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Agfa's DX-D FLFS is indicated for acquiring images for measurements in the orthopedic field (skeleton).

Agfa's DX-D FLFS is a direct radiography accessory, similar to the predicate. The device allows the user to stitch multiple acquired images of long patient anatomies (like a full leg or full spine) into a single patient image. This is particularly useful for making measurements during orthopedic examinations. The DX-D FLFS includes an optional software license for its NX workstation (for image processing) and a patient stand with grid.

The Agfa DX-D FLFS is an accessory for direct radiography systems that allows stitching multiple images of long patient anatomies (like a full leg or full spine) into a single image, useful for orthopedic measurements.

Here's an analysis of its acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not specified. The document states "Design verification tests confirm the device meets specifications" and "Performance of the complete system has been validated," but it does not provide quantities for test sets or details on the images used.
• Data Provenance: Not specified. There is no information provided about the country of origin of the data or whether it was retrospective or prospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set:

• Adjudication Method: Not specified. The document does not describe any expert review or adjudication process for establishing ground truth for the test set.

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. The document explicitly states: "No clinical testing was performed in the development of the DX-D FLFS." This device is more about image processing and stitching rather than an AI diagnostic aid requiring reader performance comparison.

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

• Standalone Study: Yes, in essence, the testing conducted was a standalone performance evaluation of the stitching algorithms and system. "Stitching algorithms operate as planned with expected measurement accuracy. Performance of the complete system has been validated." The device's primary function is automated image stitching, so these tests evaluate the algorithm performs its intended function independently.

7. The type of ground truth used:

• Type of Ground Truth: The ground truth for the performance claim of "expected measurement accuracy" is implied to be based on engineering specifications and potentially phantoms or simulated data designed to test the stitching and measurement capabilities. No independent expert review, pathology, or outcomes data is mentioned as ground truth.

8. The sample size for the training set:

• Sample Size: Not specified. The document does not provide details on any training data used for the stitching algorithms.

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

• Ground Truth Establishment: Not specified. Given the absence of clinical testing and the focus on engineering validation, it's likely the algorithms were developed and refined based on internal technical metrics and potentially synthetic or standardized images, rather than a formally established clinical ground truth for training.

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