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NICAL SMART MICRO CR system for intraoral dental images is indicated for capturing, digitization and processing of intra oral x-ray images stored in imaging plate recording media.

The NICAL/SMART MICRO is a Computed Radiography System which produces the Xray diagnostic image in digital format instead of using traditional screens and film. This device utilizes reusable X-ray storage phosphor plate (IP) that is sensitive to X-ray and stores latent image when it is exposed to X-ray. After X-ray exposure to the X-ray storage phosphor plate, X-ray storage phosphor plate is scanned by means of laser in the device. Latent image in the X-ray storage phosphor plate is released in a form of light by laser scanning. Then the light is collect and converted into a form of digital image. The signal processing is made to the digital image data such as the digital filtering, the gain & offset correction and flat fielding. The image can then be viewed on a computer workstation, adjusted if necessary, then stored locally, sent to an archive, printed or sent to PACS system. After acquisition of the latent image from the X-ray storage phosphor plate, it is erased thoroughly to be reused.

The NICAL SMART MICRO CR System for Intraoral Dental Images (K143703) was deemed substantially equivalent to its predicate device, the FireCR Dental by 3D Imaging & Simulations Corp. (K131442), based on technical performance and indications for use.

Here's a breakdown of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance

The submission primarily focuses on demonstrating equivalence to the predicate device, rather than explicit "acceptance criteria" against regulatory standards (beyond general safety and quality). However, the comparison table provided acts as a de facto set of acceptance criteria, where the NICAL device is expected to perform comparably or better than the predicate.

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

• Test Set Sample Size: The document does not specify a distinct "test set" in terms of a number of images or cases for non-clinical image quality testing. It mentions a "verification report on image testing" to check image quality and resolution.
• Data Provenance: Not explicitly stated for the non-clinical image testing or clinical images. The clinical images were reviewed by a "Board Certified US based radiologist," implying the images themselves might be from a US context or at least reviewed by a US expert.

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

• Number of Experts: One.
• Qualifications of Experts: "Board Certified US based radiologist." No years of experience are specified.

4. Adjudication method for the test set

• Adjudication method: Not applicable/not described as a formal adjudication process. The document states, "Clinical Images were reviewed by a Board Certified US based radiologist and were found to be of excellent quality, suitable for the intended use." This suggests a single expert opinion rather than a multi-reader adjudication.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. This submission is for a Computed Radiography System, not an AI-based diagnostic aid that assists human readers.

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

• Standalone Performance: Not applicable in the context of an AI algorithm. The device itself is a standalone imaging system. The performance metrics reported (MTF, spatial resolution) are inherent to the device's image acquisition capabilities.

7. The type of ground truth used

• For the non-clinical image quality and resolution tests (e.g., MTF, spatial resolution), the "ground truth" would be established by physical measurements using standardized phantoms and imaging protocols.
• For the clinical images, the "ground truth" was effectively the expert opinion of a single Board Certified US based radiologist, who deemed them "of excellent quality, suitable for the intended use." This is closer to expert consensus (though only one expert) on diagnostic suitability rather than pathology or outcomes data.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This device is a Computed Radiography System; it is not an AI/ML device that requires a training set.

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

• Ground Truth for Training Set: Not applicable, as there is no training set for this type of device.

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