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KP-View 3D is intended to produce two-dimensional digital x-ray images including panoramic and cephalometric image, and three-dimensional digital x-ray images of the dental, oral, maxillofacial region, at the direction of healthcare professionals as diagnostic support for adult and pediatric patients.

This device is not intended for use on patients less than approximately 21 kg (46 lb) in weight and 113 cm (44.5 in) in height; these height and weight measurements approximately correspond to that of an average 5 year old.

The product ( Dental Cone-beam Computed Tomography, Model: KP-View 3D) uses cone-beam computed tomography (CBCT) through X-ray cone-beam, panoramic radiography, cephalometric radiography to produce images of the dental, oral and maxillofacial areas to provides diagnostic details for the medical facilities. This product consists of Frame, X-ray generator (including Integrated X-ray source tube head, X-ray tube, Collimator), Image receptor and Image processing system (including Computer, Monitor, and Software workstation).

The provided document is a 510(k) summary for the Yian Medical Technology (Haining) Co., Ltd. KP-View 3D Dental Cone-beam Computed Tomography system.

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a tabular format for the device's performance in the way a clinical study might. Instead, it demonstrates substantial equivalence to a predicate device (iDT901X1 Dental Cone-beam Computed Tomography, K232710) by comparing technical specifications and performance characteristics. The acceptance is based on meeting safety and performance standards relevant to dental X-ray equipment.

Here's a table summarizing key comparable technical and performance characteristics, as presented in the document, which implicitly serve as a basis for acceptance by showing equivalence to the already-cleared predicate:

The "acceptance criteria" can be inferred to be that the subject device's performance characteristics, as demonstrated through non-clinical bench testing, are equivalent to those of the predicate device, and that it complies with relevant recognized standards for safety and performance (e.g., IEC 60601 series for electrical and radiation safety, IEC 62366 for usability, IEC 62304 for software lifecycle, ISO 14971 for risk management).

2. Sample Size for the Test Set and Data Provenance

The document states, "The subject of this premarket submission, did not require clinical studies to support substantial equivalence." Therefore, there is no test set of patient data from clinical studies. The testing relies on non-clinical bench testing to demonstrate equivalence. The provenance of any underlying data that informed the predicate device's clearance is not mentioned here, as this is a Special 510(k) focused on modifications to an already cleared device.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

Not applicable, as no clinical study with a test set requiring expert-established ground truth was conducted. The assessment is based on technical equivalence and compliance with standards.

4. Adjudication Method for the Test Set

Not applicable, as no clinical study with a test set was conducted.

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 device is a dental cone-beam CT system, not an AI-powered diagnostic software. The submission focuses on hardware and software equivalence for image acquisition and processing.

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

Not applicable. This is not an algorithm-only device. It is a medical imaging system. Its performance is assessed through its ability to produce images that meet quality and safety standards, as demonstrated through bench testing.

7. The Type of Ground Truth Used

For non-clinical testing, the "ground truth" would be established by reference to engineering specifications, phantom measurements, and compliance with recognized standards (e.g., image quality metrics like spatial resolution (5lp/mm) measured with phantoms, radiation dose measurements, electrical safety checks).

8. The Sample Size for the Training Set

Not applicable. This is not an AI/machine learning device that requires a training set in the conventional sense. The device is a traditional medical imaging system.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as no training set was used.

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