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This software is intended to generate digital radiographic images of the skull, spinal column, extremities, and other body parts in patients of all ages. Applications can be performed with the patient sitting, or lying in the prone or supine position and is intended for use in all routine radiography exams. The product is not intended for mammographic applications.

This software is not meant for mammography, fluoroscopy, or angiography.

The I-Q View is a software package to be used with FDA cleared solid-state imaging receptors. It functions as a diagnostic x-ray image acquisition platform and allows these images to be transferred to hard copy, softcopy, and archive devices via DICOM protocol. The flat panel detector is not part of this submission. In the I-Q View software, the Digital Radiography Operator Console (DROC) software allows the following functions:

• 1. Add new patients to the system; enter information about the patient and physician that will be associated with the digital radiographic images.
• 2. Edit existing patient information.
• 3. Emergency registration and edit Emergency settings.
• 4. Pick from a selection of procedures, which defines the series of images to be acquired.
• 5. Adiust technique settings before capturing the x-ray image.
• 6. Preview the image, accept or reject the image entering comments or rejection reasons to the image. Accepted images will be sent to the selected output destinations.
• 7. Save an incomplete procedure, for which the rest of the exposures will be made at a later time.
• 8. Close a procedure when all images have been captured.
• 9. Review History images, resend and reprint images.
• 10. Re-exam a completed patient.
• 11. Protect patient records from being deleted by the system.
• 12. Delete an examined Study with all images being captured.
• 13. Edit User accounts.
• 14. Check statistical information.
• 15. Image QC.
• 16. Image stitching.
• 17. Provides electronic transfer of medical image data between medical devices.

The provided document is a 510(k) summary for the I-Q View software. It focuses on demonstrating substantial equivalence to a predicate device through bench testing and comparison of technical characteristics. It explicitly states that clinical testing was not required or performed.

Therefore, I cannot provide details on clinical acceptance criteria or a study proving the device meets them, as such a study was not conducted for this submission. The document relies on bench testing and comparison to a predicate device to establish substantial equivalence.

Here's a breakdown of what can be extracted from the provided text regarding acceptance criteria and the "study" (bench testing) that supports the device:

1. Table of Acceptance Criteria and Reported Device Performance

Since no clinical acceptance criteria or performance metrics are provided, this table will reflect the general statements made about the device performing to specifications.

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

• Test Set Sample Size: Not applicable/not reported. The document describes bench testing, not a test set of patient data.
• Data Provenance: Not applicable. Bench testing generally involves internal testing environments rather than patient data from specific countries or retrospective/prospective studies.

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

• Not applicable. As no clinical test set was used, no experts were needed to establish ground truth for patient data. Bench testing typically relies on engineering specifications and verification.

4. Adjudication method for the test set

• Not applicable. No clinical test set or human interpretation was involved.

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, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical Testing: The bench testing is significant enough to demonstrate that the I-Q View software is as good as the predicate software. All features and functionality have been tested and all specifications have been met. Therefore, it is our conclusion that clinical testing is not required to show substantial equivalence." The device is software for image acquisition, not an AI-assisted diagnostic tool.

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

• Yes, in a sense. The "study" described is bench testing of the software's functionality and its integration with solid-state detectors. This is an evaluation of the algorithm/software itself.

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

• For bench testing, the "ground truth" would be the engineering specifications and expected functional behavior of the software and its interaction with hardware components. It's about verifying that the software performs according to its design requirements.

8. The sample size for the training set

• Not applicable. The I-Q View is described as an image acquisition and processing software, not an AI/machine learning model that typically requires a training set of data.

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

• Not applicable, as there is no mention of a training set or AI/machine learning component.

Summary of the "Study" (Bench Testing) for K203703:

The "study" conducted for the I-Q View software was bench testing. This involved:

• Verification and validation of the software.
• Demonstrating the intended functions and relative performance of the software.
• Integration testing to verify that compatible solid-state detectors performed within specification as intended when used with the I-Q View software.

The conclusion drawn from this bench testing was that the software performs to specification and is "as safe and as functionally effective as the predicate software." This was deemed sufficient to demonstrate substantial equivalence, and clinical testing was explicitly stated as not required.

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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 TOPAZ Mobile DR System, is a mobile 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, bone density, fluoroscopy and angiography applications.

The TOPAZ Mobile DR System, (TOPAZ), is a mobile x-ray system and is a modification of the predicate device. There are 2 models for TOPAZ: TOPAZ-32D (32KW) and TOPAZ-40D (40KW). TOPAZ, may be moved quietly and smoothly with a motor drive mechanism.

The core part of x-ray source is a tube assembly, motorized x-ray collimator, HV cable assembly and high frequency x-ray generator. A touch screen LCD based x-ray control console provides a user-friendly interface and technique selection. The Collimator supports high accuracy for selected x-ray field size over any SID. Selection of an anatomical study on the imaging software automatically sets up the x-ray generator's pre-programmed exposure technique.

The X-ray passing through a patient's body is sent to the detector and then converted into electrical signals. These signals go through the process of amplification and digital data conversion in the signal process on the workstation and saved in a DICOM file for review on the device or on a Picture Archiving & Communication System (PACS) workstation.

The provided text is a 510(k) summary for the DRGEM TOPAZ Mobile DR System. It discusses the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain any information about a study that proves the device meets specific acceptance criteria related to a human-in-the-loop or standalone AI performance study.

The "PERFORMANCE DATA" section explicitly states that "Nonclinical testing results are provided in the 510(k). 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." This refers to engineering and safety testing against recognized standards (e.g., IEC 60601-2-54, ANSI AAMI ES60601-1, IEC 62304 for software), not clinical performance studies involving AI or human readers.

The key information missing to answer your request is data from a clinical performance study (e.g., diagnostic accuracy, reader study results). The device described is a mobile X-ray imaging system, which captures images. There is no mention of any integrated AI component that would require an AI-specific performance study with acceptance criteria for diagnostic performance.

Therefore, I cannot populate the table or answer most of your questions as the necessary information is not present in the provided document.

Here's what can be inferred or stated based on the provided text, and what cannot:

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

Cannot populate. The document focuses on regulatory compliance and engineering standards for the X-ray system itself, not diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI component. The "acceptance criteria" mentioned are for non-clinical engineering and safety tests, not clinical performance.

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

Not applicable/Not mentioned for clinical performance. The "test set" referenced in the document pertains to engineering validation and verification tests of the X-ray system's functions, not a clinical data set for evaluating diagnostic performance of an AI.

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)

Not applicable/Not mentioned. Ground truth establishment by experts (e.g., radiologists) is relevant for diagnostic performance studies. This document reports on non-clinical engineering tests.

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

Not applicable/Not mentioned. Adjudication methods are used in reader studies or for ground truth establishment in clinical performance. This document does not describe such studies.

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. The document does not describe any MRMC study.

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

No. The document does not describe any standalone algorithm performance testing related to diagnostic accuracy.

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

Not applicable/Not mentioned for clinical performance. For engineering tests, the "ground truth" would be the successful operation of the device according to its specifications and regulatory standards.

8. The sample size for the training set

Not applicable/Not mentioned. This information would be relevant for an AI device. The document describes an X-ray imaging system, not an AI.

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

Not applicable/Not mentioned. This information would be relevant for an AI device. The document describes an X-ray imaging system, not an AI.

Summary of the Device and its Testing as per the document:

The TOPAZ Mobile DR System is a mobile X-ray imaging system. The 510(k) submission primarily focuses on demonstrating its substantial equivalence to an existing predicate device (K183292, also a TOPAZ Mobile DR System from DRGEM). The main difference for this new 510(k) (K201124) is the addition of five previously cleared digital X-ray detectors to the TOPAZ system.

The "Performance Data" section details that the system underwent non-clinical testing against various recognized international and national standards (e.g., IEC 60601 series for medical electrical equipment safety, radiation protection, usability; IEC 62304 for medical device software; DICOM standards, JPEG standards, etc.). The acceptance criteria for these tests were met, demonstrating the device's safety and effectiveness as an X-ray imaging system, and its performance as well as the predicate device. This refers to the engineering and regulatory compliance of the hardware and integrated software for image acquisition and handling, not the diagnostic interpretation or AI assistance.

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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 of hospital, in a variety of procedures of the skull, spinal column, chest, abdomen, extremities. The device may be used for other imaging applications on all patients except pedian 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. (RX Only)

The MobileRay Pulse SE system is a radiographic multi-rad, and fluoroscopic digital mobile X-Ray system that is designed for all pediatric and adult patients during diagnostic, surgery, and interventional procedures. The systems include (1) an x-ray source consisting of a X-Ray generator, X-Ray tube, and x-ray collimator, (2) a portable digital imaging system consisting of a wired and/or wireless flat panel digital detector, workstation software to acquire and process digital images in radiographic, multi-rad, and fluoroscopic modes, a laser SSD measuring system to accurately measure the distance between the X-ray tube focal spot and the patient, software which calculate radiation skin dose for KVp, mAs and SSD selected for the patient weight and body part being examined, a computer, mouse, keyboard, and image display monitor, or a laptop computer and (3) a mobile cart. The device does not incorporate a mechanically C-Arm or other mechanically device to ensure the x-ray source and flat panel detector are aligned. The device incorporates an electronic X-ray source and flat panel detector alignment system to comply with FDA regulation 21 CFR 1020.31 (g) (1). The system incorporates an automatic X-ray beam limited device to comply with FDA regulation 21 CFR 1020.32 (ii) (ii). There are several advance motion sensing technologies available to accurately determine if the Xray source is aligned to the flat panel detector. The device incorporates a radiation inhibit safety circuit to prevent the emission of radiation if the X-ray source is not aligned to the detector and to immediately shut down emission of radiation if for whatever reason the X-ray source is no longer aligned to the detector within the predetermine tolerance of FDA regulation 21 CFR 1020.31 (g) (1). The portable x-ray generator employed is a slightly modified version of the one cleared in K121410.

This document is a 510(k) Premarket Notification from Portavision Medical LLC for their MobileRay Pulse SE Digital Imaging System, demonstrating its substantial equivalence to a predicate device. The information provided heavily focuses on describing the device, comparing its technical specifications to a predicate, and detailing non-clinical bench testing for safety and effectiveness.

Crucially, the document explicitly states: "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification." This means that the device's acceptance criteria and the proof of meeting them are not based on human reader studies, ground truth establishment, or clinical performance metrics discussed in an MRMC or standalone study. Instead, the acceptance criteria are met through demonstrating equivalence in technical specifications and successful completion of robust non-clinical bench testing.

Therefore, the requested information about acceptance criteria and a study proving the device meets them, particularly regarding an AI component, MRMC study, ground truth, and expert adjudication, is not applicable to this specific 510(k) submission. This submission is for a conventional X-ray and fluoroscopy system, not an AI-powered diagnostic device.

However, I can extract information related to the device's performance based on the technical comparison and bench testing described. It's important to frame this within the context of technical equivalence rather than AI-driven performance metrics.

Acceptance Criteria and Device Performance (Based on Technical Equivalence and Bench Testing):

Since no clinical or AI-specific performance study was conducted or presented, the "acceptance criteria" here refer to the demonstration of technical equivalence and adherence to safety and performance standards for an X-ray imaging system. The "reported device performance" is a comparison of its technical specifications and safety/EMC test results against established predicate device characteristics and regulatory standards.

Regarding the specific questions about an AI study (which are NOT applicable to this submission):

1. Sample size for the test set and data provenance: No test set of clinical images used for performance evaluation (AI or human reader) was mentioned. The "test set" in this context would be the device itself undergoing bench testing.
2. Number of experts used to establish ground truth & qualifications: Not applicable. No clinical ground truth was established for performance evaluation.
3. Adjudication method for the test set: Not applicable. No clinical test set to adjudicate.
4. MRMC comparative effectiveness study: Not applicable. No MRMC study was done, as this is a traditional imaging device, not an AI-assisted one. The document explicitly states "No clinical data is necessary."
5. Standalone performance: Not applicable in the context of AI. The device's "standalone" performance is its technical capability to produce X-ray images, which was assessed through bench testing and comparison to predicate technical specifications.
6. Type of ground truth used: Not applicable. No clinical ground truth (expert consensus, pathology, outcomes data) was used for performance evaluation.
7. Sample size for the training set: Not applicable. This device is not an AI algorithm that requires a training set.
8. How the ground truth for the training set was established: Not applicable.

Summary of the Study:

The "study" described in this 510(k) submission is a non-clinical bench testing and technical comparison study.

• Objective: To demonstrate the substantial equivalence of the MobileRay Pulse SE Digital Imaging System to a legally marketed predicate device (EcoTron AnyView 500R Fluoroscopic Mobile X-ray System, K160279) and compliance with relevant safety and performance standards.
• Methodology:
  • Technical Comparison: Direct comparison of features, specifications (e.g., KV/mA ranges, generator type, software functions), and indications for use between the proposed device and the predicate.
  • Bench Testing: Electrical safety and Electromagnetic Compatibility (EMC) testing according to international standards (e.g., EN 60601-1-2, IEC 60601-1). Thermal stability testing for the X-ray generator to ensure safe operation during fluoroscopy. Validation of software according to FDA guidance. Cybersecurity assessment.
• Data Provenance: The data primarily comes from internal company testing and accredited lab testing for standard compliance. This is "prospective" bench testing data rather than retrospective or prospective clinical data. The country of origin for the data generation would be where the manufacturer and testing labs are located (not specified, but implied to be within typical regulatory testing frameworks).
• Conclusion: The submission concludes that the MobileRay Pulse SE is as safe and effective as the predicate device due to similar indications for use, similar technological characteristics, and successful non-clinical bench testing demonstrating compliance with safety and performance standards. The key difference is the use of digital panels versus an image intensifier, and a unique source-to-image receptor alignment technology, but these are deemed "insignificant technological differences" that do not raise new questions of safety or effectiveness.

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The PowerDR™ Digital X-ray Imaging System is indicated for use as an X-ray imaging modality to acquire, process, display, quality assure and store digital medical X-ray images.

The PowerDR™ Digital X-ray Imaging System is indicated for use in general radiographic and fluoroscopic examinations of any anatomy for adult, pediatric, and neonatal patients. It is not indicated for use in mammography.

The PowerDR™ Console Application is a digital medical X-ray imaging system consisting of an X-Ray detector, computer hardware and the PowerDR™ software. The User supplies the X-Ray generator. The PowerDR™ Console Application is intended to enable a procedure of medical image acquisition, processing, display, quality assurance, and storage. The software interfaces to an X-Ray detector from variety of vendors to acquire raw pixel data. Its image-processing algorithms transform raw pixel data into diagnostic quality images and image sequences to aid the medical professional in diagnosis. For temporary storage, image data can be stored on the local computer. For long term storage, image data can be stored on a portable media device or a remote PACS (Picture Archive and Communication System) server. The PowerDR™ Digital X-ray Imaging System is intended for use in general radiographic and fluoroscopic examinations of any anatomy for adult, pediatric, and neonatal patients. It is not intended for use in mammography. The system can be sold with or without a computer, and with or without a compatible, previously cleared, digital receptor panel.

The provided text is a 510(k) Premarket Notification for the PowerDR™ Digital X-ray Imaging System. This type of submission focuses on demonstrating substantial equivalence to a previously legally marketed device (predicate device), rather than proving the device meets specific performance acceptance criteria through the kind of studies typically seen for novel AI/ML devices.

Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving the device meets those criteria for AI/ML performance.

Specifically:

• No table of acceptance criteria and reported device performance is provided because this is a substantial equivalence submission, not a performance validation against defined metrics for an AI/ML component. The "performance" demonstrated is that the new device operates similarly to the predicate device in terms of image acquisition, processing, display, quality assurance, and storage.
• No sample size for a test set or data provenance is mentioned in the context of an AI/ML performance study. The "test set" here refers to the validation of the system's ability to acquire and process images, not to a diagnostic performance evaluation of an AI algorithm. The document states "image inspection, bench, and test laboratory results" were used, and "Each available digital receptor panel has undergone a rigorous verification and validation procedure."
• No number of experts or qualifications of experts used for ground truth establishment for a test set. This is not an AI/ML diagnostic study.
• No adjudication method is mentioned, as there is no diagnostic ground truth establishment process described for an AI/ML algorithm.
• No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done because there is no AI assistance component to evaluate.
• No standalone (algorithm only) performance study was done; the focus is on the integrated system's functionality.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.) is not applicable in the context of an AI/ML performance study. The "ground truth" for this device relates to the technical specifications and image quality relative to the predicate device.
• No sample size for the training set is applicable; this is not an AI/ML algorithm that undergoes a training phase as typically understood.
• How the ground truth for the training set was established is not applicable for the same reason.

The core argument for the PowerDR™ system is that it is substantially equivalent to the predicate device (Nexus DRF Digital X-ray Imaging System, K130318) in terms of its intended use, technology, and safety and effectiveness. The evidence provided to support this is:

• Bench testing: "The results of image inspection, bench, and test laboratory results indicates that the new device is as safe and effective as the predicate devices."
• Use of previously cleared components: All compatible digital panels supported by PowerDR™ "have previously received FDA 510(k) clearances" and "undergone a rigorous verification and validation procedure."
• Compliance with FDA guidance documents: Specifically, guidance for software in medical devices, cybersecurity, and pediatric imaging information.
• Comparison chart: A detailed "Substantial Equivalence Chart" (Section 5) outlining similarities in identification, intended use, description, where used, image processing, image storage, image data source, configuration, primary digital panel support (multiple for proposed vs. one for predicate, with all proposed panels being previously cleared), system software, image data format, image presentation, application software, tracking X-ray dose, fluoro image processing, MultiRad image support, dose and processing auto optimization, quality assurance, DICOM 3.0 conformance, IHE Integration profile, power source, and computer platform.

Conclusion stated in the document: "After analyzing bench testing and risk analysis and compliance to the DICOM standard, it is the conclusion of Radiology Information Systems, Inc. that the PowerDR™ Digital X-ray Imaging System is as safe and effective as the predicate device, have few technological differences, and has the same indications for use, thus rendering it substantially equivalent to the predicate device."

In summary, this 510(k) submission does not describe an AI/ML device or a study validating AI/ML performance using acceptance criteria. Instead, it demonstrates substantial equivalence to a predicate device through bench testing and comparison of technical specifications.

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The MasteRad MX30 is 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.

This device represents a new combination of already cleared solid state digital x-ray acquisition panels (plus one NEW panel) and software with the diagnostic x-ray compnents required to make a complete system. The purchaser may select their digital panel from this list: Varex PaxScan 2530Wv4, Varex PaxScan 4336Wv4, Varex PaxScan 4343R, Varex PaxScan 4343RC, Varex XRpad 4343F, Varex XRpad 3025, Varex XRpad 4336, Toshiba* FDXA4343R. As compared to our predicate system, the tube stand is floor mounted instead of ceiling mounted. The collimator is different. Instead of the Ralco collimator, a Collimare model is supplied. The purchaser selects one of the following FDA certified models: CML-150-0001-C; CTL-150-0001-C; CML-125-0001-C. The x-ray tube and the high voltage generator remains the same as our predicate. The x-ray tube is a Toshiba model and the generator is the CPI CMP 200DR. The image acquisition software is a newer version of our Voyance software originally cleared in K130377.

The MasteRad MX30 is an X-ray system, and the provided text describes its substantial equivalence to a predicate device (K143257). The acceptance criteria and supporting studies are based on demonstrating that the new device, particularly a new digital X-ray receptor panel, maintains diagnostic quality and safety.

Here's a breakdown of the requested information:

1. Table of acceptance criteria and the reported device performance

The acceptance criteria are implicitly tied to demonstrating that the new Toshiba FDXA4343R digital panel (and the overall MasteRad MX30 system) performs at least as well as, or equivalently to, the predicate device and the previously cleared Toshiba FDX4343R panel. The primary performance criterion is diagnostic quality of images.

2. Sample sized used for the test set and the data provenance

• Sample Size: The document does not specify a numerical sample size for the clinical images beyond stating "Clinical images were acquired from the new Toshiba panel." It implies a sufficient number were obtained for review, but no specific count is given.
• Data Provenance: The document does not explicitly state the country of origin. It indicates the images were "acquired from the new Toshiba panel" for the purpose of this submission, which suggests a prospective acquisition for evaluation, specifically for a new panel not previously cleared by the FDA.

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

• Number of Experts: One expert.
• Qualifications: "A board certified radiologist." No specific years of experience are mentioned.

4. Adjudication method for the test set

• Adjudication Method: Not applicable/None explicitly stated as an adjudication method. The evaluation was performed by a single board-certified radiologist who "reviewed" the images and "found them to be of excellent diagnostic quality." There is no mention of multiple reviewers or a consensus process.

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

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed.
• AI Improvement Effect Size: Not applicable. This submission is for an X-ray system and its digital detector, not an AI-powered diagnostic tool for interpretation.

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

• Standalone Performance: Not applicable. This device is an X-ray acquisition system, not a standalone algorithm. The "performance" described relates to the imaging capabilities of the hardware component (the digital detector) rather than an interpretive algorithm.

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

• Ground Truth Type: Expert opinion/evaluation. The ground truth for image quality was established by a single board-certified radiologist's assessment of "diagnostic quality." This is based on the expert's interpretation of whether the images are suitable for clinical diagnosis.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. The document describes the validation of a hardware system and its updated software, not a machine learning model that requires a training set.

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

• Training Set Ground Truth Establishment: Not applicable, as there was no training set for a machine learning model.

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These Portable Diagnostic Radiographic Systems are 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, chest, abdomen, 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).

The AMADEO M-DR mini Portable X-Ray is a fully digital X-ray system for use for first aid services, intensive care units, emergency departments, as well as ships and mobile hospitals (e.g. container solutions) in inaccessible areas, in laboratories and scientific stations in remote parts of the world. The AMADEO M-DR mini is used for wireless digital X-ray imaging. The device represents the straightforward combination of 510(k) exempt devices (x-ray generator, code IZO and collimator, code IZX) and already cleared digital panels and imaging software. Two different models of digital image acquisition panels are offered: PerkinElmer XRpad2 4336 or CareView 1500CW. Both of the panels and the associated software have been previously cleared by FDA (K161966 or K150929). Integration with the portable system was straightforward.

The provided text is a 510(k) summary for the AMADEO M-DR mini and AMADEO M-AX mini mobile X-ray systems. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific device performance or clinical studies.

Therefore, many of the requested details about acceptance criteria, performance studies, sample sizes, expert qualifications, and ground truth establishment are not present in this document.

Here's a breakdown of what can be extracted and what is missing:

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

The document doesn't provide a table of formal acceptance criteria with numerical performance targets for the device. Instead, it asserts equivalence to the predicate device based on meeting recognized standards and similar characteristics.

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

• Sample Size: Not specified. The document mentions "test images" were obtained, but no specific number of images or patients is provided.
• Data Provenance: Not specified. As clinical testing was not required, there is no mention of country of origin or whether data was retrospective or prospective.

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

This information is not provided. Since the submission states clinical testing was "Not required because the proposed digital panels have prior FDA clearance," it implies that new ground truth establishment by experts for image interpretation was not part of this specific submission.

4. Adjudication method for the test set:

Not applicable, as no formal clinical test set or adjudication by experts is described.

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:

Not applicable. This submission is for a mobile X-ray system, not an AI-powered diagnostic device, and therefore, an MRMC study comparing human readers with and without AI assistance was not performed or mentioned.

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

Not applicable. This device is an imaging system, not a standalone algorithm.

7. The type of ground truth used:

The concept of "ground truth" in the context of diagnostic accuracy from expert consensus or pathology is not directly applicable to this submission. The "ground truth" for this device's performance relies on its ability to produce diagnostic radiographic exposures that are comparable to those of the predicate device and meet established safety and performance standards. This is evaluated through:

• Compliance with DHHS Radiation Safety Performance Standard.
• Compliance with electrical safety and EMC standards (IEC-60601 series).
• Test images demonstrating total system functionality.

8. The sample size for the training set:

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable.

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The Discovery XR656 HD is intended to generate digital radiographic images of the skull, spinal column, chest, abdomen, extremities, and other body parts in patients of all ages. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position and the system is intended for use in all routine radiography exams. Optional image pasting function enables the operator to stitch sequentially acquired radiographs into a single image.
The device is not intended for mammographic applications.

The Discovery XR656 HD Radiography X-ray System is designed as a modular system with components that include an Overhead Tube Suspension with tube/collimator, wallstand, Table, X-ray generator, and wireless digital detectors. The System generates diagnostic radiographic images which can be sent through a DICOM network for applications including printing, viewing, and storage. The components may be combined in different configurations to meet specific customer needs. In addition, upgrade configurations are available for predicate devices. The optional image pasting function enables the operator to stitch sequentially acquired radiographs into a single image.

The provided text describes a 510(k) premarket notification for the GE HUALUN MEDICAL SYSTEMS CO. Ltd. Discovery XR656 HD (K172869), a digital radiographic X-ray system. The document focuses on demonstrating substantial equivalence to a predicate device (Optima XR646, K143270) rather than presenting a performance study with detailed acceptance criteria and clinical efficacy results for the entire system.

The core of the submission revolves around the change in detector technology from Ultra Wideband (UWB) to WiFi (802.11) for image transfer, utilizing cleared detectors (PerkinElmer XRpad2 3025 HWC-M Flat Panel Detector, K161942, and PerkinElmer XRpad2 4336 HWC-M Flat Panel Detector, K161966).

Here's an breakdown of the information requested, based on the provided text:

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

The document does not explicitly state quantitative acceptance criteria or specific performance metrics (e.g., sensitivity, specificity, accuracy) for the Discovery XR656 HD as a standalone diagnostic tool. Instead, it relies on demonstrating compliance with recognized standards and successful design verification and validation testing to ensure that the modifications (primarily the change to WiFi-enabled detectors) do not negatively impact the device's safety and effectiveness compared to the predicate.

The "Summary of Non-Clinical Tests" section mentions compliance with several voluntary standards. While these standards implicitly contain performance requirements, the specific numerical acceptance criteria for those requirements and the actual measured performance of the Discovery XR656 HD are not detailed in this summary.

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

The document states, "The subject of this premarket submission, Discovery XR656 HD, did not require clinical studies to support substantial equivalence for the incorporation WiFi (802.11) enabled detectors due to these detectors having their own 510(k) clearance."

Therefore, for the Discovery XR656 HD itself, there was no specific clinical "test set" and corresponding sample size for demonstrating diagnostic performance beyond its cleared components. The evaluation focused on non-clinical design verification and validation. The "testing/documentation" mentioned was "according to... FDA guidance documents" (for software and cybersecurity), and these were "bench" tests.

The cleared detectors (PerkinElmer XRpad2 3025 HWC-M and 4336 HWC-M) would have had their own clinical data for their respective 510(k) clearances (K161942 and K161966), but that data is not provided here for the Discovery XR656 HD system.

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)

Since no clinical studies were performed for the Discovery XR656 HD's diagnostic performance, there was no test set requiring expert-established ground truth in the context of diagnostic accuracy. The ground truth for the training of the system's image processing (if applicable, which falls under "image processing algorithms to accommodate multiple image matrix sizes") is not detailed here.

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

Not applicable as no clinical test set for diagnostic performance was conducted for this submission.

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

Not applicable. This device is a digital radiographic X-ray system, not an AI-assisted diagnostic tool in the sense of providing automated readings or decision support. The "image processing algorithms" mentioned are for accommodating different image matrix sizes and are not described as AI for diagnostic assistance. There is no mention of an MRMC study or AI assistance.

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

Not applicable. This is a medical imaging system, not a standalone algorithm. The "image processing algorithms" are integrated into the system, and their performance is evaluated as part of the overall system's technical validity, not as a standalone diagnostic algorithm.

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

As no clinical study for diagnostic performance was required or conducted for this 510(k) submission, the concept of "ground truth" (in the diagnostic sense) for this specific submission is not present. The "ground truth" for the system's functionality was established through design verification and validation testing against engineering specifications and industry standards.

8. The sample size for the training set

The document does not specify a training set sample size. While "image processing algorithms" are mentioned, implying potential machine learning components, no details on their training are provided. The focus of the submission is on hardware and communication changes, and the safety and effectiveness of the system with these changes.

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

Not applicable. No information is provided about a training set or its ground truth establishment.

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The Optima XR240amx is intended to take exposures utilizing film, computed radiography (CR), or wireless detectors, which are intended to replace radiographic film screen systems in all general purpose diagnostic procedures, for digital radiography (DR).

Optima XR240amx is a seff-contained; battery operated mobile radiographic imaging system designed to generate diagnostic radiographic images (medical x-rays) that may increase the ability to detect disease or injury early enough for a medical problem to be managed, treated, or cured. Medical x-rays are used in many types of examinations and procedures, some examples include: x-ray radiography (to find orthopedic damage, tumors, pneumonias, foreign objects).

The Optima XR240amx is indicated for use on adult and pediatric patients for general-purpose diagnostic radiographic examinations and procedures. Its mobility enables general-purpose radiographic procedures throughout the clinical environment, or as needed within the emergency, intensive care, premature birth ward, cardiac and operating departments, for patients that may not be able to be moved or in cases where it is unsafe or impractical to move them to a traditional RAD room.

The system is indicated for taking radiographic exposures of the skull, spinal column, extremities, and other body parts with the patient sitting, standing, or lying in the prone or supine position.

This device is not intended for mammographic applications.

The Optima XR240amx is intended to take exposures, using a wired or remote exposure switch, utilizing film, computed radiography (CR), or cleared wireless radiographic detectors, which are intended to replace radiographic film screen systems in all general purpose diagnostic procedures, for digital radiography (DR).

Optima XR240amx is a self-contained; battery operated mobile radiographic imaging system designed to generate diagnostic radiographic images (medical x-rays) that may increase the ability to detect disease or injury early enough for a medical problem to be managed, treated, or cured. Medical x-rays are used in many types of examinations and procedures, some examples include: x-ray radiography (to find orthopedic damage, tumors, pneumonias, foreign objects).

The Optima XR240amx system is indicated for use on adult and pediatric patients for general-purpose diagnostic radiographic examinations and procedures. Its mobility enables general-purpose radiographic procedures throughout the clinical environment, or as needed within the emergency, intensive care, premature birth ward, cardiac and operating departments, for patients that may not be able to be moved or in cases where it is unsafe or impractical to move them to a traditional RAD room.

The incorporation of cleared flat panel detectors provides increased functionality to enable images of patients of all sizes, and can produce comparable quality images with as little as half the dose of traditional computer radiography (CR), cassettes and other flat panel detectors with lower DQE.

The systems are indicated for taking radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts with the patient sitting, standing, or lying in the prone or supine position.

These devices are not intended for mammographic applications.

The provided text describes the GE Healthcare Optima XR240amx mobile x-ray system and its substantial equivalence to predicate devices. It focuses on the changes introduced by incorporating cleared wireless detectors with WiFi communication.

Here's an analysis of the acceptance criteria and study information provided:

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

The document does not explicitly present a table of acceptance criteria with specific numerical performance metrics (e.g., sensitivity, specificity, accuracy) for a diagnostic task for the Optima XR240amx itself, as the device is an imaging system rather than a diagnostic algorithm.

Instead, the acceptance criteria are implicitly related to demonstrating that the modifications (incorporation of WiFi-enabled detectors) do not negatively impact the safety and effectiveness of the device and that its performance is substantially equivalent to the predicate devices. The reported "performance" focuses on compliance with standards and successful verification and validation of changes.

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

The document states: "The subject of this premarket submission, Optima XR240amx, did not require clinical studies to support substantial equivalence for the incorporation WiFi (802.11) enabled detectors due to these detectors having their own 510(k) clearance."

Therefore, there isn't a "test set" in the traditional sense of a clinical trial with patient data. The testing mentioned in the document is primarily design verification and validation testing on the bench, not clinical data evaluation. The "data" provenance for these tests would be internal engineering tests.

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

Not applicable. As noted above, there was no clinical study with a patient test set requiring expert interpretation for ground truth establishment.

4. Adjudication method for the test set

Not applicable. No clinical test set.

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

Not applicable. This device is a mobile x-ray system, not an AI or CAD (Computer-Aided Detection) device that assists human readers. Therefore, an MRMC study and analysis of AI assistance effect size are not relevant to this submission.

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

Not applicable. This is not an algorithm-only device. It is a hardware system for acquiring x-ray images.

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

Not applicable for clinical ground truth. The "ground truth" for the verification and validation tests would be defined by engineering specifications and expected system behavior, tested against established standards and successful operation.

8. The sample size for the training set

Not applicable. As this device is a hardware imaging system, there is no "training set" in the context of machine learning algorithms.

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

Not applicable. No training set for a machine learning algorithm.

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The study proving the Optima XR240amx meets acceptance criteria primarily consisted of non-clinical design verification and validation testing.

• Rationale for non-clinical studies: The submission argued that clinical studies were not required because the changes were limited to wireless communication hardware and associated software to accommodate already cleared detectors (PerkinElmer, Inc. XRpad2 3025 HWC-M and XRpad2 4336 HWC-M Flat Panel Detectors, cleared under K161942 and K161966 respectively). The core imaging technology and intended use remained the same as the predicate devices (Optima XR200amx and Optima XR220amx, K142383).
• Verification and Validation Activities: GE Healthcare performed the following quality assurance measures:
  • Risk Analysis (new risks from wireless image transfer were identified, mitigated with design controls and labeling, and verified/validated).
  • Requirements Reviews
  • Design Reviews
  • Testing on unit level (Module verification)
  • Integration testing (System verification)
  • Performance testing (Verification)
  • Safety testing (Verification)
  • Simulated use testing (Validation)
• Conclusion: The results of these design verification and validation tests were deemed "acceptable," leading GE Healthcare to conclude that the Optima XR240amx is as safe, effective, and substantially equivalent in performance to the predicate devices. The device's update "does not result in any new potential safety risks, it has the same technological characteristics, and perform as well as the devices currently on the market."

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