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Alphard Model X178 is an x-ray device (cone beam computed tomography) that acquires a single 360 degree rotational sequence of the head and neck areas, including the ENT and dentomaxillofacial area for use in diagnostic support. The device is operated and used by physicians, dentists, and x-ray technologists.

Alphard series 3D X-ray CT realizes wide area imaging by adopting the principle of cone beam CT and using high-resolution wide area flat panel detector (FPD). Alphard series enables dentist to take wide range imaging from small area to wide area with appropriate imaging mode according to various treatment objects. Combination of advanced FPD (dynamic range: 14bit) and micro focus X-ray tube provides high resolution CT image from soft tissue to hard tissue. Our original software AsahiVision freely displays high picture quality 3D image and MPR image.

The provided text is a 510(k) summary for the Alphard Model X178 Dental Cone Beam CT system. This document focuses on demonstrating substantial equivalence to existing legally marketed devices rather than establishing specific performance acceptance criteria and a detailed study proving those criteria are met for the new device.

Therefore, much of the requested information (acceptance criteria, specific performance metrics, sample sizes for test/training, number and qualifications of experts, adjudication methods, MRMC studies, standalone performance, and ground truth for training data) is not present in the provided 510(k) summary.

The document implicitly "proves" the device meets acceptance criteria by demonstrating substantial equivalence to predicate devices through a comparison of indications for use and technical specifications. The acceptance criterion is essentially that the device is "as safe and effective" as the predicates.

Here's a breakdown of what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Implicit via Substantial Equivalence): The primary "acceptance criteria" presented is that the Alphard Model X178 Dental Cone Beam CT system is substantially equivalent to the predicate devices (K052587 and K063622) in terms of safety, effectiveness, technological characteristics, and indications for use.

Reported Device Performance: The document provides technical specifications for the Alphard and compares them to the predicate devices. The "performance" is considered adequate if these specifications fall within acceptable ranges relative to the predicates, implying similar image quality and functional capabilities.

Conclusion on Equivalence: "After analyzing both bench and user testing data as well as external laboratory testing to applicable standards, it is the conclusion of Takara Belmont Corporation that the Alphard Model X178 Dental Cone Beam CT System is as safe and effective as the predicate devices, has few technological differences, and has no new indications for use, thus rendering it substantially equivalent to the predicate devices."

The following information is not provided in the 510(k) summary:

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

• Not specified. The document mentions "bench, test laboratory and clinical testing" and "user testing data" but does not provide details on sample sizes, types of data (e.g., patient cases vs. phantoms), or provenance (country, retrospective/prospective).

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

• Not specified. Given the nature of a substantial equivalence submission for imaging hardware, a detailed expert-based ground truth assessment of diagnostic performance (as would be seen in an AI software submission) is typically not required or detailed in this summary.

4. Adjudication method for the test set

• Not specified.

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. This is a hardware submission, not an AI or software submission. An MRMC study comparing human readers with and without AI assistance is not relevant or included.

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

• No. This is a hardware submission. "Standalone performance" in the context of an algorithm is not applicable here.

7. The type of ground truth used

• Not specified in detail. The document mentions "bench, test laboratory and clinical testing." For hardware, ground truth typically involves physical measurements, phantom studies for image quality metrics (resolution, noise, contrast), and potentially clinical assessments of image interpretability (without a formalized ground truth process for diagnostic accuracy as for AI).

8. The sample size for the training set

• Not applicable/Not specified. This pertains to an imaging device itself, not an AI algorithm requiring a training set. The device produces images based on physical principles, not a trained model.

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

• Not applicable/Not specified. See point 8.

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