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The purpose of AcuityUDR is to acquire, store, communicate, display and process medical X-ray images. These radiographic systems are intended for use by a qualified/trained physician or both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography, interventional, or fluoroscopy use.

RadmediX AcuityUDR combines components into a complete stationary x-ray system, including tube stand, tube head, collimator, generator, a digital radiography panel, and image acquisition software. 21CFR §892.1680 Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment supports, comports, component parts, and accessories.

The provided text is a 510(k) summary for the RadmediX AcuityUDR, which is a stationary X-ray system. The document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving performance against specific acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, sample sizes for test and training sets, ground truth establishment, expert qualifications, and MRMC studies is not available in the provided text.

Here's what can be extracted based on the information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria for image quality or clinical performance. Instead, it refers to compliance with recognized standards and successful non-clinical testing.

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

• Sample Size for Test Set: Not explicitly stated. The non-clinical testing involved acquiring DICOM images "from all major body structures." This implies a set of images, but a specific number is not provided.
• Data Provenance: Not explicitly stated. It describes "field tested a complete system" with images acquired from various body structures. This suggests either phantom studies or possibly human subject studies, but the nature (retrospective/prospective, country of origin) is not detailed.

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

This information is not available in the provided text. The document states that the acquired images were "clinically acceptable," but it does not specify who made this determination, how many experts were involved, or their qualifications.

4. Adjudication method for the test set:

This information is not available.

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:

A multi-reader multi-case (MRMC) comparative effectiveness study was not done as this device is a stationary X-ray system, not an AI-powered diagnostic tool. The document states, "Clinical testing: Not required for a determination of substantial equivalence."

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

This is not applicable as the device is a hardware X-ray system with accompanying image acquisition software, not a standalone AI algorithm for interpretation. The software "communicates with the digital x-ray detector and allows acquisition and processing of x-ray images."

7. The type of ground truth used:

The text states that the non-clinical testing involved acquiring images that were "of high quality and contrast and clinically acceptable." This implies expert consensus or visual assessment of image quality was used as a form of ground truth, but the specifics of how this was established are not detailed. There is no mention of pathology or outcomes data being used for this device's non-clinical testing.

8. The sample size for the training set:

The concept of a "training set" is not applicable as the device is a hardware X-ray system with image acquisition software, not a machine learning or AI-based diagnostic algorithm that requires a training set. The software is "previously cleared" and "used unmodified."

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

This is not applicable for the same reason as above.

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Venul 717X is indicated for digital imaging solutions designed to provide general radiographic diagnosis for human anatomy including both adult and pediatric patients. It is intended to replace film/screen systems in general-purpose diagnostic procedures.

Venu1717X is a cassette-size tethered X-ray flat panel detector based on amorphous silicon thin-film transistor technology. It is designed to provide the high quality radiographic image which contains an active matrix of 3070×3070 with 139um pixel pitch. The scintillator of Venu1717X is CsI(Caesium Iodide). The technology of CsI direct growth reduces the exposure dose and improves the image quality. Since Venu1717X supports multiple trigger modes, it can satisfy both of the general DR system and retrofit DR system.

iRay SDK(include iDetector) is intend to supply API interface for DR system manufacturers.DR system manufacturer control the detector by SDK interface. SDK is not intended to be used directly by other users beside DR system manufacturers. The iRay SDK is unchanged from the predicate device.

The information provided indicates that the iRay Technology Taicang Ltd. Flat Panel Detector (Venu1717X) is a digital imaging solution for general radiographic diagnosis. While the provided text describes the device's technical specifications and non-clinical studies to establish substantial equivalence to a predicate device (Mars1717V-VSI, K201043), it does not contain details about specific acceptance criteria for diagnostic accuracy metrics (like sensitivity or specificity) for a clinical study.

Instead, the provided text focuses on demonstrating substantial equivalence primarily through technical performance characteristics and a "concurrence study" of clinical images.

Here's an attempt to answer your request based only on the provided text, highlighting what is available and what is missing:

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

The document does not explicitly state "acceptance criteria" in terms of diagnostic performance metrics for a clinical study (e.g., sensitivity, specificity, or AUC with target thresholds). It focuses on demonstrating equivalence through technical performance.

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

• Sample Size for Test Set: 30 clinical images.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). The document only states "Clinical images were provided".

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)

The document mentions a "concurrence study" but does not specify the number of experts, their qualifications, or how ground truth was established for the 30 clinical images. The statement "There was no significant difference between the images" implies a qualitative comparison by human readers, but details are missing.

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

The document does not specify any adjudication method for the "concurrence study" of the 30 clinical images.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described. The study mentioned is a "concurrence study of 30 clinical images" comparing the proposed device to a predicate device, which is different from an MRMC study designed to assess reader improvement with AI assistance. The device itself is a Flat Panel Detector, which is hardware for image acquisition, not inherently an AI-driven diagnostic assistance tool.

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

This section is not applicable as the device is a Flat Panel Detector, a hardware component for imaging, not an AI algorithm performing diagnostic tasks in a standalone manner. The software mentioned (iRay SDK, iDetector) are for controlling the detector and integration, not for standalone diagnostic interpretation.

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

For the "concurrence study" of 30 clinical images, the type of "ground truth" and how it was established is not detailed. The study aimed to show "no significant difference" between images of the proposed and predicate device, rather than assessing diagnostic accuracy against an independent ground truth.

8. The sample size for the training set

This information is not applicable as the description refers to a medical imaging device (Flat Panel Detector) and its associated control software, not an AI model that would typically have a "training set" in the context of machine learning.

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

This information is not applicable for the same reasons as #8.

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Intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. The kit allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

PRIMO S is an image acquisition and processing software application, in radiography mode for Flat Panel detectors. The software is specifically designed for integration with production equipment of the SEDECAL group. The PRIMO S application will be used on different types of Sedecal equipment / systems:

• mobile units
• fixed installations.

The PRIMO S VP application provides the following functions:

• User login: the device is usable only by authenticated users
• Management of the operator interface GUIs and setup of the application itself
• The operator interface GUI must reserve a space on the monitor for the Sedecal equipment/system GUI (choice of examination (APR), X-ray generator commands, collimator, stand, etc.)
• Management of patient data through manual entry and reception from the DICOM WORKLIST service
• Management of image processing algorithms for each type of examination
• Management of the automatic advancement procedures of the operations during the study.
• Image acquisition and processing
• Saving in Hard Disk of the acquired images
• Automatic and manual image stitching procedure
• Off-line image editing and optimization using process and graphic functions
• Documentation of images and study data using DICOM services of STORE, PRINT, CDROM, MPPS, RDSR, STORAGE COMMITMENT
• Application configuration setup
• Export and automatic saving of images on external support (USB key)

The application communicates with the Sedecal equipment through software modules (DLL) for:

• The choice of the examination, made by the operator through a GUI defined by Sedecal (APR)
• Send the exposure parameters foreseen by the selected exam (kV, mA, mAs, ms, collimator aperture, stand position, ...)
• Receive the system status parameters and the exposure result

While the provided text describes the PRIMO S device and its 510(k) submission, it explicitly states:

"6. Clinical testing. Not required for a determination of substantial equivalence."

This indicates that a clinical study with detailed acceptance criteria and performance metrics, as requested in your prompt, was not performed or required for the FDA clearance of this specific device. The clearance was based on substantial equivalence to a predicate device, supported by non-clinical testing and adherence to various standards.

Therefore, I cannot provide the specific information you requested regarding validation studies, sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, or ground truth establishment for a clinical test set, as such a study was not conducted or reported in this document.

The document primarily focuses on:

• Device Description: What PRIMO S is and what it does.
• Indications for Use: The medical conditions and body parts it's intended for.
• Technological Characteristics Comparison: How it compares to its predicate device (Sedecal SA K130883) in terms of X-ray generator, digital detectors, panel sizes, operating system, etc.
• Non-Clinical Testing: A list of standards (IEC 62304, EN/IEC 62366-1, ISO 14971, NEMA DICOM, ISO 15223-1) that were employed in development, and mention of software validation based on FDA guidance and cybersecurity considerations.

Since there's no clinical trial data, I cannot populate the table or answer the specific questions about the study design that would prove the device meets acceptance criteria based on clinical performance.

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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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Mars1717X wireless digital flat panel detector is indicated for digital imaging solutions designed to provide general radiographic diagnosis for human anatomy including both adult and pediatric patients. It is intended to replace film/screen systems in all general-purpose diagnostic procedures. The device is not intended for mammography or dental applications.

Mars1717X Wireless Digital Flat Panel Detectors (Hereinafter referred to as Mars1717X) is a kind of wireless digital flat panel detector. It supports the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 42.67cm×42.67cm.

The sensor plate of Mars1717X is direct-deposited with CsI scintillator to achieve the conversion from X-ray to visible photon. The visible photons are transformed to electron signals by diode capacitor array within TFT panel, which are composed and processed by connecting to scanning and readout electronics, consequently to form a panel image by transmitting to PC through the user interface.

The major function of the Mars1717X is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. Both kinds of detectors are the key component of DR system, enable to complete the digitalization of the medical X-ray imaging with the DR system software.

iRay SDK(include iDetector) is intended to supply API interface for DR system manufacturers. DR system manufacturer control the detector by SDK interface. SDK is not intend to be used directly by other users beside DR system manufacturers.

The provided document is a 510(k) Summary for the Mars1717X Wireless Digital Flat Panel Detector by iRay Technology Taicang Ltd. This document primarily focuses on demonstrating substantial equivalence to a predicate device (Mars1717V-VSI, K201043) rather than detailing a specific study to prove the device meets acceptance criteria regarding clinical performance.

The document states that clinical consideration may not be necessary for changes in image receptor dimensions if non-clinical information is sufficient to support substantial equivalence. This implies that a dedicated clinical study to evaluate the device against specific performance acceptance criteria for diagnostic accuracy (e.g., sensitivity, specificity for detecting conditions) was likely not performed or considered necessary by the FDA for this 510(k) clearance due to the nature of the device as an X-ray detector and the comparison to a predicate.

Therefore, many of the requested details about a study proving device performance against acceptance criteria for diagnostic capability cannot be extracted from this document, as such a study does not appear to be the basis for this 510(k) clearance. The "acceptance criteria and reported device performance" primarily relate to technical specifications and equivalence.

However, I can extract information regarding technical performance metrics and how they compare between the proposed device and the predicate. These comparisons serve as the "evidence" for substantial equivalence.

Here's the breakdown based on the provided text, focusing on the technical and non-clinical aspects:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present "acceptance criteria" in the format of a clinical performance study. Instead, it compares the technical specifications and performance characteristics of the proposed device (Mars1717X) to its predicate (Mars1717V-VSI). The "acceptance criteria" can be inferred as being at least equivalent to or better than the predicate device for relevant technical specifications to demonstrate substantial equivalence.

Regarding a "study that proves the device meets the acceptance criteria":

For this 510(k) submission, the "study" is a comparative technical performance assessment against a legally marketed predicate device (K201043). The conclusion of substantial equivalence means the device meets the regulatory "acceptance criteria" for market clearance based on this comparison. The non-clinical studies performed were used to demonstrate that changes in panel size, structure, IP grade, and surface pressure do not raise new questions of safety or effectiveness and that the performance is substantially equivalent to or better than the predicate.

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

• Sample Size: Not applicable in the context of a clinical test set for diagnostic accuracy, as no such clinical study appears to have been conducted for this 510(k). The "test set" would be the device itself undergoing various engineering and performance tests (e.g., DQE measurements, spatial resolution charts, durability tests). The document does not specify the number of units tested.
• Data Provenance: The technical performance data (DQE, spatial resolution, etc.) would be generated from laboratory tests conducted by the manufacturer, iRay Technology Taicang Ltd., in China.

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 with human diagnostic ground truth was used for this 510(k) clearance based on the provided document.

4. Adjudication Method for the Test Set:

• Not applicable, as no clinical test set requiring expert adjudication was used.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, a MRMC comparative effectiveness study was not performed according to this document. The submission focuses on technical equivalence to a predicate X-ray detector, not on the diagnostic effectiveness of human readers using the device with and without AI assistance.

6. Standalone Performance (Algorithm Only Without Human-in-the-Loop Performance):

• Yes, the evaluation is inherently a standalone performance assessment of the device itself (the flat panel detector) in terms of its image acquisition capabilities (spatial resolution, DQE, etc.). There is no AI algorithm being evaluated for diagnostic assistance in this context. The device's performance is measured objectively based on physical and technical specifications, independent of human interpretation.

7. Type of Ground Truth Used:

• For the technical performance aspects, "ground truth" refers to objective physical measurements and standards. For example:
  • Spatial resolution is measured using phantoms or line pair gauges with known patterns.
  • DQE is measured according to standardized protocols (e.g., IEC 62220-1) using known X-ray spectra and dose levels.
  • Durability (surface pressure, IP rating) is tested against engineering specifications and industry standards.
  • Safety (electrical, biological) is assessed against international standards (e.g., IEC 60601-1, ISO 10993-1).

8. Sample Size for the Training Set:

• Not applicable, as this is not an AI/machine learning device requiring a training set in the conventional sense. The "training" in manufacturing would refer to quality control and calibration processes during production.

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

• Not applicable, as there is no training set in the context of an AI algorithm.

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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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DIAMOND-5A/6A/8A, is a stationary digital diagnostic x-ray system that is indicated for use in generating radiographic images of human anatomy. This device is not intended for mammography, bone density, fluoroscopy and angiography applications.

DIAMOND-5A/6A/8A, system is a digital radiographic system. There are 3 power output configurations which are reflected in the model designation "5A/6A/8A". The models have 3 different output power ratings: 52kW, 68kW, 82kW. DIAMOND 5A/6A/8A, incorporates digital flat panel detector technology, along with an automatic motorized U-arm radiographic stand and mobile patient table that can fit into smaller rooms without the need of ceiling support structures for X-Ray tube suspensions. The subject device comes in 2 hardware configurations; a Radiographic Stand configuration for a wired detector and a Radiographic Stand for removable detectors. The main components of the subject device are the same as the predicate. Components of the x-ray source are the 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 interface and technique selection. The automatic collimator supports high accuracy for selected x-ray field size over SID. Selection of an anatomical study on the imaging software automatically sets up the x-ray generator's pre-programmed exposure technique setting, motorized radiographic stand positioning, x-ray collimation and post image processing for selected study. Also, removable high-resolution grids which have 100 and 180cm (40 and 72 inch) focal distance. The integrated touch screen console located on the tube side, operator can easily control the radiographic techniques and stand positioning. Furthermore, the operator can verify the digital x-ray image on this screen. The GUI, automatically rotates corresponds to rotation angle of U-arm.

The provided text is a 510(k) summary for the DRGEM Corporation's DIAMOND-5A/6A/8A stationary digital diagnostic x-ray system. This summary focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study of the device's diagnostic performance for measuring accuracy against a ground truth.

Therefore, much of the requested information (e.g., acceptance criteria for diagnostic capability, sample sizes for test/training sets, expert qualifications, MRMC studies, standalone performance, and ground truth types for diagnostic accuracy) is not available in this document. The document primarily addresses the safety and performance of the hardware components and software in comparison to a previously cleared device.

Here's the information that can be extracted from the provided text:

Acceptance Criteria and Reported Device Performance (as pertains to safety and technical function):

Detailed Study Information (as requested, with notes on unavailability):

1. Sample size used for the test set and the data provenance: Not applicable/available. The document describes non-clinical testing for safety and functionality, not a clinical study on diagnostic accuracy.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/available. No clinical test set requiring expert ground truth for diagnostic accuracy is described.

3. Adjudication method for the test set: Not applicable/available.

4. 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/available. This device is a digital X-ray system, not an AI-powered diagnostic aide for human readers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable/available. This refers to the performance of the X-ray system itself. The document states "The complete system has been assessed and tested at the factory and by Standards testing facilities. DIAMOND-5A/6A/8A, has passed all predetermined testing criteria." This indicates standalone testing for the system's technical function and safety.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable/available for diagnostic accuracy. For safety and performance testing, the "ground truth" would be adherence to the cited international standards and predetermined testing criteria.

7. The sample size for the training set: Not applicable/available. The device is not an AI algorithm that requires a training set in the conventional sense for diagnostic tasks. Its software (RADMAX) is for image management and system control.

8. How the ground truth for the training set was established: Not applicable/available.

Summary of the Study (as described in the document):

The "study" described in the 510(k) summary is a non-clinical performance and safety assessment comparing the DIAMOND-5A/6A/8A system to its predicate device (also DIAMOND-5A/6A/8A, K192453). The primary purpose was to demonstrate that adding new digital flat panel detectors (Fujifilm, Varex, i-Ray models) and an updated version of the RADMAX image management software (version 1.01) did not negatively impact safety or efficacy and did not raise new safety risks.

The testing involved assessing the complete system's adherence to various international standards for medical electrical equipment, radiation protection, usability, software lifecycle processes, and risk management. The conclusion was that the device met all predetermined testing criteria and demonstrated a safe and effective profile similar to the predicate device. No clinical (diagnostic accuracy) studies are reported in this summary.

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