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The CombiDiagnost R90 is a multi-functional general R/F system. It is suitable for all routine radiography and fluoroscopy exams, including specialist areas like angiography or pediatric work, excluding mammography.

The CombiDiagnost R90 is a multi-functional general Radiography/Fluoroscopy (R/F) system. It is suitable for all routine radiography and fluoroscopy exams, including specialist areas like angiography or pediatric work, excluding mammography.

The CombiDiagnost R90 is a remote-controlled fluoroscopy system in combination with high-end digital radiography. The system is suitable for routine X-ray examinations and special examinations on patients in standing, seated or laying positions. The CombiDiagnost R90 retrieves images by means of a Cesum Iodide flat panel detector.

Philips fluoroscopy systems consist of the following components (standard configuration):

• Basic unit (also called "geometry" or "table unit")
• Workstation Eleva Workspot with integrated generator control, hand switch, keyboard, mouse, touch screen and PC
• Equipped with a dual screen-monitor as standard
• Spot film device (digital camera or flat panel detector)
• X-ray Generator Velara
• X-ray tube assembly mounted in above table mode to be remote controlled
• Receptor: Flat panel detector

Optional components:

• Skyplate wireless portable detectors small and large
• Ceiling Suspension (CSM3)
• Vertical Wall stand (VS2)
• Ceiling Suspension for monitors
• Monitor trolley
• Remote control for RF viewer
• Accessories for "Stitching on the Table"

The CombiDiagnost R90 uses the same workflow from the currently marketed and predicate device, CombiDiagnost R90 (K163210) with only the following modifications:

• additional optional components (like the reference monitor, remote control),
• Eleva Workspot updated to incorporate new imaging features mainly from the previously approved reference device, DigitalDiagnost C90 (K182973) along with functional clusters like Digital Subtraction Imaging and stitching on the table
• updates to improve usability and serviceability.

The Eleva software of the proposed CombiDiagnost R90 is based on a workstation i.e., Eleva Workspot (computer, keyboard, display, and mouse) that is used by an operator to preset examination data and to generate, process and handle digital x-ray images. The Eleva Software system is decomposed into software components. These components are clustered in three component collections like the image handling focused Back-end (BE), the acquisition focused Front-end (FE) and Image Processing (IP). The Eleva software is intended to acquire, process, store, display and export digital fluoroscopy and radiographic images.

The proposed CombiDiagnost R90 is same as the predicate device (K203087) with some modifications as described.

The proposed device complies to 'Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices, dated September 1, 2016'. The solid-state imaging components including the detector in the proposed device have the same physical, functional, and operational characteristics as the predicate device (K203087). Also, other image chain components like X-ray tube and generator, which are used for exposure characteristics and clinical performance evaluation remains the same. Hence all the features and characteristics potentially influencing image quality of the proposed are in accordance with FDA guidance document. Additionally, image quality testing has been performed on the proposed device for the changes that are affecting the image quality.

The provided text is a 510(k) Summary for the Philips Medical Systems DMC GmbH CombiDiagnost R90, which is an X-ray system. This document focuses on demonstrating that the proposed device is substantially equivalent to a previously cleared predicate device, rather than proving a new medical diagnosis or treatment effectiveness. Therefore, the traditional acceptance criteria and study designs typically associated with AI/ML diagnostic devices (e.g., sensitivity, specificity, clinical accuracy, MRMC studies) are not directly applicable or reported in this type of submission.

Instead, the acceptance criteria and studies here are aimed at demonstrating that the modified device maintains the safety and effectiveness of the predicate device and complies with relevant standards and regulations.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Image Quality Details (from document):

Modulation Transfer Function (MTF) (according to IEC 62220-1-3 standard)

Detective Quantum Efficiency (DQE) (according to IEC 62220-1-3 standard) at 2 µGy

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

The document does not specify a "test set" in the context of clinical images or patient data for evaluating a diagnostic algorithm. This submission is for an X-ray imaging system, not an AI diagnostic algorithm. The "tests" mentioned are non-clinical engineering and conformity tests.

• Test Set Sample Size: Not applicable/not specified in the context of clinical images. The testing refers to verification and validation of the system's hardware and software components.
• Data Provenance: Not applicable in the context of clinical images or patient data. The tests are focused on the device's technical specifications and compliance with standards.

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

Not applicable. This is not a study requiring expert-established ground truth for diagnostic accuracy, as it's a submission for an imaging device, not an AI diagnostic tool. The "ground truth" for the engineering tests would be the established technical standards and specifications.

4. Adjudication Method for the Test Set

Not applicable. No clinical image test sets requiring adjudication are mentioned. The testing involves compliance with standards and internal system verification.

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

No. This type of study is not mentioned as it is not relevant for demonstrating substantial equivalence of an X-ray imaging system through non-clinical performance testing.

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

Not applicable. The CombiDiagnost R90 is an X-ray imaging system, not a standalone AI algorithm. While it contains "Eleva software" with imaging features, the submission focuses on the system's overall safety and performance, not a new AI algorithm's standalone diagnostic capability.

7. The Type of Ground Truth Used

The "ground truth" for the evaluations performed in this submission are:

• Engineering Specifications: The defined technical parameters and performance metrics for the device components (e.g., MTF, DQE values, electrical safety, EMC).
• Regulatory Standards: The requirements outlined in FDA recognized consensus standards (e.g., IEC 60601 series) and FDA guidance documents.
• Predicate Device Performance: The established performance and safety characteristics of the legally marketed predicate device (CombiDiagnost R90, K203087), against which the proposed device's performance is compared for substantial equivalence.

8. The Sample Size for the Training Set

Not applicable. This is an X-ray imaging device, not an AI algorithm that requires a training set for machine learning.

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

Not applicable, as there is no training set for an AI algorithm mentioned.

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ProxiDiagnost N90 is a multi-functional general R/F system. It is suitable for all routine radiography and fluoroscopy exams, including specialist areas like angiography or pediatric work, excluding mammography.

The ProxiDiagnost N90 is a multi-functional nearby controlled fluoroscopy system in combination with a high-end digital radiography system consisting of a floor-mounted tiltadjustable patient support table and a scan unit consisting of a tube and a flat panel dynamic detector, Pixium FE4343F, for the fluoroscopy examinations. The tabletop can be moved by a motor in the lateral and longitudinal direction and can be tilted -85° to +90° degrees. The scan unit tilts with the table and can be moved in the longitudinal and lateral direction, relative to the table and to the patient. The fully integrated system is provided with a x-ray tube(s) with collimator and high resolution displays. The ProxiDiagnost N90 is configured with a Philips x-ray generator and a flat panel dynamic detector, Pixium FE4343F, components of the Philips radiography/fluoroscopy Image Chain. As additional options, the ProxiDiagnost N90 can be used as a digital radiography system consisting of a mounted tube in a ceiling suspension together with the portable or fixed detector in the vertical stand.

Based on the provided text, the ProxiDiagnost N90 is evaluated for substantial equivalence to its predicate device, EasyDiagnost Eleva (K031535). The document outlines non-clinical data and makes a case against the need for a clinical study.

Here's an analysis of the requested information:

1. Table of acceptance criteria and the reported device performance:

The document broadly states that "The test results demonstrate that the proposed ProxiDiagnost N90 meets the acceptance criteria and is adequate for its intended use." However, specific numerical acceptance criteria or performance metrics for the ProxiDiagnost N90 are not detailed in a table. The comparison provided focuses on demonstrating technological similarities to the predicate device rather than presenting specific performance thresholds for the new device.

The "Discussion" column in the "Summary of technological characteristics" table implicitly suggests that if a characteristic is "Similar" or "Equivalent" to the predicate, it meets acceptance criteria for substantial equivalence.

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 explicitly states: "The proposed ProxiDiagnost N90 did not require a clinical study since substantial equivalence to the currently marketed and predicate device was demonstrated with the following attributes: Design features, Indication for use, Fundamental scientific technology, Non-clinical performance testing including validation; and Safety and effectiveness."

Therefore, there is no test set sample size from a clinical study for the ProxiDiagnost N90 itself. The evaluation relied on non-clinical verification and validation tests against recognized consensus standards and a comparison to the predicate and reference devices.

No information on data provenance for a clinical test set is available, as no clinical study was conducted.

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

Since no clinical study was performed and no test set with clinical data was used for evaluation, there were no experts used to establish ground truth for a test set in this submission.

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

As no clinical test set was used for evaluation of the ProxiDiagnost N90, no adjudication method was applied for a 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:

There is no mention of a multi-reader multi-case (MRMC) comparative effectiveness study being conducted for the ProxiDiagnost N90. The device is a general R/F system, not an AI-assisted diagnostic tool, so such a study would not be relevant in this context.

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

The device is an imaging system, not an algorithm in the AI sense. Its "performance" would relate to image quality and system functionality, which was assessed through non-clinical performance testing (verification and validation tests according to standards like IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-54, IEC 62220-1). These tests are typically "standalone" in that they evaluate the device's technical specifications and functionality independent of direct human interpretation studies.

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

For the non-clinical performance and validation tests, the "ground truth" would be established by the specified engineering tolerances, recognized international standards (e.g., IEC standards for image quality, safety, and performance), and the performance characteristics of the predicate and reference devices. For instance, the MTF and DQE values for the detector are reported and implicitly "compared" to cleared components, meaning the "ground truth" for the acceptance of these values is their alignment with previously cleared and accepted digital imagers.

8. The sample size for the training set:

As no clinical study was performed and the device is an imaging system (not an AI model requiring a training set), there is no training set sample size.

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

Since no training set was used, ground truth for a training set was not established.

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As a part of a radiographic system, the SkyPlate Detector for Philips Radiography/Fluoroscopy Systems is intended to acquire, process, store, display and export digital radiographic images. The SkyPlate Detector for Philips Radiography/ Fluoroscopy Systems is suitable for all routine radiography exams, including specialist areas like intensive care, trauma, or pediatric work, excluding mammography.

The SkyPlate Detector for Philips Radiography/Fluoroscopy Systems is a Solid State X-ray Imaging Device that converts x-ray patterns into electrical signals. The signals are converted into visible images for use in medical diagnosis. A cesium iodide scintillator absorbs the input x-ray photons in the detector. The cesium iodide scintillator in turn emits visible spectrum photons that illuminate an array of photodetectors that create an electrical charge representation of the x-ray input. A matrix scan of the array converts the integrated charges into a modulated electrical signal.

The SkyPlate Detector for Philips Radiography/Fluoroscopy Systems is optionally installed and is intended to be integrated into an x-ray system, where it constitutes an x-ray receptor for direct radiography x-ray imaging. It is electrically powered by and connected with the x-ray system. The SkyPlate Detector for Philips Radiography/Fluoroscopy Systems is connected to the Philips Eleva Workspot with SkyFlow (cleared via K153318) to create a complete x-ray imaging chain, and is intended to be used for radiography in Philips Radiography/Fluoroscopy systems, such as the CombiDiagnost R90 (cleared via K163210). The SkyPlate Detector for Philips Radiography/Fluoroscopy Systems, is used to acquire diagnostic radiographic images during radiographic procedures.

This document is a 510(k) premarket notification for the SkyPlate Detector for Philips Radiography/Fluoroscopy Systems. It outlines the device's characteristics, intended use, and claims of substantial equivalence to a predicate device.

Here's an analysis of the provided text in relation to your questions:

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

The document does not provide a specific table of quantitative acceptance criteria for device performance. Instead, it states that the device:

• "Complies with the aforementioned international and FDA-recognized consensus standards and device specific guidance documents."
• "Meets the acceptance criteria and is adequate for its intended use."
• "is as safe, as effective, and performs as well or better than the predicate device."
• "provides images of equivalent diagnostic capability."

The full list of standards mentioned are:

• ISO 14971: Medical Devices - Application of risk management to medical devices
• NEMA PS 3.1-3.20 Digital Imaging and Communication in Medicine (DICOM) Set
• AAMI ANSI IEC 62304:2006 Medical Device Software - Software lifecycle processes
• IEC 62220-1: Medical electrical equipment, Characteristics of digital x-ray imaging devices
• IEC 62220-1-1:2015: Medical electrical equipment, Characteristics of digital x-ray imaging devices – Part 1-1: Determination of the detective quantum efficiency – Detectors used in radiographic imaging
• IEC 60601-1: Medical electrical equipment – Part 1: General requirements for basic safety and essential performance (IEC 60601-1:2005 + A1:2012, MOD)
• IEC 60601-1-2: Medical electrical equipment. General requirements for basic safety and essential performance. Collateral standard: Electromagnetic compatibility requirements and tests
• IEC 60601-1-3: Medical electrical equipment. General requirements for basic safety and essential performance. Collateral standard: Radiation in diagnostic X-ray equipment
• IEC 60601-2-54: Medical electrical equipment. Particular requirements for basic safety and essential performance of X-ray equipment for radiography and radioscopy
• Guidance for the Submission of 510(k)s for Solid State C X-ray Imaging Device", issued September 1, 2016
• "Guidance for the Content of Premarket Submissions for O software contained in Medical Device", issued May 11, 2005
• Pediatric information for X-Ray Imaging Device Premarket Notifications, Draft, issued May 10, 2012

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

The document explicitly states: "The SkyPlate Detector for Philips Radiography/Fluoroscopy Systems did not require a clinical study since substantial equivalence to the currently marketed and predicate device was demonstrated with the following attributes: Design features; Indication for use; Fundamental scientific technology; Non-clinical performance testing including validation; and Safety and effectiveness." Therefore, no clinical test set was used for this 510(k) submission, and consequently, no clinical sample size or data provenance is 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)

Since no clinical study was conducted and no clinical test set was used, no experts were used to establish ground truth for a test set.

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

As no clinical study was conducted and no clinical test set was used, no adjudication method was applied.

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

The document does not describe any MRMC comparative effectiveness study. This device is an X-ray detector, not an AI-assisted diagnostic tool.

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

This refers to a standalone performance of an algorithm. The SkyPlate Detector is an X-ray imaging device, not an algorithm. Therefore, this question is not applicable to the device described. The submission relies on "non-clinical performance testing including validation" for the physical device.

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

For the non-clinical performance testing, the ground truth would be established by engineering and laboratory measurements demonstrating compliance with the specified international and FDA-recognized consensus standards. This would involve physical measurements of detector characteristics (e.g., image resolution, detective quantum efficiency, electrical signals, safety parameters) against defined benchmarks within those standards, rather than clinical ground truth from patient data.

8. The sample size for the training set

This question typically applies to machine learning or AI models. Since the device is a physical X-ray detector and not an AI algorithm, there is no concept of a "training set" in the context of this submission. The validation was based on non-clinical performance and engineering tests.

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

As explained above, this question is not applicable as there is no training set for this type of device.

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