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The GXR-Series Diagnostic X-ray System is intended for use in obtaining human anatomical images for medical diagnostic by using X-rays.

The GXR Series Diagnostic X-ray System consists of a combination of an x-ray generator, and associated equipment such as tube stand, patient table, and, digital imaging system.

Here's an analysis of the provided text regarding acceptance criteria and supporting studies for the GXR-series diagnostic x-ray system:

It's important to note that the provided document is a 510(k) Summary, which is a regulatory filing for a medical device seeking clearance from the FDA based on substantial equivalence to a predicate device. It typically focuses on demonstrating that the new device is as safe and effective as a legally marketed device, rather than proving absolute performance against specific clinical acceptance criteria in a comprehensive clinical study. Therefore, the details provided often lean towards non-clinical testing and comparison with established standards.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" for clinical performance. Instead, it relies on demonstrating adherence to recognized safety and performance standards, and comparison of technical characteristics to a predicate device. The "performance" is implicitly deemed acceptable if the device meets these standards and is substantially equivalent to the predicate.

Here's a generalized interpretation based on the document's content, focusing on what would typically be implied performance requirements for an X-ray system:

2. Sample Size Used for the Test Set and Data Provenance

• Test Set Sample Size: The document does not specify a "test set" sample size in terms of clinical images or patient cases for performance evaluation against specific acceptance criteria. The testing discussed is primarily non-clinical, related to hardware and software verification and validation.
• Data Provenance: The document implies that the testing data is generated from laboratory testing and verification during the development and modification of the device. There is no mention of clinical data or patient data being used for the performance evaluation in this 510(k) summary. Given the context of a 510(k), particularly for an X-ray system, the primary focus is on engineering and performance testing against standards, rather than large-scale clinical studies. The data is thus likely prospective in terms of being generated specifically for this submission but is non-clinical in nature.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided in the document. As the evaluation is non-clinical, there is no mention of "ground truth established by experts" in the context of diagnostic performance evaluation. The "ground truth" for non-clinical testing would typically be the expected technical output or adherence to a standard, rather than expert interpretation of images.

4. Adjudication Method for the Test Set

This information is not provided as the testing described and implied is non-clinical and does not involve expert adjudication of diagnostic findings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and effect size

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed as part of this 510(k) submission. The document focuses on demonstrating substantial equivalence through technical comparisons and compliance with standards, not on proving improved reader performance with or without AI assistance.

6. If a Standalone (algorithm only without human-in-the-loop performance) was done

This is not applicable in the sense of an AI algorithm's standalone performance. The device is a diagnostic X-ray system, which is inherently designed to be used with a human interpreter (a medical professional). While it has image processing software ("RADMAX"), this software enhances images for human diagnosis, not to provide an automated diagnosis itself.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical testing is adherence to technical specifications and international standards. For example, for radiation output, the ground truth is that the device delivers the specified kVp and mA, and for electrical safety, that it meets the requirements of IEC 60601-1. For image quality, it refers to intrinsic properties like spatial resolution, MTF, and DQE, which are measured objectively, not subjective expert consensus on diagnostic findings.

8. The Sample Size for the Training Set

This information is not applicable and therefore not provided. The device is an X-ray imaging system, not an AI/ML diagnostic algorithm that requires a training set of medical images in the conventional sense. The "training" for the device would involve calibration and configuration during manufacturing and installation to ensure it meets its technical specifications. The "RADMAX" software has image processing modules, but the document does not suggest these are deep learning models trained on vast datasets.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable for the same reasons as #8. If any parameters for the image processing modules are "learned" or optimized, the document does not elaborate on this process or the ground truth used for such optimization.

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GXR-Series Diagnostic X-Ray System, is a stationary X-ray imaging system, for the purpose of acquiring X-ray images of the desired parts of a patient's anatomy. This device is not intended for mammography or bone density applications.

GXR Series Diagnostic X-ray System is a digital radiographic system. There are 5 power output configurations which are reflected in the model's designation "GXR-XX". The models have 5 different output power ratings: 32kW, 40kW, 52kW, 68kW, 82kW. The subject device, GXR Series Diaqnostic X-ray System, is designed to diagnose the human body by providing radiographic x-ray image with anatomical structure. The subject device has the same x-ray hardware components and image management software as the predicate device. The subject device consists of a high voltage (HV) generator, a tube support unit, an X-ray beam limiting device, a patient table, wall Bucky stand, and an x-ray tube, that operates on a high-frequency inverter method. The operator control console is designed to be user-friendly, and the user can select or change x-ray parameters easily using a large graphic LCD panel display and a soft membrane switch. The GXR Series high frequency X-ray generator (manufactured by DRGEM) features accuracy, reproducibility and long-term stability with capacitor assisted general line power supply. The APR (Anatomical Programming) and the optional AEC (Automatic Exposure Control) features gives the user control of exposure factors, automatically optimized for the radiological study selected. The digital flat panel detectors provide spatial resolution, MTF, DQE and stability based on fine pixel pitch. Selection of an anatomical study on the imaging software automatically sets up the x-ray generator's pre-programmed exposure technique setting and post image processing for selected study. The subject device is able to use a total of 10 different digital detectors, (8 new plus 2 cleared in the predicate, which have been previously cleared by the 510(k) process. The GXR Series Diagnostic X-ray System consists of a combination of an x-ray generator. and associated equipment such as tube stand, patient table, and, digital imaging system. The main power cabinet contains the HT tank and control circuits, the filament drivers, the low speed starter, and interface connections to the room equipment. Tube stand and patient table allows the operator to position the patient. Full Featured Imaging Software & Digital Image Processing. Control console. The image manaqement software, RADMAX Digital Imaging Software (K182537) by DRGEM, is used in both the predicate and subject device to serve as a convenient interface to the hardware and images. Anatomical view-based digital image processing automatically optimizes and enhances the quality of the captured images. RADMAX (K182537) Digital Imaging Software is designed for acquiring images and processing the acquired images. The software can be used together with a digital X-ray detector and or an X-Ray generator. The main features of the RADMAX software are controlling and interfacing the detector, acquiring images after X-ray, storing acquired images, managing data, and image processing. It can also perform system control such as the collimation size, and filter selection.

The provided text describes a 510(k) premarket notification for the "GXR-Series Diagnostic X-Ray System." This submission aims to demonstrate substantial equivalence to a predicate device, not to evaluate the performance of an AI algorithm with specific acceptance criteria that are typically statistical (e.g., sensitivity, specificity, AUC).

Therefore, based on the provided document, I cannot fulfill your request for:

• A table of acceptance criteria and the reported device performance (related to AI algorithm statistical performance).
• Sample size used for the test set and data provenance.
• Number of experts used to establish the ground truth for the test set and their qualifications.
• Adjudication method.
• If a multi reader multi case (MRMC) comparative effectiveness study was done.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done.
• The type of ground truth used.
• The sample size for the training set.
• How the ground truth for the training set was established.

The document focuses on the device itself (an X-ray system), not an AI algorithm for image analysis. The "Performance Data" section describes nonclinical testing for general safety and effectiveness of the X-ray system as a whole, ensuring it meets standards for medical electrical equipment, radiation protection, and software lifecycle, and performs comparably to the predicate device. The only "difference" highlighted is the ability to interface with additional previously cleared digital flat panel detectors.

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The GXR-Series Diagnostic X-Ray System, (Models GXR-SD, GXR-S, SGXR-S, FDR Smart FGXR-S), is a stationary X-ray imaging system, for the purpose of acquiring X-ray images of the desired parts of a patient's anatomy. This device is not intended for mammography or bone density applications.

The GXR-Series Diagnostic X-Ray System, (Models GXR-SD, GXR-S, SGXR-S, FDR Smart FGXR-S) is comprised of 2 main configurations: GXR-SD and GXR-S, with SGXR-S, FDR Smart FGXR-S being different brand names for GXR-S. Both configurations are designed to diagnose the human body by providing radiographic x-ray image with anatomical structure.

GXR-S, SGXR-S, FDR Smart FGXR-S (analog) and GXR-SD (digital) have the same xray hardware components. However, the GXR-SD model contains image management (PACS) software and a flat panel digital detector. Interoperability is defined in the DICOM Conformance Statement which is part of the device labeling and is based upon NEMA PS 3.1 - 3.20 (2016). Digital Imaging and Communications in Medicine (DICOM) Set DICOM Standard.

The GXR-S does not have image management software and does not have a digital detector.

The GXR-SD, GXR-S, SGXR-S, FDR Smart FGXR-S, models consist of a high voltage (HV) generator, a tube support unit, an X-ray beam limiting device, patient table, wall Bucky stand, and an x-ray tube, that operates on a high-frequency inverter method.

The operator control console is designed to be simple and user-friendly, and the user can select or change x-ray parameters easily using a large graphic LCD panel display and a soft membrane switch. The GXR Series, high frequency X-ray generator features accuracy, reproducibility and long-term stability with capacitor assisted general line power supply. The APR (Anatomical Programming) and the optional AEC (Automatic Exposure Control) features gives the user control of exposure factors, automatically optimized for the radiological study selected.

RADMAX Digital Imaging Software (K182537) by DRGEM, is used in the GXR-SD model to serve as an interface to the hardware and images. Anatomical view-based digital image processing automatically optimizes and enhances the quality of the captured images.

The provided document, a 510(k) Premarket Notification summary for the GXR-Series Diagnostic X-Ray System, does not contain the detailed information typically presented in a study proving a device meets acceptance criteria for an AI/CADe (Computer-Aided Detection/Diagnosis) system.

This document describes a traditional X-ray system, not an AI software. The performance data highlighted is primarily related to non-clinical testing, electrical safety, EMC (Electromagnetic Compatibility), and conformance to various medical device standards (e.g., IEC 60601 series, ISO 14971, NEMA PS 3.1 DICOM). These are standard requirements for X-ray hardware, not for AI software performance in diagnostic tasks.

Therefore, I cannot extract the requested information regarding acceptance criteria and study details for an AI/CADe system from this document. The sections you asked for, such as sample sizes for test and training sets, expert qualifications, and MRMC studies, would be found in a submission for an AI-powered diagnostic device, which this is not.

The "Performance Data" section in the document specifically mentions "Nonclinical Testing" and lists several international standards for electrical safety and electromagnetic compatibility (EMC), as well as software lifecycle processes (IEC 62304) and risk management (ISO 14971). It concludes that "Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met." However, it does not specify what those acceptance criteria for clinical performance are, as it is a hardware device.

If you have a document describing an AI/CADe device, please provide that, and I will be able to answer your questions.

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