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Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

RadPRO® Mobile 40kW and RadPRO® Mobile 40kW FLEXPLUS, Model SM-40HF-B-D-VIR are mobile x-ray units that covers all the specific needs of any radiographic examination at the patient's bed, first aid, and emergency, orthopedics, pediatric, and operating theater. These battery or line operated units combine stand-alone for exposures with battery assisted motor drive for the greatest ease in imaging. Five different models of digital image acquisition panels are offered: Canon CXDI 401C Wireless, Canon CXDI 701C Wireless, Canon CXDI 801C Wireless. All of the Canon panels and the associated software have been cleared by FDA, (K131106 and K133693) so integration with the mobile system was straightforward. The device complies with the US Federal Safety Performance Standard and is UL listed.

This document is a 510(k) premarket notification for the RadPRO® Mobile 40kW and RadPRO® Mobile 40kW FLEXPLUS, Model SM-40HF-B-D-VIR, a mobile X-ray system. The submission aims to demonstrate substantial equivalence to legally marketed predicate devices.

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Acceptance Criteria and Device Performance

The document does not explicitly state "acceptance criteria" in the traditional sense of numerical targets for performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it focuses on demonstrating substantial equivalence to a predicate device (Sedecal Mobile Digital Diagnostic X-Ray Systems, K101517) through technical and safety comparisons, and by showing that the device is as safe and effective. The performance is assessed through compliance with relevant standards and successful integration of previously cleared components.

The table below summarizes the comparison between the new device and the predicate, highlighting the "performance" implicitly defined by these comparisons:

Study Proving Acceptance Criteria (Substantial Equivalence):

The study proving the device meets the acceptance criteria (i.e., is substantially equivalent to the predicate) is primarily a non-clinical bench and laboratory testing study, complemented by the fact that core components (digital panels) were previously FDA cleared.

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

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

• Test Set Sample Size: The document does not specify a "sample size" in terms of number of patient cases or images for testing the entire device system's imaging performance beyond general statements about "test images." However, the digital panels themselves (Canon CXDI series) were previously cleared by the FDA (K131106 and K133693), implying their performance was assessed in their respective submissions.
• Data Provenance: Not explicitly stated for specific images. The testing was conducted by SEDECAL SA in Algete, Madrid, España (Spain). The nature of the testing described (laboratory, bench, test images, clinical image comparisons) suggests some data would be internally generated or acquired during testing. Given it's a 510(k) for an X-ray system, the "data" is primarily technical specifications, compliance with standards, and image quality demonstrations rather than a large clinical dataset for a diagnostic algorithm.

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

• Number of Experts: "Sample images were verified by a Board Certified Radiologist." This indicates at least one expert.
• Qualifications: "Board Certified Radiologist." No details on years of experience.

4. Adjudication method for the test set:

• Not specified. Given only one expert is mentioned for image verification, a formal adjudication method (like 2+1 or 3+1) is unlikely to have been employed for the specific "sample images." The primary method appears to be comparison against accepted standards and the predicate device's performance.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No, an MRMC comparative effectiveness study was not done. The submission focuses on demonstrating substantial equivalence of the hardware system, not on evaluating human reader performance with or without AI assistance. The device is a mobile X-ray system, not an AI-powered diagnostic algorithm in the typical sense of needing MRMC studies to assess reader improvement.

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

• This question is not directly applicable to this device in the context of a diagnostic AI algorithm. The device itself is a standalone X-ray imaging system. The submission details its performance, safety, and effectiveness without reliance on a human-in-the-loop performance for its core function of image acquisition. The "Enhanced Work Flow" is a separate software capability for facilitating client software, not an AI algorithm for interpreting images.

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

• For the "sample images" mentioned, the ground truth was expert verification by a Board Certified Radiologist. The overall "ground truth" for the device's main function comes from compliance with established technical standards (e.g., electrical safety, radiation performance, image acquisition parameters) and the performance of the legally marketed predicate device.

8. The sample size for the training set:

• This device is a hardware X-ray system, not an AI algorithm trained on a dataset of images. Therefore, there is no "training set" in the context of machine learning.

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

• N/A, as there is no training set for an AI algorithm.

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