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ENCOMPASS Eagle 3D is intended to acquire two-dimensional digital panoramic and cephalometric radiographies, and multi-field of view 3D computed tomography images of dento-maxillo-facial region for the purpose of advanced diagnosis at the direction of qualified dental healthcare professionals

The ENCOMPASS Eagle 3D is a complete 3-in-1 system for dental imaging capable of make Tomography, Digital Panoramic Profiles and Digital Cephalometric Profiles. The machine uses a CCD sensor technology with the traditional scintillator technologies and auto image processing that speeds up the diagnostic and improves the clinic workflow. 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 the ENCOMPASS Eagle 3D CBCT/Panoramic/Cephalometric Dental X-ray device and its substantial equivalence to a predicate device (PREXION 3D ECLIPSE). However, it does not detail a study with specific acceptance criteria and reported device performance in the way a clinical performance study for an AI/ML SaMD would.

Instead, the document focuses on demonstrating substantial equivalence based on technical specifications and performance testing against the predicate device, a common approach for traditional medical devices like X-ray systems.

Here's a breakdown of the information that is available, formatted to address your request as much as possible, along with explanations of why some requested information is not present:

Acceptance Criteria and Device Performance for ENCOMPASS Eagle 3D

The device is an X-ray system, and its "performance" is primarily assessed by comparing its technical specifications and image quality characteristics (like MTF and DQE) to those of a legally marketed predicate device. The underlying acceptance criterion is that the new device should be substantially equivalent to the predicate device in terms of safety and effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

For an X-ray device, "acceptance criteria" for demonstrating substantial equivalence are typically aligned with relevant electrical, mechanical, environmental, and radiation safety standards, as well as key imaging performance metrics (e.g., resolution, noise). The "reported device performance" is then how the new device measures up against these (often implicitly defined by the predicate's performance).

2. Sample size used for the test set and the data provenance

The document states: "In accordance with the FDA guidance document on Solid State X-Ray Imaging Devices, clinical images were acquired with both the new device and the predicate device."

• Sample Size: The exact number of clinical images or cases used is not specified.
• Data Provenance: The country of origin and whether the data was retrospective or prospective are not specified. It is implied to be prospective data collection for the purpose of the submission since images were "acquired with both the new device and the predicate device" for comparison.

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

• Number of Experts: "a licensed dentist" assessed the clinical images. This implies one expert.
• Qualifications of Experts: "a licensed dentist." No further details on experience or specialization are provided in this summary.

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

• Given that only "a licensed dentist" performed the comparison, there was no adjudication method (like 2+1 or 3+1 consensus) in the traditional sense, as there was only one reviewer.

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

• No MRMC comparative effectiveness study was done. This device is an X-ray imaging system, not an AI/ML-driven diagnostic software. The comparison was primarily on the physical and imaging characteristics of the hardware and the quality of the images produced, rather than reader performance with or without AI assistance.

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

• No standalone algorithm performance study was done. This is a hardware device for image acquisition, not a software algorithm.

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

• For the clinical image comparison, the "ground truth" was implicitly established by the judgment of a single licensed dentist who compared images from the new device and the predicate device for diagnostic ability, sharpness, and quality. This is a form of expert assessment or expert-generated truth. There's no mention of pathology or outcomes data being used for this comparison.
• For the technical performance metrics (MTF, DQE), the "ground truth" comes from standard physical measurements using phantoms and calibrated equipment.

8. The sample size for the training set

• Not applicable / Not specified. This device is an X-ray imaging system, not an AI/ML algorithm that requires a "training set" in the context of machine learning. The device is trained/calibrated during manufacturing and installation processes, but this is distinct from an AI model's training data.

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

• Not applicable / Not specified. As explained above, there isn't a "training set" in the AI/ML sense for this hardware device.

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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 with CCD sensor is a complete system for dental imaging capable of Digital Panoramic Profiles and Digital Cephalometric Profiles. The machines use a sensor CCD sensor technology with the traditional scintillator technologies and auto image processing that allow a speed up the diagnostic and improve the clinic workflow. 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). ONLY THE SENSOR HAS CHANGED.

The provided text describes the ENCOMPASS HF100-Eagle Panoramic/Cephalometric X-Ray with CCD sensor. Based on the information, here's a description of the acceptance criteria and the study that proves the device meets them:

Acceptance Criteria and Device Performance

The device sought substantial equivalence to its predicate device (K110371, Encompass made for Panoramic Corp.). The acceptance criteria appear to be focused on achieving comparable diagnostic quality, sharpness, and overall image quality to the predicate device, as well as meeting relevant safety and performance standards.

Table of Acceptance Criteria and Reported Device Performance:

Overall Result: "All test results were satisfactory." and the clinical summary states the images were found to have comparable diagnostic quality, sharpness, and overall quality.

Study Details:

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

   • Sample Size: Not explicitly stated. The text only mentions "the predicate and new device pan and ceph images."
   • Data Provenance: Not specified. It does not mention the country of origin of the data, nor whether the data was retrospective or prospective.

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

   • Number of Experts: "a licensed dentist" (singular).
   • Qualifications of Experts: A "licensed dentist." No further details on experience level (e.g., years of experience, specialization) are provided.

3. Adjudication method for the test set:

   • Adjudication Method: Not specified. With only one expert reviewing, there was no adjudication process (like 2+1 or 3+1 consensus). The assessment was based on a single licensed dentist's review.

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:

   • MRMC Study: No, an MRMC study was not done. The evaluation involved a single licensed dentist comparing images from the new device and the predicate device, not assessing human reader performance with or without AI assistance. This device is an X-ray machine with a new sensor, not an AI-assisted diagnostic tool.

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

   • Standalone Performance: Not applicable in the context of an X-ray imaging device itself. The device produces images for human interpretation. The "resolution figures" and technical performance tests (safety, EMC, X-ray standards) could be considered standalone performance metrics for the device's technical capabilities, but not a standalone diagnostic "algorithm" performance.

6. The type of ground truth used:

   • Ground Truth Type: Expert opinion/consensus. In this case, it was the opinion of a single "licensed dentist" who evaluated the diagnostic quality, sharpness, and overall quality of the images. There is no mention of pathology or outcomes data being used as ground truth.

7. The sample size for the training set:

   • Sample Size: Not applicable. The device is an X-ray machine with a new sensor, not a machine learning model that requires a "training set" in the conventional sense. The "auto image processing" mentioned is likely built-in firmware/software rather than a continually learning AI.

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

   • Ground Truth Establishment: Not applicable, as there is no mention of a training set for a machine learning model.

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

The PC-1000 panoramic X-ray machine provides a panoramic picture, showing 70-80% more anatomy than a standard series of full-mouth X-rays. Inscribed lines and an angled mirror aid in accurately establishing the Frankfort plane and the midsagittal plane. In addition, the numbered temple supports allow accurate measurement of skull density for proper kVp settings, eliminating the guess work typical in panoramic radiography.

The provided text describes a 510(k) premarket notification for the Model PC-1000 Panoramic / Cephalometric X-ray Systems. This document is a predicate device comparison for substantial equivalence rather than a study demonstrating an AI device's performance against acceptance criteria.

Therefore, many of the requested categories for AI device performance are not applicable to this submission. The document focuses on showing the new device is as safe and effective as a previously marketed device (K882436) through benchmarking its characteristics against the predicate and compliance with relevant standards.

Here's an attempt to address the request based on the available information, noting the significant gaps due to the nature of the submission:

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Acceptance Criteria:

The study proving the device meets the acceptance criteria is detailed in the "Summary of Safety and Effectiveness" (referred to as Exhibit 2, although content from the exhibit is spread across the provided text) which broadly states: "The results of bench, user, and standards testing indicates that the new device is as safe and effective as the predicate devices."

The "Substantial Equivalence Chart" (likely part of Exhibit J) explicitly compares the characteristics of the new Model PC-1000 (Modified) against the predicate Model PC-1000 (K882436). The conclusion states: "After analyzing bench, user, and standards testing data, it is the conclusion of Panoramic Corporation that the Model PC-1000 Panoramic / Cephalometric X-ray Systems are as safe and effective as the predicate device, have few technological differences, and have no new indications for use, thus rendering them substantially equivalent to the predicate device."

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

• Sample Size: Not specified. The document references "bench, user, and standards testing data" without providing specific numbers of tests conducted or units observed.
• Data Provenance: Not specified. This type of submission would typically involve internal testing by the manufacturer (Panoramic Corp.) and potentially accredited lab testing for standards compliance. The document does not mention country of origin for data or if it was retrospective/prospective.

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

• Not Applicable. This is a comparison of hardware technical specifications and compliance with safety standards, not a diagnostic accuracy study requiring expert ground truth for image interpretation.

4. Adjudication method for the test set:

• Not Applicable. As above, this is not an diagnostic accuracy or image interpretation study. Adjudication methods are common for clinical studies involving disagreement among readers/experts.

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:

• Not Applicable. This is not an AI device or a diagnostic aid. It's a conventional panoramic/cephalometric X-ray system.

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

• Not Applicable. This device does not have an "algorithm only" component in the way an AI diagnostic or analytical tool would.

7. The type of ground truth used:

• For technical specifications (e.g., kVp, focal spot, exposure time, current), the "ground truth" would be established by physical measurements and calibration according to industry standards and engineering principles.
• For compliance with standards (e.g., 21 CFR Part 1020, IEC standards, UL Listing), the "ground truth" is verified through audits and specific tests mandated by those standards, conducted by the manufacturer or accredited testing bodies.

8. The sample size for the training set:

• Not Applicable. This is not a machine learning or AI device that requires a training set.

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

• Not Applicable. As above, no training set for an AI/ML algorithm is involved.

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