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The RAYSCAN a- P, SC, OCL, OCS panoramic X-ray imaging system with Cephalostat is an extra-oral source X-ray system, intended for dental radiographic examination of the teeth, jaw, and oral structures, to include panoramic examinations and implantology and for TMJ studies and cephalometry. Images are obtained using the standard narrow beam technique.

RAYSCAN α-Expert (RAYSCAN α-P, SC, OCL, OCS) provides panoramic for scanning teeth, jaw and oral structures. By rotating the C-arm, which houses a high-voltage generator, an all-in-one Xray tube and a detector on each end, panoramic images of oral and maxillofacial structures are obtained byrecombining data scanned from different angles. Functionalities include panoramic image scanning for obtaining images of whole teeth, and a Cephalometric scanning option for obtaining Cephalic images.

The provided text describes a 510(k) premarket notification for the "RAYSAN α-Expert" dental X-ray system. The submission affirms its substantial equivalence to a predicate device, K142058. While it outlines several tests conducted to support this claim, it does not provide explicit acceptance criteria in a table format nor does it detail a specific study with quantitative performance metrics for a direct comparison against such criteria.

Here's a breakdown of the information that can be extracted, and where there are gaps regarding the requested specifics:

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

The document does not provide a table of acceptance criteria with corresponding device performance metrics. Instead, it states that "All test results were satisfactory" for performance (imaging performance) testing conducted according to IEC 61223-3-4. It also mentions that "a licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use." This indicates a subjective assessment of image quality rather than quantitative performance against defined acceptance criteria.

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

• Test Set Sample Size: The document mentions that "images were gathered from all detectors of RAYSCAN α-Expert using protocols with random patient age, gender, and size" and that "Clinical imaging samples were collected from new detectors on the proposed device at the two offices where the predicate device was installed for the clinical test images." However, it does not specify the exact number of images or patients in the clinical test set.
• Data Provenance: The images were collected "at the two offices where the predicate device was installed for the clinical test images." The manufacturer is Ray Co., Ltd. located in South Korea. It's implied these are prospective clinical images gathered for the purpose of the submission.

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)

• Number of Experts: "The clinical performance of RAYSCAN α-Expert were clinically tested and approved by two licensed practitioners/clinicians."
• Qualifications of Experts: They are described as "licensed practitioners/clinicians." No specific details such as years of experience, specialization (e.g., radiologist, dentist), or board certification are provided.

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

The document states, "A licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use." It implies individual review, but does not specify any formal adjudication method (e.g., whether the two practitioners independently reviewed images and consensus was reached, or if there was a third adjudicator in case of disagreement).

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 MRMC comparative effectiveness study is mentioned. This device is an X-ray imaging system, not an AI-assisted diagnostic tool for humans, so this type of study would not be applicable. The comparison is between the new device's image quality and the image quality of the predicate device.
• Effect Size: Not applicable.

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

This refers to an X-ray imaging device, not an algorithm. Therefore, "standalone (algorithm only)" performance is not applicable. The device's primary function is image acquisition.

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

The ground truth for the clinical image quality assessment appears to be expert opinion/consensus (from two licensed practitioners) regarding whether the images were "of acceptable quality for the intended use." There's no mention of pathology or outcomes data for establishing ground truth.

8. The sample size for the training set

The document mentions software validation, but this X-ray system is not described as an AI/ML device that requires a distinct "training set" in the context of machine learning model development. This question is not directly applicable to the type of device described.

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

As the device is not described as involving an AI/ML model with a training set, this question is not directly applicable. The software mentioned is for saving patient and image data, inquiries, and image generation, and was validated according to FDA guidance for software in medical devices, not specific AI/ML training.

Summary of what is present and what is missing:

• Acceptance Criteria/Performance Table: Not provided in the requested format. General statement of "satisfactory" test results and "acceptable quality."
• Test Set Sample Size & Provenance: Sample size not quantified. Provenance is South Korea, likely prospective.
• Number & Qualification of Experts: Two licensed practitioners/clinicians. No further qualification details.
• Adjudication Method: Not specified.
• MRMC Study: Not applicable.
• Standalone Performance: Not applicable.
• Type of Ground Truth: Expert opinion on image quality.
• Training Set Sample Size: Not applicable (not an AI/ML device in this context).
• Training Set Ground Truth: Not applicable.

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RCT800 is CBCT and panoramic x-ray imaging system with cephalometric. Which is intended to radiographic examination of the dento-maxillofacial, sinus, TMJ, Airway for diagnostic support for adult and pediatric patients. And a model scan is included as an option. Cephalometric image is also includes wrist to obtain carpus images for growth and maturity assessment for orthodontic treatment. The device is to be operated and used by dentists or other legally qualified health care professionals.

The system's purpose is RCT800, a 3D computed tomography scanner for scanning hard tissues like bones and teeth. By rotating the c-arm, which is embedded with an all-in-one x-ray tube and a detector on each end, CBCT images of the dental maxillofacial area can be attained by recombining data from the same level that is scanned from different angles. Additionally, the system includes a panoramic image scanning function for attaining images of the whole teeth, a cephalometric scanning option for attaining a cephalic image, and a Model Scan option for attaining a dental model CBCT image.

The provided text describes the 510(k) summary for the Ray Co., Ltd.'s RCT800 device. While it mentions various tests and compliance with standards, it does not explicitly provide a table of acceptance criteria and reported device performance in the typical format of a clinical study report with specific metrics and thresholds. Instead, it states that "All test results were satisfactory" for performance (imaging performance) testing conducted according to IEC 61223-3-4 and IEC 61223-3-7.

It also mentions "Clinical images were provided" and that "A licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use," but it doesn't detail a formal clinical study with specific acceptance criteria beyond subjective expert opinion.

Therefore, much of the requested information regarding the study that proves the device meets the acceptance criteria in a quantifiable manner (e.g., statistical significance, specific performance numbers) is not present in the provided document. The document primarily focuses on demonstrating substantial equivalence to a predicate device through technical similarities, bench testing, and compliance with general safety and performance standards.

However, based on the provided text, I can infer and extract some information:

Acceptance Criteria and Device Performance (Inferred from compliance statements)

Since the document states that "All test results were satisfactory" for imaging performance tests and that a licensed practitioner found clinical images to be of "acceptable quality for the intended use," the implied acceptance criteria were met. However, the specific quantitative criteria are not listed.

Table 1: Implied Acceptance Criteria and Reported Device Performance

Study Details (Based on the provided text)

1. Sample sizes used for the test set and the data provenance:

   • Test Set (Clinical Images): The document states "Clinical imaging samples were collected from new detectors on the proposed device at the two offices where the predicate device was installed for the clinical test images. These images were gathered from all detectors installed with RCT800 using protocols with random patient age, gender, and size."
     • Specific Number: Not specified. It indicates "samples" and "images gathered from all detectors," implying a collection across multiple patient demographics, but no numerical count is provided.
     • Provenance: Clinical images obtained from "two offices where the predicate device was installed." The country of origin is not explicitly stated for these clinical images, but the applicant (Ray Co., Ltd.) is from SOUTH KOREA, so it is plausible these were collected within South Korea or countries where the predicate device was installed.
     • Retrospective/Prospective: Not explicitly stated, but the mention of collecting "new detectors" and "random patient age, gender, and size" suggests some form of prospective or concurrent collection for evaluation.

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

   • Number of Experts: "Two licensed practitioners/clinicians" clinically tested and approved the features. "A licensed practitioner reviewed the sample clinical images." It's unclear if these refer to the same "two" or one specific "licensed practitioner."
   • Qualifications: "Licensed practitioners/clinicians." No further details on their years of experience, subspecialty (e.g., specific type of radiologist/dentist), or formal board certifications are provided.

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

   • The document states "A licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use." This suggests a qualitative assessment, but no formal adjudication method (like 2+1 consensus) is described. It implies that the single or (if two practitioners were involved) potentially un-adjudicated opinion of the expert(s) served as the "truth."

4. 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 MRMC study was mentioned. The document focuses on demonstrating that the device itself produces images of acceptable quality for human interpretation, not on the improvement of human readers with AI assistance. This device is a source of images (an X-ray system), not an AI algorithm for image analysis.

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

   • The device is a medical imaging system (CT/panoramic/cephalometric X-ray system), not an AI algorithm for image analysis. Therefore, the concept of "standalone performance" for an algorithm does not apply in the context of this device. The performance refers to the image acquisition capabilities of the system itself.

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

   • For clinical image quality, the ground truth was expert opinion/assessment by "licensed practitioners/clinicians" who deemed the images "of acceptable quality for the intended use."
   • For bench testing, the ground truth was based on compliance with standards (e.g., IEC 61223-3-4, IEC 61223-3-7) and "designated tolerance" parameters.

7. The sample size for the training set:

   • This device is an X-ray imaging system. It takes images (presumably raw data) and reconstructs them into clinically useful images using reconstruction algorithms such as FBP (Filtered Back Projection) (as mentioned for the predicate device). The document does not describe the use of machine learning that would require a "training set" in the conventional AI sense. If any internal algorithms are adaptable or "learn," details are not provided. The phrase "training set" is typically applicable to AI/ML devices, which this is not identified as in the provided text.

8. How the ground truth for the training set was established:

   • Not applicable, as no training set (for AI/ML) is mentioned or implied for this device.

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