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The EasyVision Workstation Release 6 is an image processing workstation software package designed to run on standard PC hardware. The hardware required is made up of "off-the-shelf" standard computer components. The Easy Vision Workstation Release 6 software receives image data from medical scanning devices, such as CT or MRI, or from image archives and performs viewing, image manipulation, communication, printing and quantification of images.

The device is a software package able to run on "off the shelf" hardware components. The system operating software is a standard Windows XP Professionel operating system. The application software can be divided in view, print, store and link functions. Communication with modalities such as MRI and CT and with archive systems, operates via a standardised DICOM protocol on top of a TCP/IP network.

This 510(k) submission for the Philips EasyVision Workstation Release 6 focuses on demonstrating substantial equivalence to a predicate device rather than presenting a de novo study with specific acceptance criteria and performance data. Therefore, many of the requested sections (e.g., acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, training set details) are not explicitly present in the provided document.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Not applicable. The document does not describe specific acceptance criteria or quantitative performance metrics for a study to prove the device meets those criteria. The submission is a claim of substantial equivalence to a predicate device.

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

Not applicable. No specific test set or study data is described in this submission. The "test" in this context refers to demonstrating the equivalence in functionality and safety to the predicate device, not in a traditional clinical performance study with a test set of cases.

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

Not applicable. No ground truth establishment or expert review process for a test set is described.

4. Adjudication Method for the Test Set

Not applicable. No test set requiring adjudication is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. An MRMC comparative effectiveness study is not mentioned or described in the provided document.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No. This device is an image processing workstation software package, which inherently involves human interaction for viewing, manipulation, and quantification. It is not an AI algorithm intended for standalone diagnostic performance.

7. The Type of Ground Truth Used

Not applicable. The submission does not describe a performance study where ground truth would be established for diagnostic accuracy. The ground truth for proving substantial equivalence would be the established functionality and safety profile of the predicate device.

8. The Sample Size for the Training Set

Not applicable. The document does not mention any machine learning or AI components that would require a "training set" in the context of algorithm development.

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

Not applicable. As no training set is mentioned, the method for establishing its ground truth is also not applicable.

Summary of Relevant Information from the Provided Document:

• Device Type: Image processing workstation software package.
• Purpose: Receives image data from medical scanning devices (CT, MRI) or archives, and performs viewing, image manipulation, communication, printing, and quantification of images.
• Intended Use Statement: "The EasyVision Workstation Release 6 is an image processing workstation software package designed to run on standard PC hardware. The hardware required is made up of "off-the-shelf" standard computer components. The Easy Vision Workstation Release 6 software receives image data from medical scanning devices, such as CT or MRI, or from image archives and performs viewing, image manipulation, communication, printing and quantification of images."
• Regulatory Pathway: 510(k) premarket notification.
• Predicate Device: Philips EasyVision Workstation (K920950).
• Substantial Equivalence Claim: The Philips Easy Vision Workstation Release 6 is substantially equivalent to the Easy Vision Workstation systems (K920950).
• Safety Information: "No new hazards are introduced by the development of Easy Vision Workstation Release 6. Hazards known during the lifecycle of the Easy Vision Workstations are again considered and measurements are taken."

In essence, this 510(k) submission is a declaration that the new device has the same intended use, technological characteristics, and safety profile as a previously cleared device, rather than a clinical study evaluating its performance against specific acceptance criteria.

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The BOLD Analysis option for the EasyVision is intended for use in analyzing images created using the BOLD function of a Gyroscan NT system. The BOLD Analysis option is useful in quantifying small susceptibility changes in the human brain, created by the execution of specific tasks.

The BOLD Analysis package supports the visualization and analysis of dynamic MRI studies based on Blood Oxygen Level Dependent (BOLD) contrast. The image contrast differs over dynamic scans as a result of the variation of blood oxygenation through task performance by the subject (e.g. finger tapping). BOLD data can be processed with the BOLD Analysis package to provide data analysis based on standard statistical methods.

The provided text is a 510(k) Summary for the Philips Easy Vision Family Workstation Option BOLD Analysis Package. It describes the device's intended use and safety information, as well as the FDA's clearance letter. However, this document does not contain any information about acceptance criteria, device performance metrics, or any studies proving the device meets acceptance criteria.

Therefore, I cannot fulfill your request for the specific details outlined in your prompt based on the provided text. The document focuses on regulatory clearance based on substantial equivalence to a predicate device rather than detailed performance studies.

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The Quantitative MT Analysis option on the Easy Vision is intended for use in quantifying the Magnetization Transfer in tissue. The ratio image enhances the image contrast of MT sensitive tissue by the elimination of the T1 and T2 (spin-lattice and spin-spin relaxation time) effect. Visualization of Magnetization Transfer effects in sensitive tissue can improve lesion conspicuity, e.g., in white matter and cartilage.

The Quantitative MT Analysis option uses MTC images created by an MR system and transferred to the EasyVision. The image contrast can be changed by calculating the ratio (based on (MT image- non-MT image)/MT image)) of the scans with and without the MT effect. The resultant image represents the percentile MT effect. The image contrast therefore becomes independent of the T1 (spin-lattice) and T2 (spin-spin) relaxation times and is defined by the MT effect alone.

The provided text does not contain information regarding acceptance criteria or a study proving the device meets them. The document is a 510(k) summary for the Philips Easy Vision Family Workstation Option Quantitative MT Analysis Package, primarily focusing on its description, intended use, and substantial equivalence to a predicate device, as determined by the FDA.

Therefore, I cannot provide the requested information in the specified format from the given text.

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EasyCorrect is intended for use in situations where digital images acquired from fluoroscopic imaging systems without distortion are required. The corrected images may be either hard-copy or soft-copy. Examples of (but not limited to) such situations are: making stereotactic measurements for Radiation Treatment Planning Systems or reconstructing digital spotfilm series into composite (survey) images.

The EasyCorrect package is an option to the Vascular Analysis Package. EasyCorrect will support the creation of images acquired by a digital image intensifier based system that can be compared to conventional acquired images (cassette film). Thereby the same measurements can be performed on the digital acquired image as on the conventional acquired image. The EasyCorrect package will correct images for distortion through the following process: Calibration and clinical images are acquired according to acquisition protocols described in documentation delivered with the system. The calibration image will be acquired with a grid phantom included in the package. The software will compare the geometric characteristics of the calibration image (taken with the grid) with the actual geometrical characteristics of the grid. The difference(s) in geometrical characteristics between the two images is a measure of the distortion(s) in the digital acquired image. By applying the result of this calculation of distortion to clinical images taken under the same conditions as the calibration grid image, the clinical images can be corrected for the distortion(s) introduced by the digital technique.

The provided text is a 510(k) summary for the Philips EasyVision Family Workstation Option (EasyCorrect). It describes the device, its intended use, and the regulatory approval process, but it does not contain explicit acceptance criteria or a detailed study report demonstrating how the device meets specific performance metrics.

However, based on the information provided, we can infer some aspects and highlight what is missing.

Inferred Acceptance Criteria and Reported Device Performance (Based Solely on the Provided Text)

Missing Information (Not Available in the Provided Text)

The provided document is a 510(k) summary, which typically focuses on substantial equivalence and intended use. It does not contain the detailed study information requested. Therefore, the following points cannot be answered from the given text:

2. Sample size used for the test set and the data provenance: No information on the number of images or cases used for demonstrating the correction capability, nor their origin (country, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: There is no mention of experts or their qualifications involved in evaluating the corrected images.
4. Adjudication method: Not discussed.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: No information on human reader studies or comparison with/without AI assistance. The device is a correction tool, not necessarily an AI interpretation tool in the modern sense.
6. Standalone performance (algorithm only without human-in-the-loop performance): While the description details how the algorithm works, there are no reported quantitative performance metrics (e.g., distortion reduction percentage, accuracy of measurements on corrected images) that would typically be part of a standalone performance study.
7. Type of ground truth used: The "ground truth" for distortion is inherently the known geometry of the grid phantom. However, how the effectiveness of the correction was validated against a ground truth (e.g., pathology, clinical outcomes, or expert consensus on linearity/measurement accuracy) is not detailed.
8. Sample size for the training set: Not applicable or not described, as the correction method relies on a calibration image (grid phantom) and a calculation from that, rather than a large "training set" in the machine learning sense.
9. How the ground truth for the training set was established: As above, the "ground truth" for the calibration is the known, ideal geometry of the grid phantom.

Summary of What the Document Provides vs. What it Lacks:

The Philips 510(k) summary provides a high-level description of the EasyCorrect device, its mechanism for distortion correction using a grid phantom calibration, and its intended use. It emphasizes that the corrected images can be used for measurements typically done on conventional images. However, it does not delve into the detailed performance metrics, validation studies, sample sizes, expert involvement, or statistical analyses that would typically be required to fully address the requested points regarding acceptance criteria and proof of their fulfillment. The document's purpose is to establish substantial equivalence for regulatory clearance, not to provide a comprehensive technical performance report.

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The Vascular Analysis Package is intended for off-line image processing and manipulation of digitally acquired datasets from Integris systems. The use of the Vascular Analysis package is comparable with that on the Integris operator console (the algorithms used with the Easyvision are identical to those already used on the Integris systems, although the user interface is different).

With the Vascular Analysis package the user can optimize images and perceived image quality for vascular application specific purposes.

The vascular analysis package supports the postprocessing on Digital Subtraction Angiography (DSA) images done to perform diagnosis. In a vascular study series of images are acquired either with or without contrast media. These contrast media can be iodine or CO2, and they make the vasculature visible in the image. The features in the vascular package allow for optimizing these images in the following way. Subtraction is a common used technique in DSA . Two images representing the same part of the anatomy (one with contrast media and one without contrast media) are subtracted from each other. The resulting image is an image that displays the vascular anatomy/pathology only, due to the fact that all equal anatomical structures in the two images are subtracted from each other. Thereby leaving only visible the vascular structures filled with contrast media. Run subtraction is identical to subtraction but now the subtraction process is applied to two series of images wherein image 1 of series 1 correlates w.r.t anatomy/position to image 1 in series 2.

Landmarking will allow to bring back some of the anatomical structure back into the image as to relate vascular pathology to anatomical position. Sometimes there can be a mismatch between two images that are subtracted from each other due to patient movement. To correct for this movement pixel shift is applied to the image pair, where the mask image (image without the contrast) is shifted in horizontal and/or vertical axis compared to the contrast image. This will enhance the visibility of the vascular structure only.

This can either be done:

• Manually, the user shifts in a Region Of Interest (ROI) to have an optimal result. The . shift result in the ROI will be applied to the whole image.
• Split Screen, to allow different shifts in one subtracted pair. The image is either divided . by a horizontal or vertical line into two areas. In each of those two areas different values of shift can be applied.
• . AutoWarp, a means of enhancing a pair of subtracted images by adapting regions in the mask image to regions in the contrast image.

The provided 510(k) summary for the Philips Easy Vision Family Workstation Option, Vascular Analysis, states that "The algorithms used with the Easyvision are identical to those already used on the Integris systems, although the user interface is different." This implies that the device's acceptable performance is benchmarked against the predicate Integris systems, and the FDA's clearance is based on this substantial equivalence. However, the document does not describe specific acceptance criteria or an independent study detailing the device's performance against such criteria for the new workstation.

The 510(k) summary focuses on demonstrating that the Easy Vision Vascular Analysis package is substantially equivalent to the predicate Philips Integris systems and Siemens systems. It describes the intended use and system description, detailing the image processing and manipulation functions for Digital Subtraction Angiography (DSA) images, such as subtraction, run subtraction, landmarking, and pixel shift methods (manual, split screen, and AutoWarp).

Without a dedicated performance study for the Easy Vision workstation or explicitly stated acceptance criteria in the provided text, the specific details requested in the prompt cannot be fully extracted for this particular device. The information below reflects what can be inferred or is directly stated regarding the predicate device's performance and the basis for substantial equivalence, rather than a separate study for the Easy Vision workstation itself.

Here's an attempt to answer the questions based on the available information, noting the gaps:

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

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

• Sample Size: Not specified for a dedicated test set for the Easy Vision workstation. The claim of "identical algorithms" suggests reliance on prior validation of the Integris systems.
• Data Provenance: Not specified.

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 specified. Given the reliance on substantial equivalence, any prior validation on the Integris likely involved expert review, but details are not provided for the Easy Vision.

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

• Not specified.

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 specified. This is a workstation that provides tools for image manipulation, rather than an AI-assisted diagnostic tool in the modern sense. The "AI" (AutoWarp) mentioned is a specific image processing algorithm.

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

• While the algorithms themselves function without human interaction once initiated (e.g., AutoWarp), the document describes a "Workstation" and "Vascular Analysis package" where a user ("the user can optimize images") interacts with the system. The focus is on the tools available to the user for post-processing, implying human-in-the-loop performance is inherent to its intended use. No standalone evaluation of the algorithms separate from the workstation in a user context is described.

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

• Not specified. For a system processing DSA images, the "ground truth" for evaluating image optimization would typically involve expert assessment of image quality, clarity of vascular structures, and accuracy of anatomical representation after processing, likely against clinical or expert-interpreted images.

8. The sample size for the training set

• Not applicable as this document focuses on a 510(k) submission based on substantial equivalence, not a de novo algorithm development and training. The algorithms are stated to be "identical to those already used on the Integris systems," implying they were previously developed and validated.

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

• Not applicable for the same reasons as above.

Summary of Gaps and Inferences:

The provided 510(k) summary primarily asserts substantial equivalence to predicate devices (Philips Integris, Siemens) by stating that the algorithms used in the Easy Vision Vascular Analysis package are "identical" to those already in use on the Integris systems. This means that the regulatory acceptance is built upon the prior demonstrated safety and effectiveness of the predicate devices. The document does not detail new, independent performance studies with specific acceptance criteria, sample sizes, expert qualifications, or ground truth establishment for the Easy Vision workstation itself. Instead, the "study" proving the device meets acceptance criteria is essentially the assertion and FDA's acceptance of the "identical algorithms" claim.

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