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Opal Chiro and 20/20 P-DR are intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography.

The Opal Chiro and 20/20 P-DR system represents the straightforward integration of a new digital x-ray receptor panel (cleared in K062376) and our previously cleared (K123644 and K133139) software. The Opal Chiro and 20/20 P-DR are Digital Radiography systems, featuring an integrated flat panel digital detector (FPD). The Opal Chiro and 20/20 P-DR is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a filmless environment and improves cost effectiveness. The major functions and principle of operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion + DR, K123644, wherein we combined our OPAL-RAD software with two new digital panels. The upgrade kits are compatible with modern HF diagnostic X-ray generators like Sedecal and CPI. The 20/20 P-DR has been tested with X-Cel 700/900 series of generators.

The provided text describes Opal Chiro and 20/20 P-DR, a Digital Radiography system. However, it does not contain specific acceptance criteria, detailed study designs, or performance metrics that would allow for a comprehensive answer to all parts of your request. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance studies against specific acceptance criteria.

Based on the available information, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for device performance. Instead, it relies on a qualitative assessment compared to a predicate device.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the sample size used for the clinical image acquisition and review. It states that "Clinical images were acquired and evaluated." The provenance of the data (country of origin, retrospective or prospective) is also not mentioned.

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

The test set involved evaluation by "a board certified radiologist." The number of experts is one. Their specific qualifications beyond "board certified radiologist" are not detailed (e.g., years of experience, subspecialty).

4. Adjudication Method for the Test Set

With only one radiologist evaluating the images, an adjudication method like 2+1 or 3+1 is not applicable or mentioned. The single expert's evaluation served as the basis for comparison.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study is not indicated. The document describes a comparison of images by a single radiologist against a predicate, not a study of human reader improvement with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The device itself is a digital X-ray receptor panel and associated software for image capture and processing. The performance evaluated here is essentially the standalone performance of the imaging system in producing images. It's not an AI algorithm in the sense of making diagnoses, but rather an image acquisition and processing system. The evaluation focused on the quality of the output images.

7. The Type of Ground Truth Used

The ground truth for the clinical images was established through expert visual assessment/consensus by a board-certified radiologist, comparing the images to those from a predicate device. There is no mention of pathology or outcomes data being used as ground truth.

8. The Sample Size for the Training Set

The document does not provide any information about a training set since the device described is an imaging system (hardware and associated software for image processing), not a machine learning model that typically requires a distinct training set. The software mentioned (OpalRad Software) is described as "previously cleared" and its major functions and principle of operation "were not changed," implying it was not "trained" in the typical AI sense for this submission.

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

Since there is no mention of a training set for an AI model, the method for establishing its ground truth is not applicable or described in this document.

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