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The NewTom VG Computed Tomography X-ray System is a dedicated X-ray imaging device that acquires a 360-degree rotational X-ray sequence of images for use as diagnostic support in radiology of the dento-maxillo-facial complex and in the field of maxillofacial surgery.

The NewTom VG accomplishes this task by reconstructing a three-dimensional matrix of the examined volume, producing two-dimensional views of this volume and displaying both two-dimensional images and three-dimensional renderings.

The NewTom VG Computed Tomography X-Ray System (NewTom VG) is a dedicated X-ray imaging device that acquires a 360-degree rotational X-ray sequence of images. It then reconstructs a three-dimensional matrix of the examined volume and produces two-dimensional views of such volume, displaying both two- and three-dimensional images. The NewTom VG can measure distances and thickness on two-dimensional images. Such images can be printed or exported on magnetic and optical media.

The NewTom VG hardware, including a scanner unit (comprised of an X-ray source, flat panel detector and a motorized arm) and a control box. facilitates the acquisition of a full X-ray sequence by the device software. The NewTom VG software runs on an x86 architecture based workstation. The NewTom VG reconstructs a three-dimensional model of x-ray images similar to the threedimensional model obtained using the parent NewTom 3G Computed Tomography X-Ray System (NewTom 3G).

This 510(k) summary for the NewTom VG Computed Tomography X-Ray System indicates that the device met all requirements during performance testing. However, it does not explicitly state acceptance criteria or provide a detailed study that proves the device meets specific performance criteria. Instead, it relies on substantial equivalence to a predicate device (NewTom 3G Computed Tomography X-Ray System K041137) and general performance testing for electrical safety, EMC/EMI, and verification/validation.

Therefore, much of the requested information cannot be extracted directly from the provided text.

Here's a breakdown of what can be inferred or cannot be found:

1. A table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

• Number of Experts: Not specified. This type of information would typically be relevant for studies evaluating diagnostic accuracy, which is not detailed in this 510(k) summary.
• Qualifications of Experts: Not specified.

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

• Adjudication Method: Not specified.

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

• MRMC Study: No, an MRMC comparative effectiveness study is not mentioned. This device is an X-ray system, not an AI-assisted diagnostic tool. The document focuses on the system's ability to acquire and reconstruct images, not on its impact on human reader performance in conjunction with AI.
• Effect Size of AI Improvement: Not applicable.

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

• Standalone Performance: Not explicitly detailed in terms of qualitative or quantitative metrics. The document describes the system's ability to reconstruct 3D models and produce 2D views, which implies its standalone image generation capabilities. However, no specific performance study of the algorithm's output quality as a standalone component is described with measurable results.

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

• Type of Ground Truth: Not specified. Given the nature of a 510(k) for an imaging device, ground truth for image quality might be related to objective phantom measurements or comparison to established imaging standards. However, details of such a process are not provided in this summary.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This document describes an X-ray imaging system, not an AI model that requires a training set.

9. How the ground truth for the training set was established

• Ground Truth for Training Set Establishment: Not applicable.

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