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Planmeca Viso is a system intended to produce two-dimensional (2D) and three-dimensional (3D) digital x-ray images as well as three-dimensional (3D) optical images of the dento-maxillo-facial, cervical spine and Throat) regions at the direction of healthcare professionals as diagnostic support for pediatric and adult patients.

The Planmeca Viso -X-ray unit uses cone beam computed tomography (CBCT) to produce three-dimensional (3D) images of the maxillofacial and ENT anatomies. Two dimensional (2D) images are produced with tomosynthesis method (panoramic) imaging) as well as conventional 2D radiography (cephalometric imaging, 2D views). In CBCT a cylindrical volume of data is captured in one imaging procedure. The data consists of several hundred sample images which are taken from different directions to cover a certain pre-programmed target area. These samples are used for 3D reconstruction (using a separate 3D reconstruction PC) that can be viewed in three dimensions using separate workstation and Planmeca Romexis software.

The provided text describes a 510(k) premarket notification for the Planmeca Viso, a CT X-ray system. However, the document focuses on establishing substantial equivalence to a predicate device rather than presenting detailed acceptance criteria and a study proving the device meets those criteria, as would typically be seen in a clinical performance study for an AI/CAD device.

The document primarily compares the technical characteristics and intended uses of the Planmeca Viso with its predicate device (Planmeca ProMax 3D Max) and reference devices. It states that "Results from performance bench testing demonstrate that Planmeca Viso produces substantially equivalent image quality compared to the predicate and reference devices," but does not provide specific acceptance criteria or the details of these performance bench tests.

Therefore, based on the provided text, it is not possible to fully answer all aspects of your request, especially regarding acceptance criteria, sample sizes, expert involvement, and ground truth establishment in a clinical performance study context for an AI device. The document is a regulatory clearance letter, not a detailed study report.

However, I will extract and infer what information is available and highlight what is missing.

Acceptance Criteria and Device Performance (based on provided text):

The document does not explicitly state quantitative acceptance criteria or corresponding device performance in a table format for diagnostic accuracy (e.g., sensitivity, specificity, AUC). Instead, the "acceptance criteria" appear to be met by demonstrating substantial equivalence to a predicate device in terms of intended use, technological characteristics, and image quality as determined through "performance bench testing."

Study Details (as much as can be inferred from the provided text):

1. Sample size used for the test set and the data provenance:

   • The document mentions "performance bench testing" but does not specify the sample size of images or patients used for these tests.
   • Data provenance (e.g., country of origin, retrospective/prospective) is not mentioned.

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

   • This information is not provided. The document refers to "diagnostic support for pediatric and adult patients" at the "direction of healthcare professionals," but it does not detail the process of establishing ground truth for evaluating device performance.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • This information is not provided.

4. 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 describe an MRMC study or any AI components, nor does it discuss human reader improvement with or without AI assistance. The device is a "Computed tomography x-ray system" (hardware).

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

   • The document focuses on the imaging system itself (hardware) rather than an AI algorithm. Therefore, "standalone performance" in the context of an algorithm is not applicable or discussed.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • This information is not provided. For an imaging device, ground truth for image quality often involves quantitative metrics (e.g., spatial resolution, contrast-to-noise ratio, dose efficiency) derived from phantoms or objectively evaluated clinical images against a reference standard, but the specific methods are not detailed here.

7. The sample size for the training set:

   • This information is not applicable as the document describes a hardware device (CT X-ray system), not a machine learning/AI algorithm that would typically have a "training set."

8. How the ground truth for the training set was established:

   • This information is not applicable for the same reason as above.

Summary of Missing Information (Critical for a complete answer to your prompt):

The provided document is a 510(k) clearance letter for an imaging device (Planmeca Viso). It confirms the device's substantial equivalence to a predicate device. It lacks the detailed clinical study information (acceptance criteria, specific metrics, sample sizes, ground truth establishment, expert involvement, and reader studies) that would typically be required for evaluating the performance of an AI-driven diagnostic device. The "performance data" mentioned is stated to be from "bench testing" demonstrating image quality equivalence, rather than a clinical performance study with human readers or diagnostic accuracy metrics.

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