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For Panoramic or Cephalometric diagnostic radiographic use in dental, oral surgery, and orthodontic practices.

The ENCOMPASS HF100- Eagle Panoramic X-Ray Machine is a complete system for dental imaging capable of: Film Panoramic Profiles Film Cephalometric Profiles Digital Panoramic Profiles Digital Cephalometric Profiles The digital machines use a sensor with CdTe/CMOS technology for imaging that allows for direct conversion between x-ray photons into voltage levels making it less noisy than traditional scintillator technologies. The equipment has three movement axes (two in orthogonal directions and one rotational) making it possible to execute elaborate imaging profiles. It features a complex profile movement around the dental arch and radiographic emission compensation in the spinal region, when necessary reconstructing the dental arch into a plane image. Each individual profile prioritizes a set of characteristics improving diagnostic capabilities. For example, the standard panoramic prioritizes image layer width, constant vertical magnification and homogeneous exposure along the whole image. Likewise, the low dosage profile prioritizes the reduction of dosage (time and anodic current).

The provided text describes a 510(k) premarket notification for the ENCOMPASS HF100- Eagle Panoramic/Cephalometric X-Ray device. This document focuses on demonstrating substantial equivalence to a predicate device and safety and performance testing for overall device functionality, rather than presenting a study to prove a specific algorithm's performance against defined acceptance criteria for diagnostic accuracy.

Therefore, the requested information regarding acceptance criteria, device performance metrics (like sensitivity, specificity, AUC), sample sizes for test/training sets, expert qualifications, ground truth establishment, or multi-reader multi-case studies for AI algorithm performance is not available in the provided text.

The document primarily addresses:

• Device Description: It's an X-ray machine for dental, oral surgery, and orthodontic practices.
• Safety and Performance: Electrical, mechanical, environmental safety, and X-ray specific compliance testing are mentioned. It states "Accuracy testing and software validation was performed. All test results were satisfactory." However, it does not detail what accuracy was tested or what the acceptance criteria were for this 'accuracy testing'.

Summary of available information:

1. A table of acceptance criteria and the reported device performance: Not explicitly stated for diagnostic accuracy criteria of an algorithm. The document mentions "Accuracy testing and software validation was performed. All test results were satisfactory." but does not provide specific metrics or criteria.
2. Sample size used for the test set and the data provenance: Not applicable/not provided for an algorithm performance study. The document refers to general device testing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/not provided.
4. Adjudication method for the test set: Not applicable/not provided.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done: No, not for an AI algorithm.
6. If a standalone was done: The "Accuracy testing and software validation" mentioned is for the overall device functionality, but not presented as a standalone clinical performance study for an AI algorithm.
7. The type of ground truth used: Not applicable/not provided for an AI algorithm performance study.
8. The sample size for the training set: Not applicable/not provided. This device is not described as having a machine learning component requiring a training set.
9. How the ground truth for the training set was established: Not applicable/not provided.

Conclusion:

This 510(k) summary focuses on the safety and effectiveness of the physical X-ray device and its equivalence to a predicate, not on the performance of a specific AI algorithm intended for diagnostic interpretation. The "accuracy testing" mentioned is likely related to the physical output and image quality of the X-ray machine itself, not a diagnostic algorithm's performance.

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