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PreXion3D Excelsior is intended to produce two dimensional digital panoramic 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 images 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 a 510(k) premarket notification for the PreXion3D Excelsior device, a dental Cone-beam Computed Tomography (CT) system. The submission aims to establish substantial equivalence to a predicate device (K161881). The key modification is the addition of a "Complete mode" for CT scans, which simulatively creates a wider Field of View (FOV) by extending the FOV height.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Assessment: The document states that the 3D MTF results for the Complete mode met the predicate device criteria, implying that the spatial resolution in the extended FOV is comparable. However, no specific numerical acceptance threshold or performance value for 3D MTF is provided in the document. The general acceptance criteria are implicit: the modified device should perform as well as the predicate device in relevant aspects.

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

The document does not explicitly state the sample size used for the performance testing.

• It mentions "the stitching area of the volume data of Complete mode" was assessed, but the number of cases or images is not quantified.
• Data Provenance: Not specified. It can be inferred that the testing was performed by the manufacturer, PreXion Corporation, likely in Japan, given their address. There is no information on whether the data was retrospective or prospective.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

The document does not provide information on the number of experts used or their qualifications to establish ground truth for the test set. The assessment appears to be a technical measurement (3D MTF) rather than relying on expert radiographic interpretation as ground truth.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method. Since the primary performance testing mentioned is a technical measurement (3D MTF), an adjudication method by experts would not be applicable in this context.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

The document does not indicate that an MRMC comparative effectiveness study was performed. The focus is on technical equivalence and performance of the device itself, not on human reader performance with or without AI assistance.

6. If a Standalone Study (i.e., algorithm only without human-in-the-loop performance) Was Done

The performance testing mentioned ("assessment of 3D MTF") is inherently a standalone (algorithm only) evaluation, as it objectively measures image quality characteristics of the device's output without human intervention for interpretation.

7. The Type of Ground Truth Used

The ground truth for the performance testing (3D MTF) appears to be based on technical standards and predicate device criteria for image quality measurements. It is not based on expert consensus, pathology, or outcomes data.

8. The Sample Size for the Training Set

The document does not provide information on a training set sample size. This device is a CT imaging system (hardware and associated software for image reconstruction), not an AI/ML algorithm that typically requires a separate training set. The "software modifications" refer to changes that allow for the expanded FOV and reconstruction, not necessarily a machine learning model that needs a training set for diagnostic tasks.

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

Since there is no mention of a training set for an AI/ML algorithm, this information is not applicable/not provided. The "ground truth" concerning the device's functionality and image reconstruction capabilities would have been established through engineering design, simulations, and empirical testing against known physical phantoms or established imaging standards.

In summary:

This 510(k) submission primarily focuses on demonstrating technical equivalence for a modification to an existing CT device. The performance testing described is a technical assessment of image quality (3D MTF) in the newly introduced "Complete mode" to ensure it meets established (predicate device) criteria. It does not involve diagnostic performance studies with human readers, expert consensus on images, or AI/ML training data.

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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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