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Agfa's DX-D Imaging Package is indicated for use in general projection radiographic applications to capture for display diagnostic quality radiographic images of human anatomy. The DX-D Imaging Package may be used wherever conventional screen-film systems may be used.

Agfa's DX-D Imaging Package is not indicated for use in mammography.

The device is a direct radiography imaging system of similar design and construction to the predicate. Agfa's DX-D Imaging Package uses the company's familiar NX workstation with MUSICA2 TM image processing and flat panel detectors of the scintillator-photodetector type. Flat panel detectors with scintillators of both Cesium lodide (Csl) and Gadolinium Oxysulfide (GOS) are available. The device is used to capture and directly digitize x-ray images without a separate digitizer common to computed radiography systems. This new version uses a previously cleared detector with wireless communication capability.

The device uses a direct conversion process to convert x-rays into a digital signal. X-rays incident on the scintillator layer of the detector generate light that is absorbed by photo-detectors, converted to a digital signal and sent to the workstation the data is processed by Agfa's MUSICA image processing software. The acronym MUSICA stands for Multi-Stage-Image-Contrast-Amplification. MUSICA-acts on the acquired images to preferentially enhance the diagnostically relevant, moderate and subtle contrasts.

The provided 510(k) summary does not contain specific acceptance criteria for device performance, nor does it detail a study proving the device meets particular quantitative metrics. Instead, it focuses on demonstrating substantial equivalence to a predicate device.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

As noted, the document does not specify quantitative acceptance criteria or performance metrics in the way your request implies (e.g., sensitivity, specificity, accuracy). The evaluation is based on comparison to a predicate device and adherence to industry standards for safety and image quality.

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

• Sample Size: Not specified. The document mentions "Image quality measurements have been completed" and "Image quality comparisons between the new and predicate devices have been performed as well. Sample images have been provided." This implies a set of images was used for comparison, but the size is not disclosed.
• Data Provenance: Not specified. Given the nature of a 510(k) demonstrating substantial equivalence for an imaging system, these would likely be technical image quality test images (e.g., phantoms) rather than clinical patient data. The summary states, "No clinical testing was performed in the development of the DX-D Imaging Package."

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

This information is not provided in the 510(k) summary. Since "No clinical testing was performed," it is unlikely that human experts were involved in establishing ground truth for a clinical test set from patient data. The "ground truth" for technical image quality assessments would be derived from the known properties of the phantoms used and objective image quality metrics.

4. Adjudication Method for the Test Set

This information is not provided. Given the lack of clinical testing and expert involvement, an adjudication method for a clinical test set is not applicable here.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states: "No clinical testing was performed in the development of the DX-D Imaging Package." Therefore, no effect size of AI assistance could be reported.

6. If a Standalone (algorithm only without human-in-the-loop performance) Study was Done

The device is an imaging system (hardware and software for image acquisition and processing), not an AI algorithm intended for diagnostic interpretation. Therefore, a "standalone algorithm only" performance study in the context of interpretation accuracy (e.g., sensitivity/specificity for disease detection) is not applicable as it's outside the scope of this device's intended use or claim. The "performance" assessment focuses on image quality and system functionality.

7. The Type of Ground Truth Used

Based on "No clinical testing was performed," the ground truth for any image quality measurements would likely be based on physical phantom measurements and objective image quality metrics (e.g., spatial resolution, contrast-to-noise ratio, modulation transfer function, detective quantum efficiency) rather than expert consensus, pathology, or outcomes data from human subjects.

8. The Sample Size for the Training Set

This information is not applicable/not provided. The device is an X-ray imaging system with image processing (MUSICA2). While MUSICA2 is an image processing algorithm, the document describes it as enhancing contrast rather than performing diagnostic interpretation based on a trained model in the current AI sense. There is no mention of a "training set" for a machine learning model. The focus is on the physics of image acquisition and standard image processing.

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

This information is not applicable/not provided for the same reasons as #8. If MUSICA2 involves learned parameters, their derivation is not disclosed, but it's unlikely to involve a "ground truth" in the diagnostic context.

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