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XPlus 35 Series (XPLUS 35. XPLUS 35FD) are mobile digital C-arms designed to provide fluoroscopic and radiographic images of the patient during diagnostic, surgical and interventional procedures. Examples of clinical application may include endoscopy, orthopedic, neurologic, critical care and emergency room procedures. i.e. surgical interventions needing X-ray imaging and interventions inside and outside the operating room.

XPLUS 35 Series (XPLUS 35, XPLUS 35FD), C-arm mobile, is used for providing fluoroscopic image of patient anatomy, especially during diagnostic, surgical and interventional procedures. XPLUS 35 Series (XPLUS 35, XPLUS 35FD) consist of X-ray tube, X-ray generator, C-arm including image receptor, monitor cart, medical monitor and accessories such as foot switch and hand switch.

This document is a 510(k) premarket notification for the XPLUS 35 Series (XPLUS 35, XPLUS 35FD) mobile digital C-arm. It mainly focuses on demonstrating substantial equivalence to predicate devices based on design, technical specifications, and compliance with recognized standards.

The document does not contain information about acceptance criteria and a study proving the device meets those criteria in the context of an AI/ML driven software device.

The provided text describes the device, its intended use, a comparison to predicate devices, and lists various standards for safety, electromagnetic compatibility (EMC), and radiation protection that the device complies with. It briefly mentions "Software verification testing of the functional requirements as well as performance and safety" and "Non-clinical validation testing" but does not provide specific acceptance criteria, study methodologies, or performance metrics in a way that would be typical for an AI/ML product's clinical performance evaluation.

Therefore, the following information cannot be extracted from the provided text:

1. A table of acceptance criteria and the reported device performance: No specific acceptance criteria or performance metrics related to diagnostic accuracy (e.g., sensitivity, specificity, AUC) are provided for an AI component.
2. Sample size used for the test set and the data provenance: Not applicable, as there's no diagnostic performance study described.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method for the test set: Not applicable.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size: Not applicable.
6. If a standalone study (algorithm only without human-in-the-loop performance) was done: Not applicable for an AI/ML diagnostic function. The device itself is a standalone C-arm system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

What the document does indicate regarding testing and and the "study" context (though not for an AI/ML diagnostic component):

• "Study" Context: The "study" referenced in the document is primarily about demonstrating compliance with recognized electrical safety, EMC, radiation protection standards, and software verification/validation.
• Acceptance Criteria (Implicit for safety/performance of the C-arm system): Meeting the requirements of the standards listed (e.g., IEC60601-1, IEC60601-1-2, IEC60601-1-3, IEC60601-2-28, IEC60601-2-43) and FDA Radiation Safety Performance Standard (21CFR 1020.30, 1020.31, 1020.32). The device is found to be "as safe and effective as the predicate device" through "software verification testing" and "Non-clinical validation testing."
• Reported Device Performance (against these implicit criteria): "Results demonstrated that all executed verification tests were passed" and "all test results were satisfactory." This confirms the device met the requirements of the standards and its own specifications.
• Ground Truth (for the C-arm system): The "ground truth" for these types of tests are the specifications and requirements defined by the international standards and the manufacturer's own design specifications for the hardware and software's functional safety.

In summary, this document is for a traditional medical imaging device (C-arm X-ray system) and its substantial equivalence claims are based on engineering and safety standards, not on the diagnostic performance of an AI/ML algorithm.

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