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VIVIX-S FW series is used for the general-purpose diagnostic procedures, and as well as intended to replace radiographic film/ screen systems. The VIVIX-S FW series is not intended for mammography applications.

VIVIX-S -FW, a series for of flat panel detectors models named; FXRD-2530FAW, FXRD-3643FAW, FXRD-4343FAW, with imaging areas of 25cm x 30cm, 36cm x 43cm, 43cm x 43cm, respectively. The detectors can acquire static images as well as fluoroscopic images up to 6fps.

The device intercepts x-ray photons and the scintillator (Cesium lodide) emits visible spectrum photons that illuminate an array of photo (a-SI)-detectors that create electrical signals. After the electrical signals are generated, it is converted to digital value is transmitted either by wire via cable or wirelessly through a system control unit (SCU), and the software called Vxvue acquires and processes the data values from the detector. The SW is of moderate level of concern. On the Vxvue, the use can view as well as perform basic manipulations such as (rotation, enlargement, etc.) on the acquired images. These devices should be integrated with an operating PC and an X-Ray generator. It can be utilized to digitalize x-ray images and transfer for radiography diagnostic.

The provided text describes a 510(k) summary for a digital flat panel X-ray detector, VIVIX-S FW, and its substantial equivalence to a predicate device, VIVIX-S VW. The study focuses on demonstrating that the new device provides images of equivalent diagnostic capability to the predicate devices.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for substantial equivalence are primarily based on demonstrating non-inferiority or equivalence to the predicate device in terms of "Performance (MTF)" and "Performance (DQE)," and meeting current spatial resolution standards. While the document states "similar performance," the exact acceptance thresholds (e.g., within a certain percentage point) for MTF and DQE are not explicitly quantified as absolute acceptance criteria values in the provided text. Instead, observed values are compared to the predicate.

Note on "Equivalence" Column in the provided table: The provided document's table includes an "Equivalence" column which states "Equivalent" for characteristics like Common Name, Classification Name, etc. For MTF, DQE, and Spatial Resolution, this column is blank in the source document, indicating a direct comparison rather than a simple "Equivalent" stamp. The text states "There is similar performance as follow" for MTF and DQE, and the table then lists the values.

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

The document states: "A single-blinded concurrence study according to CDRH's Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices was conducted, and the study confirmed that the new x-ray detectors VIVIX-S FW provide images of equivalent diagnostic capability to the predicate devices..."

• Sample Size: The specific sample size (number of images or cases) used for the clinical test set is not explicitly stated in the provided text.
• Data Provenance: The provenance (country of origin, retrospective/prospective) of the data used for the clinical study is not explicitly stated in the provided text.

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

The document mentions "a single-blinded concurrence study," which implies expert review. However:

• Number of Experts: The specific number of experts involved in establishing ground truth or evaluating images for the test set is not explicitly stated.
• Qualifications of Experts: The qualifications of these experts are not explicitly stated.

4. Adjudication Method for the Test Set

The document refers to a "single-blinded concurrence study." While this implies a comparison of images by readers, the specific adjudication method (e.g., 2+1, 3+1, none) for the test set is not explicitly stated. "Concurrence" suggests agreement among readers, but the process for resolving disagreements or establishing a definitive ground truth from the expert readings is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Improvement with AI vs. Without AI Assistance

• MRMC Study: The document describes a "single-blinded concurrence study" comparing the VIVIX-S FW device to predicate devices. This sounds like it could be an MRMC-like study in its nature of comparing image quality or diagnostic capability, but it's focused on device equivalence rather than AI assistance.
• AI Assistance Effect Size: The device described (VIVIX-S FW) is a digital X-ray detector, not an AI-powered diagnostic tool. Therefore, the study is not assessing the improvement of human readers with AI assistance. The concept of "AI vs. without AI assistance" is not applicable to this device and study.

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

The device is an X-ray detector, which captures images. Its performance is evaluated through objective metrics like MTF and DQE, and through a clinical "concurrence study" involving human interpretation of the images produced by the device, comparing them to images from a predicate device. This is not an "algorithm-only" performance evaluation in the context of an AI algorithm, but rather a standalone evaluation of the image acquisition hardware. The non-clinical data (MTF, DQE, spatial resolution) are objective measures of the device's technical image quality, which can be seen as a form of standalone performance evaluation in the engineering sense.

7. The Type of Ground Truth Used

The clinical study is described as a "concurrence study" to confirm "equivalent diagnostic capability." This strongly suggests that the ground truth for diagnostic capability was established by expert consensus or through a process where experts evaluated the images for diagnostic equivalence. It does not mention pathology, outcomes data, or other definitive methods as the primary ground truth.

8. The Sample Size for the Training Set

The provided text describes a 510(k) for a hardware device (digital X-ray detector) and its associated software for image processing and viewing (Vxvue). It does not mention machine learning or AI models requiring a "training set." Therefore, a training set sample size is not applicable and not provided in this document.

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

Since there is no mention of an AI model or training set, this question is not applicable based on the provided information.

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