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The DigitalDiagnost is intended to acquire, process, store, display and export digital radiographic images. The DigitalDiagnost is suitable for all routine radiography examinations, including specialist areas like intensive care, trauma or pediatric work, excluding fluoroscopy, angiography and mammography.

The proposed DigitalDiagnost is a high-end digital radiography system consisting of a height adjustable patient support table and a ceiling suspension consisting of a tube including a control handle used to acquire images with a flat panel fixed RAD detector. Additionally, different vertical stands for the radiography examinations are available. The ceiling suspension can be moved in longitudinal and lateral directions and additionally the tube can be tilted and rotated as well. The system is configured with a Philips x-ray generator and a flat panel fixed RAD detector, Pixium 4343RCE. Together with the tube these components form the radiography Image Chain. The additional option of the portable wireless detector i.e. the SkyPlates family can be used for free exposures as well as in the patient support table or in the vertical stand.
The proposed DigitalDiagnost is a modification of the predicate device, DigitalDiagnost C90 (K202564). The modifications include change of colour of the table, stand and ceiling suspension; changes in ceiling suspension, service features and a software update. The changes related to the software updates and service features have been recently cleared in the reference device, CombiDiagnost R90 (K203087).

The provided text describes a 510(k) summary for the Philips Medical Systems DMC GmbH DigitalDiagnost, demonstrating its substantial equivalence to a predicate device. The information details the device, its intended use, and the non-clinical tests performed. It explicitly states that no clinical data was submitted for this 510(k) premarket notification.

Therefore, many of the requested details regarding acceptance criteria for device performance, expert ground truth, MRMC studies, or training/test set specifics cannot be directly extracted from the provided document as they pertain to clinical studies or AI/algorithm performance evaluations, which were not part of this submission. The provided text focuses on demonstrating the substantial equivalence of modifications (e.g., color changes, mechanical button changes, software updates for service features) to an existing cleared device through non-clinical testing.

Here's a breakdown based on the available information:

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

The acceptance criteria are implicitly met by "Pass" results for the listed non-clinical tests. The reported device performance is that it complies with the requirements for each test.

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

The document does not specify a "test set" in the context of clinical data, as it explicitly states that no clinical data was submitted. The tests conducted were non-clinical verification and validation tests, implying laboratory or engineering testing rather than a clinical study with patient samples. Therefore, information on sample size for a test set (meaning patient data) and data provenance (country of origin, retrospective/prospective) is not applicable or provided in this 510(k) summary.

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 ground truth was established for a test set in this non-clinical submission.

4. Adjudication method (e.g., 2+1, 3+1, none) 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

No MRMC study was performed or reported, as no clinical data or AI assistance feature is mentioned in the context of this 510(k) for the DigitalDiagnost. The changes are related to physical components and underlying software infrastructure, not an AI-based interpretation aid.

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

Not applicable, as there is no mention of a standalone algorithm for diagnostic performance. The device is an X-ray system, and the software updates are described as related to service features (logging, remote export, etc.) and not image interpretation algorithms.

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

For the non-clinical tests, the "ground truth" would be the engineering specifications and performance standards against which the device was tested (e.g., system requirements, risk control measures, imaging performance requirements, usability requirements). These are established technical benchmarks, not clinical ground truth derived from expert consensus or pathology.

8. The sample size for the training set

Not applicable, as there is no mention of a training set, which is typically associated with machine learning or AI models. The software updates are for system functionality and service.

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

Not applicable, as there is no training set for an AI/ML model.

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The DigitalDiagnost C90 is intended to acquire, process, store, display and export digital radiographic images. The DigitalDiagnost C90 is suitable for all routine radiography examinations, including specialist areas like intensive care, trauma or pediatric work, excluding fluoroscopy, angiography and mammography.

The proposed DigitalDiagnost C90 is same as the 510(K) approved predicate (K182973) as mentioned below. It is a high-end digital radiography system consisting of a height adjustable patient support table and a ceiling suspension consisting of a tube including a control handle used to acquire images with a flat panel fixed RAD detector. Additionally, different vertical stands for the radiography examinations are available. The ceiling suspension can be moved in longitudinal and lateral directions and additionally the tube can be tilted and rotated as well. The proposed DigitalDiagnost C90 is configured with a Philips x-ray generator and a flat panel fixed RAD detector, Pixium 4343RCE, together with the tube these components form the radiography Image Chain. The proposed DigitalDiagnost C90 introduces a new wireless portable detector, pixium 3543DR i.e. SkyPlate E (cleared in reference device 510(K) K191813) and their relevant grids, in addition to the family of SkyPlate detectors (pixium 3543EZ i.e. Large and pixium 2430EZ i.e. Small) that are already integrated in the currently marketed (predicate) DigitalDiagnost C90 (K182973).

The Philips DigitalDiagnost C90 is a stationary x-ray system, and the submission K202564 introduces the SkyPlate E detector and its relevant grids as a modification to the previously cleared DigitalDiagnost C90 (K182973). The acceptance criteria and the study proving the device meets these criteria are primarily based on demonstrating substantial equivalence to the predicate device through non-clinical performance testing. No clinical study was performed.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Philips DigitalDiagnost C90, specifically regarding the addition of the SkyPlate E detector, are based on demonstrating equivalence or non-inferiority to the predicate device (DigitalDiagnost C90 with existing SkyPlate detectors) in key technological characteristics and the maintenance of clinical image quality, safety, and effectiveness. The reported device performance indicates that the new SkyPlate E detector either meets or is equivalent to the performance of the existing detectors, or that any differences do not negatively impact clinical image quality or safety.

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 DigitalDiagnost C90 did not require 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; and Safety and effectiveness."

Therefore, there was no clinical test set with human subject data used for this specific 510(k) submission. The evaluation was based on non-clinical performance data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable, as no clinical test set was used for this submission. The ground truth, in this context, was established through adherence to recognized standards and technical measurements, not expert clinical assessment of a dataset.

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

Not applicable, as no clinical test set 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. This submission is for an x-ray system with a new detector, not an AI-powered diagnostic tool. No MRMC study was performed.

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

Not applicable, as this is not an AI algorithm. The performance evaluation was for the imaging system itself.

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

The "ground truth" for this submission was established through:

• Adherence to international and FDA-recognized consensus standards: This includes technical specifications and performance metrics outlined in standards like IEC 60601 series, IEC 62220-1, and IEC 62304.
• Results of non-standard performance tests: These tests are designed to verify specific technical aspects of the device and confirm its functionality and safety. The report mentions "System Verification Test," "Image Quality Test," and "Human Factors and Usability Engineering Test."
• Comparison to the predicate device: The core of the substantial equivalence claim relies on demonstrating that the new detector either performs the same as, or does not negatively impact the performance of, the previously cleared predicate device based on its technical specifications.

8. The sample size for the training set

Not applicable, as this is not an AI algorithm requiring a training set.

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

Not applicable, as this is not an AI algorithm.

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The DigitalDiagnost C50 system is intended for use in generating radiographic images of human anatomy by qualified/ trained doctor or technician. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. This device is not intended for mammographic applications.

The DigitalDiagnost C50 Digital Radiography System (DigitalDiagnost C50) is a flexible digital radiography (DR) system that is designed to provide fast and smooth radiography examinations of sitting, standing or lying patients. The DigitalDiagnost C50 consist of the following components: ceiling suspension with X-ray assembly, wall stand with detector carrier, patient table with detector carrier and floating table top, high voltage generator, and an acquisition and reviewing workstation for post-processing, storage and viewing of images. Images may be transferred via a DICOM network for printing, storage and detailed review.

Here's a breakdown of the acceptance criteria and study information for the DigitalDiagnost C50, based on the provided text.

1. Table of Acceptance Criteria & Reported Device Performance:

Study Proving Acceptance Criteria:

The document states that a non-clinical verification/validation study was performed. The basis for substantial equivalence is that the DigitalDiagnost C50 is considered equivalent to the predicate DigitalDiagnost C50 (K163410) based on:

• Identical Indications for Use.
• Fundamental scientific technology (including largely identical components or components identical to other cleared reference devices).
• Non-clinical performance testing (demonstrating compliance with standards).
• Safety and effectiveness (as supported by the non-clinical testing).

The non-clinical verification and validation tests demonstrated that the DigitalDiagnost C50:

• Complies with the aforementioned international and FDA-recognized consensus standards and FDA guidance documents.
• Meets the acceptance criteria and is adequate for its intended use.

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

The document explicitly states: "The DigitalDiagnost C50 does not require clinical study..." and "Summary of Clinical Data: Based on the information provided above, the DigitalDiagnost C50 is considered substantially equivalent to the currently marketed and predicate DigitalDiagnost C50 (K163410, January 4, 2017) in terms of fundamental scientific technology."

Therefore, there appears to be no clinical test set, sample size, or specific data provenance for a clinical study as part of this 510(k) submission. The evaluation relies on non-clinical performance data and equivalence to predicate/reference devices.

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

Since no clinical study with a test set was performed, this information is not applicable and not provided in the document.

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

Since no clinical study with a test set was performed, this information is not applicable and not provided in the document.

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 MRMC comparative effectiveness study was mentioned. The device described, DigitalDiagnost C50, is an X-ray system, not an AI-assisted diagnostic device. Therefore, this information is not applicable and not provided in the document.

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

The DigitalDiagnost C50 is an X-ray imaging system. There is no mention of a standalone algorithm-only performance study, as it's not a standalone diagnostic algorithm. Therefore, this information is not applicable and not provided in the document.

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

For the non-clinical verification and validation tests, the "acceptance criteria" were derived from international and FDA-recognized consensus standards and FDA guidance documents (listed on pages 11-12). These standards themselves implicitly define the "ground truth" or acceptable performance ranges for device characteristics, image quality, electrical safety, radiation protection, software lifecycle, usability, and risk management. No other forms of expert consensus, pathology, or outcomes data are mentioned for establishing ground truth for the device's technical specifications.

8. The sample size for the training set:

Since no clinical study or AI algorithm training is described for this device, this information is not applicable and not provided in the document.

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

Since no clinical study or AI algorithm training is described for this device, this information is not applicable and not provided in the document.

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The DigitalDiagnost C90 is intended to acquire, process, store, display and export digital radiographic images. The DigitalDiagnost C90 is suitable for all routine radiography examinations, including specialist areas like intensive care, trauma or pediatric work, excluding fluoroscopy, angiography and mammography.

The DigitalDiagnost C90 is a high-end digital radiography system consisting of a height adjustable patient support table and a ceiling suspension consisting of a tube including a control handle used to acquire images with a flat panel fixed RAD detector. Additionally, different vertical stands for the radiography examinations are available. The ceiling suspension can be moved in longitudinal and lateral directions and additionally the tube can be tilted and rotated as well. The DigitalDiagnost C90 is configured with a Philips x-ray generator and a flat panel fixed RAD detector, Pixium 4343RCE (K170113 - February 9, 2017), together with the tube these components form the radiography Image Chain. As additional options, a portable detector (K141736 - July 25, 2014) can be used for free exposures as well as in the patient support table or in the vertical stand.

The provided text describes the Philips DigitalDiagnost C90, a stationary X-ray system, and states that it did not require a clinical study. Instead, substantial equivalence was demonstrated through non-clinical performance testing and validation.

However, the document does not contain a table of acceptance criteria or details of a study that proves the device meets specific acceptance criteria related to its performance beyond general safety and equivalence to a predicate device. It confirms that the device meets "the acceptance criteria" in general, but does not quantify them or describe the study in detail.

Therefore, many of the requested elements cannot be extracted from the provided text.

Here's a breakdown of what can and cannot be provided based on the input:

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

• Cannot be provided. The document states "The test results demonstrate that the proposed DigitalDiagnost C90 meets the acceptance criteria," but does not specify what those criteria are or report detailed device performance against them. It focuses on demonstrating substantial equivalence to a predicate device based on similar technological characteristics and adherence to 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):

• Cannot be provided. The document refers to "nonclinical verification and validation tests as well as image quality testing" but gives no details about the sample size of any test sets or the provenance of any data used in these non-clinical tests.

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):

• Cannot be provided. Since no specific clinical or performance study with a test set and ground truth is detailed, information about experts and their qualifications is absent.

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

• Cannot be provided. No details on adjudication methods for a test set are mentioned.

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:

• Cannot be provided. The document explicitly states: "The proposed DigitalDiagnost C90 did not require a clinical study". Therefore, no MRMC study with AI assistance was performed or described.

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

• Cannot be provided. The device is an X-ray system, not primarily an AI algorithm. Its performance is evaluated as an imaging system, and no standalone algorithm performance is discussed.

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

• Cannot be provided. As no specific performance study is detailed, the type of ground truth used is not mentioned.

8. The sample size for the training set:

• Cannot be provided. The document does not describe any machine learning or AI components that would require a "training set" in the context of X-ray image interpretation or diagnostics. The device is a radiographic image acquisition, processing, storage, display, and export system.

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

• Cannot be provided. As no training set is discussed, how its ground truth was established is not relevant or provided.

In summary, the provided document focuses on demonstrating substantial equivalence to a predicate device (Philips Eleva Workspot for DigitalDiagnost K141736) through comparisons of technological characteristics, adherence to recognized standards for safety and performance (e.g., ISO 14971, IEC 60601 series), and non-clinical testing for verification and validation. It explicitly states that a clinical study was not required. No specific "acceptance criteria" table or quantitative performance data from a dedicated study assessing diagnostic accuracy or similar metrics are present.

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The DigitalDiagnost C50 system is intended for use in generating radiographic images of human anatomy by qualified/ trained doctor or technician. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. This device is not intended for mammographic applications.

The Philips DigitalDiagnost C50 Digital Radiography System (Philips DigitalDiagnost C50) is a flexible digital radiography (DR) system that is designed to provide fast and smooth radiography examinations of sitting, standing or lying patients.

The Philips DigitalDiagnost C50 consists of the following components: ceiling suspension with X-ray assembly, wall stand with detector carrier, patient table with detector carrier and floating table top, high voltage generator, and an acquisition and reviewing workstation for post-processing, storage and viewing of images. Images may be transferred via a DICOM network for printing, storage and detailed review.

Based on the provided text, the device in question, the Philips DigitalDiagnost C50, is a stationary x-ray system cleared through a 510(k) premarket notification. The document does not describe acceptance criteria or a study that proves the device meets acceptance criteria in the context of an AI/algorithm-driven diagnostic aid.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Philips DuraDiagnost K141381) and a reference device for the wireless detector (Varian Nexus DR™ Digital X-ray Imaging System K161459).

Therefore, I cannot provide the requested information about acceptance criteria and a study proving the device meets acceptance criteria related to AI/algorithm performance, a multi-reader multi-case study, standalone algorithm performance, or the ground truth establishment for a training set. The device is a traditional x-ray system, not an AI-powered diagnostic tool as suggested by some of the detailed questions.

However, I can extract information regarding overall device compliance and performance from the text as it relates to demonstrating substantial equivalence for an X-ray system:

Acceptance Criteria and Device Performance for the Philips DigitalDiagnost C50

The provided text on the Philips DigitalDiagnost C50's 510(k) submission does not include acceptance criteria and a study in the context of an AI-driven diagnostic device. Instead, it focuses on demonstrating substantial equivalence to predicate and reference devices for a stationary X-ray system. The "acceptance criteria" mentioned refer to the device meeting the requirements set forth by international and FDA-recognized consensus standards and device-specific guidance documents, as well as the successful completion of non-clinical verification and validation tests.

1. Table of Acceptance Criteria and Reported Device Performance (as related to Substantial Equivalence and Safety/Effectiveness):

The document details a comparison of technological characteristics between the proposed device (DigitalDiagnost C50) and its predicate (Philips DuraDiagnost) and reference device (Varian Nexus DR™ Digital X-ray Imaging System for the wireless detector). The "acceptance criteria" here are implicitly that the proposed device's characteristics are either identical or that any minor differences do not affect the safety or effectiveness, thus demonstrating substantial equivalence (SE).

2. Sample Size and Data Provenance for Test Set (for an AI/Algorithm):

• Not applicable. The submission is for a traditional X-ray system, not an AI/algorithm-driven diagnostic device. The performance data relies on comparing the technical specifications and non-clinical bench testing against established standards and predicate devices.

3. Number of Experts and Qualifications to Establish Ground Truth (for an AI/Algorithm):

• Not applicable. See point 2.

4. Adjudication Method for Test Set (for an AI/Algorithm):

• Not applicable. See point 2.

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

• Not applicable. The document explicitly states: "The DigitalDiagnost C50 did not require a clinical study since substantial equivalence to the primary currently marketed and predicate device was demonstrated with the following attributes: Design features; Indication for use; Fundamental scientific technology; Non-clinical performance testing; and Safety and effectiveness." There is no mention of an MRMC study or an effect size for human readers with or without AI assistance.

6. Standalone Algorithm Performance:

• Not applicable. The device is an X-ray system, not a standalone algorithm.

7. Type of Ground Truth Used (for an AI/Algorithm):

• Not applicable. For this X-ray system, "ground truth" for performance is established through adherence to recognized standards, technical specifications, and successful non-clinical performance (bench) testing, demonstrating that the images generated are of appropriate quality and the system functions safely and effectively as intended.

8. Sample Size for the Training Set (for an AI/Algorithm):

• Not applicable. See point 2.

9. How the Ground Truth for the Training Set Was Established (for an AI/Algorithm):

• Not applicable. See point 2.

In summary, the Philips DigitalDiagnost C50 is a conventional X-ray system whose acceptance criteria are fundamentally tied to demonstrating substantial equivalence to legally marketed predicate devices through comprehensive non-clinical performance (verification and validation) tests and adherence to established international and FDA-recognized consensus standards. The document does not describe the evaluation of an AI or algorithm.

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