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SeeFactorCT3 is a cone beam computed tomography x-ray imaging system that acquires sequences of the head including the ear, nose and throat (ENT), dento-maxillofacial complex, teeth, mandible and jaw, temporo-mandibular joint (TMJ), other areas of human skull and neck with sections of upper cervical spine, and upper and lower extremities for use in diagnostic support. The device displays two and three dimensional images for each examined anatomical region.

The device is operated and used by physicians, dentists, x-ray technologists and other legally qualified professionals.

See Factor CT3 is a Diagnostic CBCT (Cone Beam Computed Tomography) device that integrates High Definition Computed Tomography (HDCT) for obtaining High Resolution 3D Volume with 2D High Resolution Scouting, through Dynamic Scouting and Single Pulse Modality.

This document is a 510(k) Premarket Notification from the FDA, which focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than providing a detailed performance study with acceptance criteria and clinical trial data. Therefore, many of the requested details about acceptance criteria, study design, and performance metrics are not available within this document.

Here's what can be extracted and what cannot:

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

• Cannot be provided. This document does not specify quantitative acceptance criteria for image quality or clinical performance, nor does it present a table of reported device performance against such criteria. The basis of the 510(k) is substantial equivalence, not a demonstration of specific performance metrics.

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

• Test Set Sample Size: "Living and deceased animals were imaged during the development of this device. A substantial number of diagnostic-quality animal images are shown in the appendices." No specific number is given for the "test set" as a formal clinical trial with a defined test set wasn't conducted or reported in this summary.
• Data Provenance: The document explicitly states "No clinical testing was performed in the development of this product." The "diagnostic-quality animal images" do not have specified provenance (e.g., country of origin, retrospective/prospective).

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)

• Not applicable. Since "No clinical testing was performed" and no human clinical test set was established for ground truth validation, there's no mention of experts, their number, or qualifications for establishing ground truth on a test set.

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

• Not applicable. No clinical test set and no expert ground truth establishment means no adjudication method was used or reported in this context.

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. An MRMC study was not done. This device is a CT imaging system, not an AI-powered diagnostic assist tool. The 510(k) focuses on the physical device's equivalence to a predicate, not its impact on human reader performance.

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

• Not applicable. This device is an imaging system, not an algorithm, so algorithm-only performance is not relevant or reported here. Its "performance" would be related to image quality, dose, scan time, etc., and this is primarily addressed by demonstrating technological equivalence and by showing "diagnostic-quality animal images."

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

• Not explicitly stated in the context of a formal "ground truth" establishment for performance evaluation. The "diagnostic-quality animal images" are presented as supportive data for the device's capabilities, but not as part of a structured clinical ground truth validation. The core of the 510(k) is the comparison of technical characteristics to a predicate device.

8. The sample size for the training set

• Not applicable. This document describes a physical medical imaging device, not a machine learning algorithm that requires a "training set" in the computational sense.

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

• Not applicable. See point 8.

Summary of Device and Performance Information from the Document:

• Device Name: SeeFactorCT3
• Regulation Number: 21 CFR 892.1750 (Computed tomography x-ray system)
• Product Code: OAS
• Regulatory Class: Class II
• Intended Use: Cone beam computed tomography x-ray imaging system that acquires sequences of the head (ENT, dento-maxillofacial, teeth, TMJ, skull, neck, upper cervical spine) and sections of upper and lower extremities for use in diagnostic support. Displays 2D and 3D images.
• Predicate Device: K142222 (NewTom 5G, THEMA S.r.l., Italy)
• Reference Device: K130442 (NewTom VG i and NewTom 5G, THEMA S.r.l., Italy)
• Performance Claim: The device operates the same as the predicate (same power source, image acquisition method, intended use, indications for use, target professional healthcare workers).
• Distinguishing Features (claimed superiority): "superior imaging resolution, it weighs less, it can be moved and it can be covered during surgical procedures should there be a need." (Note: This is a claim, not a quantitative performance metric substantiated in this summary).
• Non-Clinical Data: "Living and deceased animals were imaged during the development of this device. A substantial number of diagnostic-quality animal images are shown in the appendices." (Appendices 2, 3, and 4).
• Clinical Testing: Explicitly stated, "No clinical testing was performed in the development of this product."

In essence, this FDA 510(k) document is a regulatory submission demonstrating substantial equivalence to a predicate device based on technological characteristics and non-clinical data, rather than a clinical study report with detailed performance metrics against pre-defined acceptance criteria.

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