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The EXSYS DEXi is a diagnostic X-ray system intended for use in generating radiographic images of human anatomy for general purpose. The system obtains necessary information of patient's anatomical structure by an image processing (workstation) after process of examination using radiation exposure with DR. This system is not intended for mammography applications.

The EXSYS DEXi is a diagnostic X-ray system intended for use in generating radiographic images of human anatomy for general purpose. The system obtains necessary information of patient's anatomical structure by an image processing (workstation) after process of examination using radiation exposure with DR. This system is not intended for mammography applications.

The EXSYS DEXi composed of a x-ray generator, tube, collimator, tube stand, bucky stand, patient table, flat panel detector and console.

This FDA 510(k) summary does not contain information about acceptance criteria and device performance as it pertains to AI/ML or image analysis aspects. The document focuses on the substantial equivalence of the modified EXSYS DEXi diagnostic X-ray system to a previously cleared predicate device (K233530) based on hardware and software updates, and compliance with general safety and performance standards for X-ray systems.

Specifically, the document refers to non-clinical data and verification and validation testing demonstrating compliance with various international and FDA-recognized consensus standards (e.g., IEC 60601 series for medical electrical equipment, ISO 14971 for risk management, IEC 62304 for medical device software, UL ANSI 2900-1 and IEC 81001-5-1 for cybersecurity). It states, "The test results support that all the specifications have met the acceptance criteria. Verification and validation testing were found acceptable to support the claim of substantial equivalence." However, it does not provide a table of acceptance criteria with reported device performance metrics in an AI/ML context, nor does it describe specific studies that would typically prove such performance (e.g., standalone performance studies, MRMC studies, details on ground truth establishment for a diagnostic algorithm, sample sizes for test/training sets relevant to AI performance).

The "technological characteristics" table (Table 1) compares design parameters of the subject device (new models of EXSYS DEXi) with the predicate device, highlighting additions like new collimators, mechanical parts, detectors, and software (EConsole2). The discussion column for these additions generally states, "The system has been tested and there is 'No negative impact on safety or efficacy' and there are no new potential or increased safety risks concerning this difference." This refers to overall system safety and performance in line with a general X-ray system, not specific AI/ML diagnostic performance.

Therefore, based on the provided document, the following information cannot be extracted:

1. A table of acceptance criteria and the reported device performance (for AI-specific functions): Not provided. The document states general compliance with standards and "test results support that all the specifications have met the acceptance criteria," but does not detail these criteria or performance metrics specific to an AI component's diagnostic accuracy, sensitivity, specificity, etc.
2. Sample size used for the test set and the data provenance: Not provided for AI/ML performance evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not provided for AI/ML performance evaluation.
4. Adjudication method for the test set: Not provided for AI/ML performance evaluation.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size: Not mentioned.
6. If a standalone (algorithm only without human-in-the-loop performance) was done: Not mentioned.
7. The type of ground truth used: Not specified for AI/ML performance evaluation.
8. The sample size for the training set: Not provided for AI/ML performance evaluation.
9. How the ground truth for the training set was established: Not provided for AI/ML performance evaluation.

The document states, "Clinical studies are unnecessary to validate the safety and effectiveness of the Stationary x-ray system, EXSYS DEXi, the subject of this 510(k) notification," further indicating that specific performance data from clinical trials or detailed AI algorithm validation studies (which typically involve such criteria) are not included in this submission summary. The software updates mentioned (EConsole2) were previously cleared via K240243, suggesting that any specific performance data for that software might be found in its own 510(k) submission, but not in this document.

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Intended for use by a qualified/trained medical professionals, who have full understanding of the safety information and emergency procedures as well of capabilities and function of the device provides radiographic, multiradiographic and fluoroscopic imaging and is used for guidance and visualization during diagnostic radiographic, surgery, and interventional procedures. The device is to be used in healthcare facilities both inside and outside of hospital, in a variety of procedures of the skull, spinal column, extremities, and at the discretion of the medical professional the device may be used for other imaging applications on all patients except neonates (birth to one month) within the limits of the device. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. The system is not intended for mammography applications

The Virtual C DRF system is a mobile imaging system that acquire, process and display both static radiographic images and dynamic radiographic images such as multi-rad and fluoroscopy. Dynamic image acquisition is performed without the limitation of a mechanical linkage between the x-ray source and the x-ray detector. The mechanical linkage typical in existing dynamic imaging systems is either a c-arm or u-arm that ensures the alignment of the imaging components during image acquisition. The Virtual C DRF System features a novel collimator with built-in x-ray source to detector alignment software (Machine-Vision Collimator (MVC), combine they provide the technology for a "virtual c-arm" system. The novel MVC utilized four independent shutter to automatically position the radiation beam, so the area of exposure always remains within the confines of the active area of the detector. In addition, the angle and inclination of x-ray source is displayed to the operator. A visual display provides real time video images of the patient and a shaded area within the video images represent the location and size of the radiation beam with respect to the patient. As compared to our predicate device, there are three main changes: The digital receptor panel become a DRTECH brand panel, the generator changes from Sedecal to Source-ray, and and the collimator is changed from Colimar to a PortaVision "Machine Vision" collimator. An initial report was submitted for that collimator.

The provided document is a 510(k) Premarket Notification for the "Virtual C DRF Digital Imaging System." It focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study with an AI algorithm.

Therefore, the document does not contain the information requested regarding acceptance criteria for an AI-powered device, a study proving it meets these criteria, or details about expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance.

The document primarily discusses non-clinical testing (bench testing, electrical safety, EMC, software validation, cybersecurity) and a comparison of the new device's technical specifications and intended use against a predicate device. It explicitly states: "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification."

In summary, none of the requested information (acceptance criteria table, study details, sample sizes, expert qualifications, ground truth, MRMC study, standalone performance) for an AI-powered device is present in this medical device submission.

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