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The Coronis 5MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, including digital mammography, for review by trained medical practitioners.
The Coronis 5MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images, including digital mammography, for review and analysis by trained medical practitioners.

The Coronis 5MP device is a digital image display system
The Coronis 5MP device consists of components to provide high resolution visualization of digital images.

This document is a 510(k) summary for the Barco Coronis 5MP Medical Flat Panel Display System, a digital image display system intended for viewing digital images, including digital mammography.

1. Table of Acceptance Criteria and the Reported Device Performance:

The provided document does not contain a table of acceptance criteria or reported device performance in the typical sense of quantitative metrics for an AI device. Instead, it describes a medical device (a display system) and seeks substantial equivalence to existing devices. The "performance" being assessed here is the device's ability to display images adequately for medical review, and the acceptance is based on meeting the regulatory requirements for such a display system.

However, based on the context of a 510(k) for a display system, the implicit acceptance criteria would revolve around the display's ability to accurately and sufficiently present medical images, particularly for mammography. This would typically involve:

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

• No specific test set or data provenance is mentioned. This document is a regulatory submission for a display device, not a study evaluating an AI algorithm's diagnostic performance on a dataset of patient images. The evaluation is focused on the characteristics of the display itself and its equivalence to other legally marketed predicate devices.

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

• Not applicable. As this is a display device, there's no "ground truth" establishment in the context of diagnosing cases. The evaluation focuses on technical specifications of the display and its suitability for medical image review.

4. Adjudication method for the test set:

• Not applicable. No test set requiring expert adjudication is mentioned for this device.

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 document pertains to a medical display system, not an AI algorithm. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant or mentioned.

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

• Not applicable. The device is a display system, not an algorithm.

7. The type of ground truth used:

• Not applicable. No ground truth in the context of diagnostic accuracy is used for evaluating this display system. The "ground truth" for a display would refer to objective technical specifications and performance against industry standards.

8. The sample size for the training set:

• Not applicable. This document does not describe the development or training of an AI algorithm.

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

• Not applicable. This document does not describe the development or training of an AI algorithm.

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The Nio 5MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners.

The Nio 5MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The Nio 5MP device is a digital image display system.

The Nio 5MP device consists of components to provide high resolution visualization of digital images.

The provided text is a 510(k) summary for a medical flat panel display system (Nio 5MP) and its FDA clearance letter. It does not contain information about acceptance criteria or a study proving that the device meets those criteria, as typically understood for AI/algorithm-based medical devices.

Instead, this document focuses on establishing substantial equivalence for a hardware display system based on its intended use and technological characteristics compared to a predicate device.

Therefore, I cannot fulfill your request for the specific information regarding acceptance criteria and a study that proves the device meets those criteria for this particular submission. The device described is a display system, not an AI/algorithm producing diagnostic outputs for which performance metrics like sensitivity, specificity, or AUC would be established through clinical studies.

The information provided confirms:

• Device Name: Nio 5MP Medical Flat Panel Display System
• Intended Use: "displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners."
• Classification: Image processing system, Class II, Product Code 90 LLZ.
• Predicate Device: Nio 5MP Medical Grayscale Display System (K040040)

Without a study described in the provided text, I cannot provide details on the following:

1. A table of acceptance criteria and the reported device performance: Not applicable.
2. Sample sized used for the test set and the data provenance: Not applicable.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method for the test set: Not applicable.
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.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used: Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

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The MGP 15 Dicom Theater device is intended to be used in displaying and viewing digital images for review by trained medical practitioners.
The MGP 15 Dicom Theater is intended to be used as a tool in displaying and viewing digital images for review and analysis by trained medical practitioners.

The MGP 15 Dicom Theater device is a digital image display system
The MGP 15 Dicom Theater consists of components to provide high resolution visualization of digital images.

This 510(k) premarket notification (K042942) for the Barco MGP 15 Dicom Theater is for a digital image display system. As such, it is not an AI/ML device and the concept of "acceptance criteria" and a "study proving the device meets the acceptance criteria" in the context of diagnostic performance metrics like sensitivity, specificity, or reader agreement is not applicable here.

This submission focuses on demonstrating substantial equivalence to a predicate device (Dicom Theater, K033153) for its function of displaying and viewing digital images for review by trained medical practitioners. The "acceptance criteria" for such a device would relate to technical specifications, image quality, and compliance with standards, rather than clinical performance metrics.

The provided documents do not contain information about:

1. A table of acceptance criteria and reported device performance: This type of table is relevant for medical devices with diagnostic or AI/ML components where performance metrics like sensitivity, specificity, accuracy, etc., are measured against predefined targets. For a display system, performance would be characterized by technical specifications like resolution, brightness, contrast, color depth, viewing angles, and compliance with DICOM standards, none of which are detailed here.
2. Sample size, data provenance, number of experts, adjudication method, MRMC study, standalone study, type of ground truth, training set size, or how ground truth was established: These details are typically found in studies evaluating the diagnostic performance of a device, especially AI/ML systems. Since the MGP 15 Dicom Theater is a display system, these types of studies are not relevant to its regulatory clearance.

In summary, based on the provided text, the MGP 15 Dicom Theater is a display system, not an AI/ML diagnostic tool. Therefore, the questions posed regarding acceptance criteria validated by clinical performance studies are not applicable to this device and no such information is present in the 510(k) summary.

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The Nio 3MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners.
The Nio 3MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The Nio 3MP device is a digital image display system
The Nio 3MP device consists of components to provide high resolution visualization of digital images.

The provided text is for a 510(k) premarket notification for a medical display system, not an AI-powered diagnostic device. Therefore, the typical acceptance criteria and study designs associated with AI performance (like sensitivity, specificity, MRMC studies, ground truth establishment with experts, etc.) are not applicable here.

The device in question, the "Nio 3MP Medical Flat Panel Display System," is a display system, and its acceptance criteria would primarily relate to image quality, display characteristics, and compliance with relevant medical display standards to ensure it's suitable for viewing digital medical images. The substantial equivalence determination is based on a comparison to a legally marketed predicate device (Nio 3MP Medical Grayscale Display System, K040041), implying that the new device meets similar performance and safety standards.

Below, I've outlined the information based on the context of a medical display system, rather than an AI diagnostic tool, as the original request's categories don't directly map to this type of device.

Acceptance Criteria and Study for Nio 3MP Medical Flat Panel Display System

Based on the provided 510(k) summary for the Barco Nio 3MP Medical Flat Panel Display System, the device is a digital image display system intended for viewing and displaying digital images (excluding digital mammography) for review by trained medical practitioners. The "study" in this context refers to the demonstration of substantial equivalence to a predicate device, as is typical for 510(k) clearances. Performance criteria for a medical display would typically include aspects like luminance, contrast ratio, uniformity, resolution, color accuracy (if applicable), and compliance with DICOM Part 14 Grayscale Standard Display Function.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly list a table of acceptance criteria or detailed performance specifications for the Nio 3MP device. However, for a medical display system, typical "acceptance criteria" for regulatory clearance would revolve around demonstrating that the device meets established industry standards for medical image display and performs comparably to its predicate.

Since this is a display system, not a diagnostic algorithm, the following points address the questions from the perspective of regulatory clearance for such a device. Many of the requested categories (e.g., sample size for test set, number of experts for ground truth, MRMC studies) are not applicable to the clearance pathway for a medical display.

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

• Not applicable in the context of a display system's 510(k) clearance. The "test set" for a display would refer to internal validation data for technical specifications (e.g., luminance, resolution, color accuracy), rather than a dataset of medical images for diagnostic performance evaluation. The 510(k) largely relies on demonstrating technical equivalence to a predicate.

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

• Not applicable. Ground truth, in the sense of expert-established diagnoses for medical images, is not relevant for the clearance of a medical display system itself. The system is a tool for viewing images, not for making an automated diagnosis or assessment.

4. Adjudication Method for the Test Set

• Not applicable. This concept relates to expert consensus on diagnostic interpretations for an algorithm's performance, which is not part of a display system's regulatory submission.

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. MRMC studies are specific to evaluating the clinical impact of an AI algorithm on human reader performance. This device is an image display, not an AI system.

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

• Not applicable. This device is a display monitor, not an algorithm. Therefore, "standalone algorithm performance" is not relevant.

7. The Type of Ground Truth Used

• Not applicable. Ground truth (expert consensus, pathology, outcomes data) is for validating diagnostic claims of an algorithm or a new diagnostic method. For a display system, the "truth" is its adherence to technical specifications and industry standards for image presentation.

8. The Sample Size for the Training Set

• Not applicable. Display systems do not have "training sets" in the AI sense. Their development involves engineering and calibration to meet specified technical and regulatory requirements.

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

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

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The Nio 2MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners.
The Nio 2MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The Nio 2MP device is a digital image display system
The Nio 2MP device consists of components to provide high resolution visualization of digital images.

The provided K042660 document is a 510(k) summary for the Barco Nio 2MP Medical Flat Panel Display System, which is an image display system. The document establishes substantial equivalence to a predicate device (Nio 2MP Medical Grayscale Display System, K040039).

This type of device (a medical image display system) does not typically undergo clinical studies with human subjects or AI performance evaluations against a ground truth in the same way an AI-powered diagnostic device would. Its performance is primarily assessed through technical specifications related to image quality and display functionality. The "acceptance criteria" for a display system are typically defined by industry standards and technical performance metrics rather than clinical accuracy metrics like sensitivity or specificity.

Therefore, many of the requested points regarding clinical study design, ground truth, expert adjudication, MRMC studies, and training set information are not applicable to this type of device based on the provided document.

Here's an analysis based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly list "acceptance criteria" in a table format with corresponding "reported device performance." However, for a medical display system, the performance is typically assessed against technical specifications to ensure it can accurately display medical images. The critical "performance" for a display device revolves around its ability to present images with sufficient resolution, luminance, contrast, and stability.

The substantial equivalence argument implies that its technical performance is comparable to the predicate device (K040039). Key performance characteristics for a display system like this would typically include:

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

• Not Applicable. This is a medical image display system, not a diagnostic algorithm. Performance is assessed through technical measurements and comparison to established display standards, not through a "test set" of medical images for diagnostic accuracy.

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

• Not Applicable. There is no "ground truth" established by experts for a display system in the context of diagnostic accuracy. Its function is to clearly and accurately display existing medical images.

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

• Not Applicable. No test set or expert adjudication for diagnostic performance.

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 device is a display system, not an AI-powered diagnostic tool. There is no AI component, and thus no MRMC study to assess the impact of AI assistance on human readers.

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

• Not Applicable. This is a hardware display system, not a standalone algorithm.

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

• Not Applicable. The "ground truth" for a display system's functionality relates to its technical specifications and proper calibration for medical image viewing, not diagnostic accuracy based on clinical findings.

8. The sample size for the training set:

• Not Applicable. This is a display system, not a machine learning algorithm requiring a training set.

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

• Not Applicable. This is a display system, not a machine learning algorithm.

Summary of the Study (Implied from the 510(k) and Device Type):

The "study" for a device like the Nio 2MP Medical Flat Panel Display System would primarily consist of technical performance verification and validation against technical specifications and existing industry standards for medical image displays. The 510(k) process relies on demonstrating substantial equivalence to a predicate device (K040039, Nio 2MP Medical Grayscale Display System). This means that Barco would have provided data to FDA demonstrating that the Nio 2MP Medical Flat Panel Display System met comparable technical specifications for image quality, resolution, luminance, contrast, uniformity, and stability as the predicate device, ensuring it is safe and effective for its intended use of displaying digital medical images (excluding mammography). This typically involves:

• Bench testing: Measuring technical parameters like luminance, contrast ratio, uniformity, color accuracy (if applicable), viewing angles, and spatial resolution.
• Compliance with standards: Demonstrating adherence to relevant standards such as DICOM Part 14 (Grayscale Standard Display Function) to ensure consistent image presentation.
• Comparison to predicate device: Providing evidence that the new device's technical specifications and performance are equivalent to the legally marketed predicate device.

The provided document does not contain details of such technical studies, as it is a summary for the 510(k) clearance, which confirms substantial equivalence rather than detailing the full technical report.

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The Coronis 5MP HD display is intended to be used in displaying and viewing digital images for review by trained medical practitioners. It is specifically designed for digital mammography applications.

The Coronis 5MP HD is a diagnostic display

The provided text is a 510(k) summary for the Barco Coronis 5MP HD display system, which is a medical image display intended for digital mammography applications.

Unfortunately, this document does not contain the detailed information necessary to answer your request regarding acceptance criteria and a study proving those criteria were met.

Here's why and what information is missing:

• No Acceptance Criteria or Performance Data: The document is primarily a regulatory submission summary, focusing on device description, intended use, and substantial equivalence to a predicate device. It explicitly states it's a "510(K) SUMMARY." This type of document, particularly from 2004, typically does not include the detailed test results or acceptance criteria used to validate the device's performance. It confirms regulatory approval based on demonstrating equivalence, not necessarily presenting a full performance study outcome.
• No Mention of a Specific Performance Study: While a manufacturer must perform testing to demonstrate safety and effectiveness for a 510(k) submission, the details of those tests, including specific acceptance criteria or an overarching study proving it met them, are not provided in this public summary. There is no mention of a clinical or technical performance study, sample sizes, ground truth establishment, or expert involvement.
• No AI Component: This device is a display monitor, not an AI or algorithm-based diagnostic tool. Therefore, questions regarding AI-specific aspects like standalone algorithm performance, AI assistance for human readers, or training sets are completely inapplicable.

In summary, the provided text describes a medical display monitor and its 510(k) regulatory clearance, but it does not contain any of the requested information about acceptance criteria or a performance study.

Therefore, I cannot populate the table or answer the specific questions based on the input text.

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The MGD 521M display is intended to be used in displaying and viewing digital images for review and analysis by trained medical practitioners. It is specifically intended for use with any digital mammography system for which the MGD 521M device meets the criteria specified by the manufacturer of the digital mammography system.

The MGD 521M device is a digital image display system, image monitor/display, and others workstation, image processing

This document describes the 510(k) summary for the Barco MGD 521M, a 5-megapixel diagnostic display intended for displaying and viewing digital mammography images. The submission asserts substantial equivalence to the Barco NV Display Systems MGD 521 (K980541).

Acceptance Criteria and Device Performance:

The document does not explicitly state quantitative acceptance criteria or a detailed "device performance" section in the traditional sense of a clinical or technical study outcome. Instead, the acceptance criteria for the Barco MGD 521M appear to be defined by its conformity to the specifications required by digital mammography system manufacturers and the functional equivalence to its predicate device.

The "reported device performance" in this context is the statement that the device is a "high resolution monitor with electronic capabilities for evaluation of high resolution digital images." The focus is on meeting the technical characteristics required for displaying such images accurately for review by trained medical practitioners.

The critical acceptance criterion is implicit: the Barco MGD 521M must meet the criteria specified by the manufacturer of the digital mammography system with which it is intended to be used. Furthermore, its performance must be "substantially equivalent" to the predicate device, the Barco NV Display Systems MGD 521 (K980541).

Study Information (Based on the provided text):

The provided 510(k) summary and FDA letter do not describe a specific clinical study or technical validation study with detailed methodology, sample sizes, or ground truth establishment relevant to performance metrics like sensitivity, specificity, or reader agreement. This type of submission (for a display monitor) typically focuses on technical specifications, safety, and substantial equivalence to a previously cleared predicate device, rather than a clinical trial assessing diagnostic accuracy of the display itself.

Therefore, many of the requested items cannot be directly answered from the given text.

1. Sample size used for the test set and the data provenance: Not applicable/Not provided. The document does not describe a test set or clinical data used to evaluate diagnostic performance. The criteria refer to the display's technical capability to show images, not to interpret them.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/Not provided. No test set requiring expert ground truth establishment is mentioned for this device.
3. Adjudication method for the test set: Not applicable/Not provided.
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: Not applicable. This device is a display monitor, not an AI-assisted diagnostic tool.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This is a hardware display device, not an algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable/Not provided.
7. The sample size for the training set: Not applicable/Not provided. This device is a display monitor and does not use a training set in the context of machine learning.
8. How the ground truth for the training set was established: Not applicable/Not provided.

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The MIVD 1218 18 Inch Grayscale Display Module is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The MIVD 1218 is a diagnostic display. The MIVD 1218 device is a high resolution monitor with electronic capabilities for evaluation of high resolution medical images.

This document describes the 510(k) summary for the Barco MIVD 1218, an 18-inch grayscale display module. It's important to note that this is a display device, not an AI or image processing algorithm in the modern sense. Therefore, many of the typical AI/ML acceptance criteria and study components will not apply.

Based on the provided text, the device is a medical display, and the "study" demonstrating its performance would primarily involve technical specifications and conformance to industry standards for medical displays, rather than a clinical trial with patient data or expert read comparisons.

Here's an attempt to address your points based on the available information, noting where information is not present or not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly detail a table of acceptance criteria or a "reported device performance" in the context of a clinical study assessing diagnostic accuracy. For a display device like this, acceptance criteria would typically revolve around technical specifications such as resolution, luminance, contrast ratio, uniformity, viewing angle, and compliance with standards like DICOM Part 14.

The document states:

• Proprietary Name: MIVD 1218
• Device Description: The MIVD 1218 is a diagnostic display
• Technological Characteristics: The MIVD 1218 device is a high-resolution monitor with electronic capabilities for evaluation of high-resolution medical images.

Without access to the full 510(k) submission, we cannot provide specific numerical values for these technical performance metrics. The core "performance" for a display is that it accurately and consistently presents medical images within specified parameters.

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

This information is not applicable and not provided as the device is a display monitor, not an algorithm that processes medical images from a test set of patient data. The "test" for this device would involve engineering verification and validation against technical specifications and performance standards, likely using test patterns, calibrated measurement devices, and internal quality control procedures.

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

This information is not applicable and not provided. As a display device, there's no "ground truth" derived from patient cases in the way there would be for an AI algorithm. Ground truth for a display refers to its technical specifications and performance against industry standards, typically verified by engineers and quality control personnel.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. Adjudication methods like 2+1 or 3+1 are used for resolving discrepancies in expert interpretations of clinical cases, which is not relevant for a display device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size.

This information is not applicable and not provided. An MRMC study assesses the diagnostic performance of human readers, typically with and without the assistance of an AI tool, across multiple cases. The Barco MIVD 1218 is a display device, not an AI tool, so such a study would not apply. Its effectiveness is in faithfully reproducing images, which can indirectly impact reader performance but isn't measured in this way.

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

This information is not applicable and not provided. This refers to the performance of an AI algorithm independent of human interaction. The MIVD 1218 is a hardware device (a monitor) and does not perform algorithmic analysis.

7. The Type of Ground Truth Used

This information is not applicable in the clinical sense. For a display, the "ground truth" for its performance evaluation would be its adherence to defined technical specifications and industry standards (e.g., DICOM Part 14 for grayscale display function, luminance uniformity, contrast ratio). This would be established through a combination of engineering design specifications, calibrated measurement instruments, and standardized test patterns.

8. The Sample Size for the Training Set

This information is not applicable and not provided. A training set is used for machine learning algorithms. The MIVD 1218 is a hardware device and does not involve machine learning.

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

This information is not applicable and not provided. As there is no training set for a hardware display device, there is no ground truth to establish for it.

In summary: The provided document is a 510(k) summary for a medical display. The clearance process for such a device focuses on demonstrating substantial equivalence to a predicate device based on technical specifications and adherence to relevant standards, rather than clinical performance studies involving patient data and expert diagnoses in the way AI/ML devices are evaluated.

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The MFGD 1318 18 Inch 1 Megapixel Grayscale LCD Display is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The MFGD 1318 is a diagnostic display. The MFGD 1318 device is a high resolution monitor with electronic capabilities for evaluation of high resolution medical images.

This 510(k) premarket notification (K033005) is for a medical display device, not an AI/ML algorithm. Therefore, many of the requested categories related to AI/ML software performance (like sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable.

The submission focuses on establishing substantial equivalence to a predicate device (Coronis 1MP Medical Flat Panel Display System, K023340) based on technological characteristics and intended use. The "acceptance criteria" here refer to the performance specifications of the display hardware, and "study" refers to tests and comparisons demonstrating these specifications are met and are equivalent to the predicate.

Here's the information that can be extracted, and where the requested AI/ML specific information is not applicable (N/A):

1. Table of acceptance criteria and the reported device performance

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

   • Sample size for test set: N/A (as this is a hardware device, not an AI/ML algorithm evaluated on a dataset of medical images).
   • Data provenance: N/A

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

   • N/A (no ground truth established in the context of an AI/ML algorithm's performance on medical images).

4. Adjudication method for the test set

   • N/A

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

   • N/A (This is not an AI-assisted device). The evaluation here is about the technical performance of a display, not its impact on human reader performance with AI.

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

   • N/A (This is a display device, not a standalone algorithm).

7. The type of ground truth used

   • N/A. The "ground truth" for a display device would relate to its physical characteristics meeting industry standards and safety regulations, not a medical diagnosis dataset.

8. The sample size for the training set

   • N/A.

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

   • N/A.

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The MGD 2621P Medical Grayscale Display is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The MGD 2621P is a diagnostic display

The provided text is a 510(k) summary for the Barco MGD 2621P Medical Grayscale Display. This document does not contain the information requested in points 1-9 regarding acceptance criteria and a study proving the device meets these criteria.

The 510(k) summary focuses on general device information, intended use, and substantial equivalence to a predicate device (Barco MGD 221 2 Megapixel Diagnostic Display - K000293). It describes the device's technical characteristics as a high-resolution monitor with electronic capabilities for evaluating high-resolution medical images.

The letter from the FDA confirms market clearance based on substantial equivalence but does not delve into specific performance studies or acceptance criteria for the display itself. It mainly cites relevant regulations and guidelines for the manufacturer.

Therefore, I cannot provide the requested table or answer questions 1-9 based on the input text. The document is essentially a regulatory clearance notice, not a detailed performance study report.

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