Computer. The detected x-ray absorption data is processed by the console software to reconstruct the diagnostic images. The PreXion3D Excelsior has three operation modes, CT scan, Panoramic scan and Cephalometric exposure.

The provided text describes the PreXion3D Excelsior, a dental cone-beam computed tomography device, and its substantial equivalence to predicate devices, but it does not contain the detailed acceptance criteria or a specific study proving the device meets those specified acceptance criteria in the way requested by your prompt.

Specifically, the document states:

• Non-clinical performance data: Conformance to harmonized standards (listed in section 5.7), testing for 3D imaging performance to assess MTF (Modulation Transfer Function) for three image orientations (x, y, z) for 3D modes, and non-clinical considerations according to FDA Guidance "Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices."
• Clinical performance data: Clinical considerations according to FDA Guidance "Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices" were performed by qualified clinical assessors.

However, the document lacks specific quantitative acceptance criteria (e.g., minimum MTF values, specific accuracy thresholds for diagnostic tasks) and detailed results from a study that would demonstrate the device met those specific criteria. The evaluation focuses on substantial equivalence based on conformance to standards and general considerations rather than a detailed performance study with defined acceptance criteria and statistical analysis.

Therefore, I cannot populate the table and answer the following questions with the provided text:

1. A table of acceptance criteria and the reported device performance: The document lists standards it conforms to but does not quantify specific acceptance criteria (e.g., for image quality, diagnostic accuracy) with corresponding performance values.
2. Sample sizes used for the test set and the data provenance: Not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. It mentions "qualified clinical assessors" for clinical considerations but no further detail.
4. Adjudication method: Not specified.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: Not mentioned.
6. Standalone (algorithm only) performance study: Not mentioned. The device is a hardware imaging system, not an AI algorithm in the typical sense for standalone performance.
7. Type of ground truth used: Not specified.
8. Sample size for the training set: Not applicable as this is a hardware device submission, not an AI algorithm requiring a training set in the machine learning sense.
9. How the ground truth for the training set was established: Not applicable.

The document's purpose is to establish substantial equivalence based on technological characteristics and general safety/effectiveness considerations, not to provide a detailed performance study against specific, quantified acceptance criteria for a novel diagnostic algorithm.

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