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The uMC 560i is intended to provide digital imaging of patients during diagnostic and surgical procedures. Examples of clinical application may include, but are not limited to: orthopedic, pain therapy, neurological, pediatric examinations and critical care. The visualization of such anatomical structures assists the clinical decisions. This device does not support direct radiographic film exposures and is not intended for use in performing mammography.

uMC 560i is the first mobile C-arm X-ray system developed and produced by UIH Medical XR Business Unit. It is designed to meet medical institutions' demands. To cover the most surgical imaging needs, it's X-ray imaging of the anatomical structures of patient during clinical applications may include, but are not limited to: orthopedic, pain therapy, neurological, pediatric examinations and critical care. uMC 560i consists of C-arm, Monoblock, Anti-scatter Grid, CMOS flat panel detector, Collimator system, Exposure handswitch, Exposure footswitch, Connects cables for Monitor cart and C-arm mobiles stand. Monitor cart, Touchable control panel, HD monitor, Examination workstation. The powerful system performance brings a safe, fluent and efficient operation experience.

The provided text is a 510(k) summary for the uMC 560i Mobile C-arm X-Ray System. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting acceptance criteria and a detailed study proving the device meets those criteria from an AI performance perspective.

Therefore, the document does NOT contain information about:

• Specific quantitative acceptance criteria for AI performance.
• A standalone study proving the device meets AI acceptance criteria.
• Sample sizes for a test set in the context of AI performance.
• Data provenance for a test set (country of origin, retrospective/prospective).
• Number of experts or their qualifications for establishing AI ground truth.
• Adjudication method for an AI test set.
• A multi-reader multi-case (MRMC) comparative effectiveness study for AI improvement.
• Whether a standalone (algorithm only) performance study was done for AI.
• The type of ground truth used for AI (expert consensus, pathology, outcomes data, etc.).
• Sample size for a training set (for AI).
• How ground truth for a training set was established (for AI).

Instead, the document focuses on non-clinical and clinical tests to demonstrate the safety and effectiveness of the uMC 560i X-ray system itself, comparing its technical specifications and performance against a predicate device.

Here's an analysis of the provided information concerning the device's performance and testing:

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

The document doesn't provide a direct "acceptance criteria" table in the sense of specific thresholds for diagnostic accuracy, but rather lists compliance with various national and international standards and then compares specific technical specifications to a predicate device. The "performance" is implicitly deemed acceptable if it complies with these standards and is substantially equivalent to the predicate.

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

• Test Set Sample Size: Not explicitly stated for the clinical evaluation. The text only mentions "fluoroscopy sequences images and static images produced by the uMC 560i in clinical environment."
• Data Provenance: Not explicitly stated. The device manufacturer is in Shanghai, China, which might imply the clinical evaluation was conducted there, but this is not confirmed. It was conducted "in clinical environment," implying prospective data collection for this evaluation.

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: "a board-certified clinical reviewer" (singular).
• Qualifications: "board-certified clinical reviewer." No specific years of experience or specialty (e.g., radiologist, although likely given the device type) are provided.

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

• Adjudication Method: "None" or not applicable, as only a single reviewer was used. The reviewer provided a "statement indicating that images are of diagnostic quality."

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:

• No MRMC comparative effectiveness study was done or reported. This submission is for an X-ray imaging system, not an AI-powered diagnostic aid for human readers.

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

• This device is not an AI algorithm; it is an X-ray imaging system. Therefore, a standalone algorithm-only performance study is not applicable and was not done.

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

• For the clinical evaluation, the "ground truth" for image quality was based on the subjective assessment of a "board-certified clinical reviewer" stating that images were of "diagnostic quality." This is closer to expert opinion/assessment of image quality rather than a definitive disease diagnosis confirmed by pathology or outcomes.

8. The sample size for the training set:

• Not applicable. This is not an AI device with a distinct training set.

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

• Not applicable.

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