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Anyview-500R fluoroscopic mobile x-ray system is radiation medical equipment only used by professional radiologists. This product is designed to provide fluoroscopic and spot film images of the patient during diagnostic and interventional procedures.

This system can be applied in emergency room, operation room, cast room or etc. of hospital.

This device is a mobile x-ray fluoroscopic imaging system used by radiation experts. This device is a fluoroscopic imaging system to visualize human body's anatomical structure using a principle that x-ray qenerates hypophonesis difference when penetrating human body depending on tissue's density and thickness. The device is composed of main body, x-ray generating equipment (x-ray controller, high voltage generator, x-ray tube, motortype collimator), image collecting equipment (Image Intensifier, CCD Camera) and digital imaging system (cart including computer and monitor). The product's arm is mobile and rotatable in X, Y and Z axes, which facilitates use of x-ray in every direction.

ANYVIEW imaging software is a Digital Imaging System (DIS) designed for C-arm, Anyview-500R. ANYVIEW imaging software provides useful functions to manage X-ray images obtained from Anyview 500R C-arm.

ANYVIEW imaging software provides various image tools. One of the most noticeable features is that the C-arm images taken during an exam are stored in the database for further review. Image data is integrated with the patient information in DICOM(OPTION) compatible format which allows compatibility with existing DICOM and PACS system. All these features are available in a single application program, ANYVIEW.

The provided text describes a 510(k) premarket notification for the "Anyview-500R Fluoroscopic Mobile X-ray System," focusing on its substantial equivalence to a predicate device, KMC-950 (K032761). The document primarily addresses the technical specifications and safety standards rather than detailed acceptance criteria for an AI-powered device or a study proving its performance against such criteria.

Therefore, many of the requested details about acceptance criteria, study design for AI evaluation, expert qualifications, and ground truth are not applicable or not provided in the given text.

Here's an attempt to answer the questions based only on the provided text:

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

The document does not explicitly define "acceptance criteria" in the context of a specific performance threshold for an AI-powered device. Instead, it demonstrates substantial equivalence by comparing the technical characteristics and adherence to safety standards of the new device (Anyview-500R) against a predicate device (KMC-950).

The performance comparison is detailed in tables on pages 6, 7, and 8. The provided text highlights differences in specifications such as Resolution, Output Power, Fluoroscopy Pulsed mode, Radiography mAs range, and Image Intensifier Contrast. However, these are technical specifications, not acceptance criteria for an AI device's clinical performance.

Note: The differences are discussed on page 9, stating that the Anyview-500R has a higher resolution CCD camera (1K x 1K vs 512 x 512) and requires less X-ray source, which leads to lower capacity for the X-ray generator and tube heat storage compared to the predicate device. These differences "do not raise additional risk concerns" and "do not have an effect on safety and effectiveness compared to the predicate device."

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

The document explicitly states: "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification. Bench testing was performed to assess the device safety and effectiveness." (Page 10, Section 11).

Therefore, there was no clinical test set, and hence no sample size, data provenance, or other details related to a clinical test set are provided. The evaluation was based on non-clinical (bench) testing.

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)

As per the answer to question 2, no clinical test set was used, and therefore, no experts were utilized for establishing ground truth for a clinical test set.

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

Not applicable, as no clinical test set was used.

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. The device is a fluoroscopic mobile x-ray system, not an AI-assisted diagnostic tool.

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

Not applicable. The device is an X-ray imaging system, not a standalone algorithm.

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

Not applicable, as no clinical studies were performed. The "ground truth" for the device's substantial equivalence was based on its technical specifications, conformance to recognized international electrical and safety standards (e.g., IEC 60601 series, NEMA PS 3.1-3.20, 21 CFR 1020.30-32), and software validation and verification testing (page 10).

8. The sample size for the training set

Not applicable, as this is not an AI/machine learning device. The "training" for the device's development would refer to engineering design and testing, not a dataset in the context of AI.

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

Not applicable, as this is not an AI/machine learning device. The "ground truth" during development would be engineering specifications and compliance with established standards.

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