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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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CombiDiagnost R90 is a multi-functional general RF 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 lying positions. The CombiDiagnost R90 retrieves images by means of a Cesium Iodide flat panel detector.

Philips fluoroscopy systems (standard configuration) consist of the Basic unit ("geometry" or "table unit"). Workstation Eleva Workspot (with integrated generator control, hand switch, keyboard, mouse, touch screen and PC), dual screen-monitor, Spot film device (digital camera or flat panel detector), Dynamic detector, Fixed detector, X-ray Generator Velara, X-ray tube assembly, Receptor (Flat panel detector). The optional component like 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", are also available.

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. As part of the radiographic system, the Eleva software is intended to acquire, process, store, display and export digital Fluoroscopy and radiographic 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 Front-end Software is intended to acquire images.

• The Back-end Software is intended to query patient data from Radiology Information System (RIS), store, display and export digital radiographic images to Picture Archiving and Communication System (PACS)

• The Image Processing Software is intended to perform the pre and post processing on the acquired raw images.

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 (K202564) along with functional clusters like Digital Subtraction Imaging and stitching on the table
• updates to improve usability and serviceability. -

The provided text does not contain detailed acceptance criteria or a study that directly proves the device meets specific performance metrics in a way that would typically be described for an AI/CADe device. The document is a 510(k) summary for a general radiography/fluoroscopy system (CombiDiagnost R90) and focuses on demonstrating substantial equivalence to a predicate device.

However, based on the information provided, I can infer some aspects related to acceptance and testing.

Here's an attempt to structure the information according to your request, acknowledging the limitations from the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of explicit, quantitative acceptance criteria for the new features (like UNIQUE 2 image processing or Bone Suppression) or their specific performance against those criteria. Instead, it relies on demonstrating that these features, which are either identical to or upgrades from previously cleared devices, maintain or improve safety and effectiveness.

The closest to "acceptance criteria" are the standards and guidance documents followed:

• The Eleva software is upgraded to incorporate new features for better imaging, and tests verified no impact on safety or effectiveness. (Page 7)
• The Image Acquisition remains the same on a basic level, while incorporating new features. (Page 7) |
  | Mitigation of risks associated with changes (software, optional components) | Safety risk assessment report conducted. Risks associated with changes are considered in the risk management report and activities, showing all risks are sufficiently mitigated and overall residual risks are acceptable. (Page 5, 10) |
  | No negative impact on safety and effectiveness compared to predicate. | Comparisons in Table 1 and Table 2 demonstrate that minor differences in technological characteristics (like the OS upgrade, additional reference monitor, firmware tool) or the inclusion of features from a reference device (UNIQUE 2, Bone Suppression) do not affect the safety or effectiveness of the CombiDiagnost R90 when compared to the predicate device. (Pages 6-9) |
  | Adequate Human Factors and Usability. | Human Factors and Usability Engineering Test performed. (Page 10) |

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

The document does not specify a "test set" in terms of patient data or image datasets for the non-clinical performance tests mentioned. The testing refers to conformance to standards and internal verification/validation processes for the device itself. Given it's a 510(k) for an X-ray system, not an AI diagnostic algorithm, the "test set" would typically refer to phantom images, system measurements, and functional tests rather than a patient image dataset.

• Sample Size: Not explicitly stated for any specific test. The phrase "non-clinical verification and validation tests as well as image quality testing" suggests a range of internal engineering and performance tests.
• Data Provenance: Not applicable in the context of patient data as this summary focuses on device substantial equivalence rather than a new diagnostic AI a diagnostic AI algorithm. The device manufacturer is Philips Medical Systems DMC GmbH, located in Hamburg, Germany.

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 because the submission is not for an AI/CADe device requiring expert ground truth for interpretation of medical images. The "ground truth" for this type of device would be established by engineering specifications, physical measurements, and compliance with recognized standards.

4. Adjudication Method for the Test Set

Not applicable, as this is not an AI/CADe device requiring human interpretation adjudication.

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 performed. This type of study is typically conducted for AI/CADe devices to evaluate their impact on human reader performance, which is not the primary focus of this 510(k) for an X-ray imaging system. The document explicitly states: "The CombiDiagnost R90 did not require a clinical study since substantial equivalence... was demonstrated..." (Page 11).

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

This is not applicable as the device is an X-ray system, not a standalone AI algorithm. It mentions "Image Processing Software" and features like "UNIQUE 2" and "Bone Suppression," but these are integrated functionalities within the imaging system to enhance image quality, not standalone diagnostic algorithms.

7. The Type of Ground Truth Used

For an X-ray imaging system, the "ground truth" for non-clinical testing would typically involve:

• Engineering Specifications: Conformance to design parameters and functional requirements.
• Physical Measurements: Using phantoms and test equipment to measure parameters like resolution, contrast, dose, noise, and geometric accuracy.
• Compliance with Standards: Meeting the requirements outlined in recognized national and international standards (e.g., AAMI ANSI ISO 14971, AAMI ES60601-1, IEC 60601-1-2/3, IEC 60601-2-54, IEC 62220-1-1).

The document mentions "image quality testing" (Page 10) and verifies that upgraded software features (like UNIQUE 2) aim to provide "improved image processing, reduced noise, and improved contrast" (Page 8), suggesting these metrics are part of the testing ground truth.

8. The Sample Size for the Training Set

Not applicable. This device is an X-ray system, not a machine learning model that requires a training set of data. The software components are developed and verified through traditional software engineering processes rather than machine learning training.

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

Not applicable, as there is no machine learning "training set" for this device.

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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 remote controlled fluoroscopy system in combination with a high-end digital radiography system consisting of a floor-mounted tilt- and heightadjustable patient support and a scan unit consisting of a tube and a flat panel detector, Pixium FE 4343F. The tabletop can be moved by a motor in the lateral direction and can be tilted +/- 90 degrees. The scan unit tilts with the table and can be moved in the longitudinal direction, relative to the table and to the patient. The fully integrated system is provided with a touch screen console, glass or metal x-ray tube(s) with collimator and high resolution displays. As a fully integrated system, the proposed CombiDiagnost R90 can be configured with a Philips generator, the flat panel detector Pixium FE 4343F, and the Philips Dynamic Eleva Image Chain acquisitionstation also provided with the currently marketed and reference device, Eleva Workspot with SkyFlow (Eleva Workspot). The proposed CombiDiagnost R90 uses the same workflow from the currently marketed and reference device, Eleva Workspot with SkyFlow. The only modification to the Eleva Workspot is integration with the Pixium FE 4343F detector.

The provided text is a 510(k) summary for the Philips CombiDiagnost R90, an X-ray system. This document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study proving the device meets specific acceptance criteria in the manner one might expect for a diagnostic AI algorithm.

Therefore, much of the requested information regarding acceptance criteria for a diagnostic performance study, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, or standalone performance of an AI algorithm is not applicable to this type of submission. This document describes a medical device, not a diagnostic AI.

However, I can extract the information related to the device's technical specifications and the non-clinical testing performed to show its safety and effectiveness.

Here's the breakdown of the available information:

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

The document does not provide a specific table of quantitative acceptance criteria for diagnostic performance and corresponding reported performance values for the CombiDiagnost R90's imaging capabilities (e.g., sensitivity, specificity for a particular pathology). Instead, it presents a comparison of technological characteristics between the proposed device and its predicate, along with a statement that non-clinical tests met acceptance criteria.

Technological Characteristics Comparison (Proposed Device vs. Predicate Device)

The study (non-clinical verification and validation tests as well as image quality testing) "demonstrate[d] that the proposed CombiDiagnost R90 meets the acceptance criteria and is adequate for its intended use." The acceptance criteria for these non-clinical tests are defined by the referenced international and FDA-recognized consensus standards.

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

This information is not provided in the document as it is a 510(k) submission for an X-ray system, not a diagnostic AI algorithm. The "test set" here refers to the physical device undergoing non-clinical technical testing, not a dataset of patient images.

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)

This information is not applicable as the document describes non-clinical technical testing of an X-ray system, not a diagnostic study requiring expert ground truth for image interpretation.

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

This information is not applicable for the same reasons as #3.

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

An MRMC study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, which is not the purpose of this 510(k) submission for an X-ray system.

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

A standalone performance study of a diagnostic algorithm was not done. This document concerns an X-ray imaging system.

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

For the non-clinical testing of the CombiDiagnost R90, the "ground truth" would be established by engineering specifications and validated measurement equipment according to the referenced standards (e.g., IEC 62220-1 for detective quantum efficiency, IEC 60601 series for safety and performance). This is a technical ground truth, not a clinical one based on patient outcomes or expert reads.

8. The sample size for the training set

This information is not applicable as the device is an X-ray system, not an AI algorithm requiring a training set of images.

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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