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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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The DigiX FDX radiographic systems are used in hospitals, clinics and medical practices. DigiX FDX enables radiographic exposure of the whole body including: Skull, chest, abdomen, and extremities and may be used on pediatric, adult and bariatic patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma critical ill) applications. Exposure may be taken with the Patient's sitting, standing, or in the prone/ supine position.

The DigiX FDX System is not meant for mammography.

The DigiX FDX uses an integrated or portable or fixed or wi-fi digital detector for generating diagnostic images by converting X-Ray into electronics signals. DigiX FDX is also designed to be used with conventional film/screen or Computed Radiography (CR) Cassettes.

The DigiX FDX system is a diagnostic X-Ray system intended for general purpose radiographic imaging of the human body. It is not intended for mammographic imaqing.

The DigiX FDX system is comprised of a combination of devices that include a ceiling mounted X-Ray tube suspension, vertical Bucky stand, fixed or mobile patient Bucky table, X-Ray generator, X-Ray tube, beam limiting device, and a solid-state image receptor.

The DigiX FDX systems are not intended to be operated with any other cleared devices, or to be integrated with other software/hardware devices via direct or indirect connections.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document focuses on demonstrating substantial equivalence to predicate devices rather than defining specific quantitative performance metrics as "acceptance criteria" for a new AI/software feature in the way clinical performance studies usually do. Instead, the "acceptance criteria" are implied to be that the modifications do not negatively impact safety or effectiveness, and that the device performs comparably to the predicate devices and meets relevant safety standards.

For the new features explicitly mentioned (Automatic Stitching and Dual Energy Subtraction), the document states they add functionality without affecting patient safety or effectiveness. For the other components, the criteria are often "Same" or "Similar functionality with same imaging results" or "doesn't affect the safety or effectiveness."

To represent this in a table, we'll extract performance comparisons from the "Functional and Specification Differences" table (Table 4) and the "Justification for Differences" (Table 5).

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

The document states:

• "Non-clinical testing included verification and validation testing, image evaluation, testing, and safety testing."
• "Performance testing included functional testing of all motions of the system(s) with respect to the design specifications. Image performance testing was conducted and results included in the submission."
• "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system."

The document does NOT specify a sample size for any test set (clinical or otherwise) in terms of patient data or images used for validation of the radiographic system itself, nor does it mention data provenance (country of origin, retrospective/prospective). It primarily relies on hardware and software equivalence, and compliance with industry standards.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. The document explicitly states "Clinical testing is not applicable." Therefore, there was no clinical study conducted that would necessitate expert readers to establish ground truth for a test set. The evaluation focuses on technical performance and equivalence to predicate devices.

4. Adjudication Method for the Test Set

Not applicable. As no clinical test set requiring expert adjudication was performed, no adjudication method is mentioned.

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

No MRMC comparative effectiveness study was done. The document states "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system." Therefore, there is no information on how much human readers improve with or without AI assistance. The new software features (Automatic Stitching, Dual Energy Subtraction) are presented as additional functionalities that don't affect safety or effectiveness, not as AI-assisted diagnostic tools requiring a comparative effectiveness study.

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

Not applicable. The device is a radiographic system, not an AI algorithm intended for standalone diagnostic performance. While it includes new software features (Automatic Stitching, Dual Energy Subtraction), these are integrated functionalities of the imaging system and not described as standalone diagnostic algorithms requiring independent performance evaluation without human interaction.

7. Type of Ground Truth Used

The "ground truth" for the evaluation is primarily based on:

• Compliance with technical specifications and design requirements: Functional testing, image performance testing.
• Adherence to safety and performance standards: IEC 60601 series, EN ISO 14971, IEC 62366-1, IEC 62304, 21 CFR 1020.30, 21 CFR 1020.31.
• Substantial equivalence to predicate devices: Demonstration that the new device has the same intended use, fundamental technological characteristics, and that any differences do not raise new questions of safety or effectiveness.
• Software documentation assessment: For the software components, including the new features, documentation was provided for a "Moderate Level of Concern" software as per FDA guidance.

No clinical ground truth (e.g., expert consensus, pathology, outcomes data) was used or required given the nature of this submission.

8. Sample Size for the Training Set

Not applicable. The document describes an X-ray imaging system, not an AI/ML device that requires a training set of data. The new software features (Automatic Stitching, Dual Energy Subtraction) are described as functionalities, not adaptive algorithms that learn from data.

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

Not applicable. As there was no training set, there was no ground truth to establish for it.

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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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ProRad Series Stationary Radiographic System is intended for use by a qualified, trained doctor or technician on both adult and paediatric 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 ProRad series Stationary Radiographic System is a diagnostic x-ray system intended for general purpose radiographic imaging of the human body. There are two types of configurations (2FC and 3NC) for ProRad; the difference is in the mounting of the X-ray tube. For X-ray tube mounting the configuration is either the floor mounted (2FC) or ceiling suspension (3NC) assembly.

The devices are a new combination of a previously cleared solid state digital x-ray acquisition panel and software with the diagnostic x-ray components (including Xray tube, high frequency X-ray generator, a tilting vertical bucky, X-ray table and collimator) required to make a complete system. The purchaser may select any of the digital panels and software based on the user's requirements. The other components are also available in different configurations to meet specific customer needs. The X-ray panel and imaging software have been previously cleared by the FDA, and most of the other components are used in previously cleared 510(k) devices.

Here's an analysis of the acceptance criteria and study information for the ProRad 2FC and ProRad 3NC Digital Stationary Radiographic Systems, based on the provided text:

Acceptance Criteria and Device Performance Table:

The document primarily focuses on demonstrating substantial equivalence to predicate devices rather than setting and reporting specific performance metrics with acceptance criteria in a comparative table for novel device features. The "Comparable Properties" table (pages 6-8) is used to show alignment with predicate devices.

1. Sample sized used for the test set and the data provenance:

• Sample Size: Not explicitly stated as a separate "test set" for a dedicated algorithm performance study. Instead, compliance is demonstrated through testing of the integrated system and reliance on previous FDA clearances for individual components.
• Data Provenance: Not applicable in the context of an algorithm performance test set. The clinical images reviewed by a radiologist were "acquired by the device," but the origin (e.g., country, prospective/retrospective status) is not specified.

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

• Number of Experts: One radiologist.
• Qualifications of Experts: Only "a radiologist" is mentioned. Specific qualifications (e.g., years of experience, board certification) are not detailed.

3. Adjudication method for the test set:

• Adjudication method: Not applicable. The radiologist's review was a single assessment, not a consensus or adjudication process among multiple readers.

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:

• MRMC Study: No. The document explicitly states: "Since the digital x-ray panels and software have previously received FDA clearance, a clinical study was not required as per the FDA guidance document." The clinical image review was supplementary.
• Effect size of human reader improvement with AI: Not applicable, as no MRMC study or AI assistance evaluation was conducted. The device is an imaging system, not an AI diagnostic tool.

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

• Standalone Performance Study: No. This device is a diagnostic X-ray system, which intrinsically requires a human (a qualified doctor or technician) in the loop for operation and interpretation. The performance of individual cleared components (digital panels, software) was relied upon.

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

• Type of Ground Truth: For the supplementary review, the "ground truth" was the radiologist's assessment that the images were "acceptable and allowed the radiologist to make an accurate diagnosis." This is a form of expert opinion on image quality and diagnostic utility, rather than an objective "truth" like pathology or outcomes.

7. The sample size for the training set:

• Sample Size for Training Set: Not applicable. This document does not describe a machine learning algorithm that requires a training set. The device is a conventional X-ray system composed of cleared components.

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

• Ground Truth for Training Set: Not applicable, as there is no machine learning algorithm described.

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The Televere Digital Imaging System is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used. Allows imaging of the skull, chest, shoulders, pelvis, and extremities. Not for mammography.

The Televere Digital Imaging System consists of a combination of digital imaging software, a flat panel display (FPD), a PC-based computer and a power supply. The imaging software has previously been cleared by FDA (i.e., K061035, TigerView Professional). This previously cleared software provides basic image adjustment features: An image management system that allows the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. TigerView Professional runs on standard PCcompatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card. The FPD component seeking clearance (PerkinElmer Model XRPad 4343F N) has not been previously cleared by FDA. The FPD uses a large-area amorphous silicon sensor array with a gadolinium oxysulfide (GadOx) scintillator for displaying high quality images over a wide range of dose settings and is intended to be integrated into a complete X-ray system. This premarket notification seeks clearance for a combination finished device consisting of the combination of the previously cleared digital imaging software and the FPD. The combination of the digital imaging software and the FPD does not affect the safety or efficacy of either component device alone, or in combination.

The provided document is a 510(k) premarket notification for the Televere Digital Imaging System. It describes the device, its intended use, and proposes it as substantially equivalent to a predicate device.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a numeric fashion other than stating the new device is "as safe and effective as the predicate device" and that "Clinical images collected demonstrate equal or better image quality as compared to our predicate." However, it does provide a comparative table with performance specifications of the new device against the predicate.

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

The document mentions "Sample clinical images from the new device were also provided however they were not necessary to demonstrate substantial equivalence." It does not specify a sample size for these clinical images, nor does it provide data provenance (country of origin, retrospective/prospective). The primary basis for substantial equivalence seems to be bench testing and comparison of technical specifications.

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 in the document. The substantial equivalence relies on physical and performance characteristic comparisons, not on expert-adjudicated clinical image interpretations for a test set to establish ground truth in the context of device performance metrics like sensitivity/specificity. The statement "Clinical images collected demonstrate equal or better image quality as compared to our predicate" suggests a qualitative assessment, but details about who made this assessment, how many, or their qualifications are absent.

4. Adjudication method for the test set

This information is not provided. Given that quantitative clinical ground truth was not the primary method for demonstrating substantial equivalence, formal adjudication methods are not detailed.

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 done. The Televere Digital Imaging System is a digital X-ray receptor, not an AI-powered diagnostic tool. The purpose of the submission is to demonstrate substantial equivalence to a predicate X-ray system, primarily through technical specifications and bench testing, for image capture. There's no mention of AI or human reader improvement with or without AI assistance.

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

This question is not applicable as the device is an X-ray imaging system, not an algorithm, and does not operate independently in a diagnostic capacity without human interpretation.

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

For the technical performance metrics (MTF, DQE), the ground truth is established by physical measurements and standardized testing according to IEC standards and FDA guidance documents for solid-state digital X-ray panels. For the qualitative assessment of "clinical images," the type of ground truth and method of establishment is not explicitly stated, but it likely refers to a visual comparison of image quality, not a formal disease presence/absence ground truth.

8. The sample size for the training set

This information is not applicable as the Televere Digital Imaging System is a hardware device (digital X-ray receptor) and not a machine learning or AI algorithm that requires a training set.

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

This information is not applicable as the device is not an AI algorithm and does not use a training set.

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The DigiX FDX radiographic systems are used in hospitals, clinics and medical practices. DigiX FDX enables radiographic exposure of the whole body including: Skull, chest, abdomen, and extremities and may be used on pediatric, adult and bariatric patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma critical ill) applications. Exposure may be taken with the Patient's sitting, standing, or in the prone position. The DigiX FDX System is not meant for mammography. The DigiX FDX uses an integrated or portable or fixed or wi-fi digital detector for generating diagnostic images by converting X-Ray into electronics signals. DigiX FDX is also designed to be used with conventional film/screen or Computed Radiography (CR) Cassettes.

The DigiX FDX system is a diagnostic x-ray system intended for general purpose radiographic imaging of the human body. It is not intended for mammographic imaging. The DigiX FDX system is comprised of a combination of devices that include a ceiling mounted x-ray tube suspension, vertical Bucky stand, fixed or mobile patient Bucky table, x-ray generator, x-ray tube, beam limiting device, and a solid-state image receptor. The DigiX FDX systems are not intended to be operated with any other cleared devices, or to be integrated with other software/hardware devices via direct or indirect connections.

Here's a summary of the acceptance criteria and the study information for the Allengers Medical Systems Limited DigiX FDX device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on substantial equivalence to a predicate device (Siemens Ysio K081722) rather than defining explicit, quantitative acceptance criteria for clinical performance. The "acceptance criteria" can be inferred as meeting or being sufficiently similar to the predicate device in terms of functionality and safety, as well as complying with relevant standards.

• G1092: 0.6mm/1.2mm focal spot (Predicate: 0.6mm/1.0mm), 1 MHU (Predicate: 783 kHU), 108 mm target diameter (Predicate: 100 mm).
  G292: 0.6mm/1.2mm focal spot (Predicate: 0.6mm/1.0mm), 600 KHU (Same), 12° target angle (Predicate: 16°), 102 mm target diameter (Predicate: 100 mm). | Similar, providing essentially same imaging resolution and higher loading for some G1092 models. Different target angle for G292 provides full coverage at 40" SID. Differences in heat units and target diameter also noted as "similar" or providing higher loading/instantaneous focal spot loading. |
  | Beam Limiting Device: Construction, compliance with CFR 21 1020.31, automatic feature. | Matches predicate. | Same. |
  | Solid State X-ray Image Detectors: Panel type, active area, pixel pitch, pixel matrix, input scintillator, limiting resolution. | Detectors (e.g., P-E XRPAD 4343F vs. Trixell Pixium 4600):
• Active area: 432x432mm (Predicate: 429x429mm).
• Pixel pitch: 100 µm (Predicate: 143 µm).
• Pixel matrix: 4318x4320 (Predicate: 3001x3001).
• Limiting resolution: 5 lp/mm (Predicate: 3.57 lp/mm).
  Similar differences for other detector models listed. | Essentially the same imaging area. Provides higher resolution for pixel pitch, pixel matrix, and limiting resolution in most cases, which is considered an improvement and not negatively affecting safety or effectiveness. |
  | Viewing Monitors: Size, resolution. | Matches predicate. | Same. |
  | Software Features: DICOM 3.0 compatibility, operating system, user interaction, multi-user, image import/export, acquisition device, image interferences, organization, search, storage, database, viewing, measurement, annotation, operations, security, generator control. | Matches predicate for all listed software features. Also uses previously cleared image processing software. | Same. |
  | Safety Standards Compliance: | Complies with 21 CFR 1020.30, 21 CFR 1020.31, IEC 60601-1, EN 60601-1-2, IEC 60601-1-3, IEC 60601-2-54, EN ISO 14971, EN 62366, EN 62304. | All applicable standards met. |
  | Functional Performance: All system motions, image performance. | All functions met design requirements. Image performance criteria satisfactorily met (details in Section 18 of the original submission, not provided in this extract). | Confirmed. |
  | Software/Firmware Functionality: All functions between DROC software and IntegraX firmware. | All functions passed testing criteria. | Confirmed. |

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

The document explicitly states: "It was determined that clinical evaluation was not required as all imaging devices have been previously cleared by the FDA."
Therefore, there was no clinical test set used for this specific 510(k) submission. The evaluation was based on non-clinical testing and substantial equivalence to previously cleared devices.

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

Not applicable, as no clinical test set requiring expert ground truth was used.

4. Adjudication Method for the Test Set:

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

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. The device is a diagnostic X-ray system, not an AI-powered diagnostic tool, and no MRMC study was conducted.

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

Not applicable. The device is a diagnostic X-ray system, not an algorithm, and its performance is evaluated as a system used by a human operator.

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

Not applicable for clinical ground truth, as no clinical evaluation was performed. For non-clinical performance (image quality, functional testing, safety), the "ground truth" was compliance with design specifications and relevant international standards.

8. The sample size for the training set:

The document does not describe the use of machine learning or AI models that would require a "training set" in the traditional sense. The device is a traditional X-ray system. The component parts, such as solid-state detectors and image processing software, are stated to have been "previously cleared by the FDA" or "tested and evaluated per Guidance for the Submission of 510(k)s for Solid State X-ray Imaging Devices." Therefore, any implicit training (e.g., for image processing algorithms) would have occurred as part of the development and clearance of those component devices, but details are not provided here for the system submission.

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

Not applicable, as no training set for an AI/ML model is described for this device.

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