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This product is intended for use in clinical radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

RadiForce GX570 is a monochrome LCD monitor for viewing medical images including those of mammography. The monochrome panel employs in-plane switching (IPS) technology allowing wide viewing angles and the matrix size (or resolution) is 2,048 x 2,560 pixels (5MP) with a pixel pitch of 0.165 mm.

Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF), a specific luminance range and a specific color temperature, are stored in lookup tables within the monitor, the tone curve is e.g. DICOM compliant regardless of the display controller used. This helps ensure tone curves even if a display controller or workstation must be replaced or serviced.

The Digital Uniformity Equalizer function compensates luminance non-uniformity, one of the inherent characteristics of LCD panel modules, to the levels required by various QC standards and guidelines.

The Sharpness Recovery function compensates sharpness degradation caused by the inherent characteristics of LCD panel modules (A user selectable).

There are two model variations, GX570 and GX570-AR. The difference of the two variations is the surface treatment of the GX570 is Anti-Glare (AG) treatment and that of the GX570-AR is Anti-Reflection (AR) coating.

Two GX570 monitors mounted on a single stand configuration is available identified by with "MD" like GX570-MD and GX570-AR-MD.

RadiCS is application software to be installed in each workstation offering worry-free quality control of diagnostic monitors including the RadiForce GX570 based on the QC standards and guidelines and is capable of quantitative tests and visual tests defined by them. The RadiCS is included in this 510(k) submission as an accessory to the RadiForce GX570.

RadiCS is of Basic Documentation Level and that it's being used unchanged from the predicate software. RadiCS supports the functions of the monitor RadiForce GX570 and it's not a medical imaging software.

The provided FDA 510(k) clearance letter and summary are for a medical display monitor (RadiForce GX570), not an AI device or a diagnostic algorithm. Therefore, the information requested regarding acceptance criteria and a study proving an AI device meets those criteria cannot be extracted from this document.

The document discusses the technical performance of a display monitor, such as:

• Spatial resolution (MTF)
• Pixel defects
• Luminance and chromaticity (including DICOM GSDF conformance)
• Temporal response
• Noise (NPS)
• Display reflections
• Small-spot contrast ratio

These are physical and optical performance characteristics of a display hardware, not the diagnostic performance of a software algorithm.

Therefore, I cannot populate the requested table or answer the questions related to AI device performance, sample sizes for test/training sets, expert adjudication, MRMC studies, or ground truth establishment, as this information is not relevant to a medical display monitor clearance.

The document does state that the device is intended for use with "clinical radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners." However, the studies described are bench tests to assure the display hardware meets performance standards for displaying these images, not for interpreting them with AI.

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This product is intended for use in clinical radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

RadiForce RX570 is a color LCD monitor for viewing medical images including those of mammography. The color panel employs in-plane switching (IPS) technology allowing wide viewing angles and the matrix size (or resolution) is 2,048 x 2,560 pixels (5MP) with a pixel pitch of 0.165 mm. Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF), a specific luminance range and a specific color temperature, are stored in lookup tables within the monitor, the tone curve is e.g. DICOM compliant regardless of the display controller used. There are two model variations, RX570 and RX570-AR. The difference of the two variations is the surface treatment of the display screens; the surface treatment of the RX570 is Anti-Glare (AG) treatment and that of the RX570-AR is Anti-Reflection (AR) coating. Two RX570 monitors mounted on a single stand configuration is available identified by with "MD" like RX570-MD and RX570-AR-MD. RadiCS is application software to be installed in each workstation offering worry-free quality control of the diagnostic monitors including the RadiForce RX570 based on the QC standards and guidelines and is capable of quantitative tests and visual tests defined by them. The RadiCS and its subset, RadiCS LE, are included in this 510(k) submission as an accessory to the RadiForce RX570. RadiCS is Basic Documentation level and that it's being used unchanged from the predicate software. RadiCS supports the functions of the monitor RadiForce RX70 and it's not a medical imaging software.

The provided document describes the EIZO RadiForce RX570; RadiForce RX570-AR medical display monitor and its substantial equivalence to predicate devices, the RadiForce RX560 and RadiForce GX540. It evaluates the device based on performance testing against predefined criteria.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document states that "The bench tests below were performed on the RadiForce RX570 following the instructions in 'Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology' issued on September 28, 2022" and that "the display characteristics of the RadiForce RX570 meet the pre-defined criteria when criteria are set." However, it does not provide a specific table directly listing the acceptance criteria values alongside the measured device performance values.

Instead, it lists the types of measurements performed and provides a general statement about meeting predetermined criteria and equivalence to predicate devices. For example, for DICOM GSDF conformance, it states "Verification of the conformance to DICOM GSDF as specified in Assessment of Display Performance for Medical Imaging Systems by AAPM Task Group 18 (TG18 guideline)," implying that the device met the DICOM GSDF conformance criteria.

Therefore, a table cannot be fully generated with specific numeric acceptance criteria and performance data from the provided text. The document acts as a high-level summary of the testing performed and the conclusion reached.

For a comprehensive table, access to the full test report would be needed. Based on the general statements, the interpretation is that the device did meet the criteria for each test:

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

The document does not explicitly state a "sample size" for the test set in terms of number of devices or datasets. The testing appears to have been performed on the RadiForce RX570 device itself to assess its physical and technical characteristics.

The testing methods are described as "bench tests" performed "following the instructions in 'Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology'." This indicates the data provenance is from prospective bench testing conducted in a lab environment. There is no information about the country of origin of the data beyond the manufacturer being EIZO Corporation of Japan.

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

This information is not applicable to this submission. The device is a medical display monitor, not an AI or diagnostic software that requires human expert review to establish ground truth for performance evaluation in medical image interpretation. The "ground truth" for this device's performance is established by objective physical measurements based on industry standards and FDA guidance.

4. Adjudication Method for the Test Set

This information is not applicable. Since the performance evaluation relies on objective physical measurements and conformance to technical standards (e.g., DICOM GSDF, TG18 guidelines), there is no need for an adjudication method involving multiple experts.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. This type of study is typically used for diagnostic AI systems or CADe/CADx devices to evaluate their impact on human reader performance. The RadiForce RX570 is a display monitor, and its performance is evaluated by its technical specifications and adherence to display standards, not by its effect on human readers' diagnostic accuracy.

6. Standalone Performance

A standalone performance evaluation was done. The entire Section 7, "Performance Testing," describes the standalone (algorithm-only, or in this case, device-only) performance testing of the RadiForce RX570. The device's characteristics (e.g., resolution, luminance, DICOM conformance) were measured directly against established technical guidelines and standards.

7. Type of Ground Truth Used

The ground truth used for this device's evaluation is primarily based on technical standards, physical measurements, and industry guidelines. Specifically, the document mentions:

• "Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology"
• "Assessment of Display Performance for Medical Imaging Systems by AAPM Task Group 18 (TG18 guideline)"
• "DICOM GSDF" (Grayscale Standard Display Function)

8. Sample Size for the Training Set

This information is not applicable. The RadiForce RX570 is a physical display device, not an AI algorithm that undergoes training.

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

This information is not applicable for the same reason as above; there is no training set for a display monitor.

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C310S, C316S and C616W are indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The displays are not intended for mammography.

G310S and G316S are intended to be used in displaying digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. The devices are not specified for digital mammography systems.

3MP LCD Monitors C310S, G310S, C316S, G316S are 21.3-inch TFT LCD monitors, which are specifically designed to provide the high definition image output for general radiography. These products have been strictly calibrated so that they can meet DICOM Part 3.14 and other standards. They use the latest generation of LED backlight panel, supporting resolution 1536 x 2048. The built-in brightness stabilization control circuit makes sure the brightness of these monitors is stable, so these products meet the demand of high precision medical imaging. The anti-glare screen can prevent display from reflection under highlight conditions, make the image and display clearer. 6MP Color LCD Monitor C616W is a 30-inch TFT LCD monitor, which is specifically designed to provide the high definition image output for general radiography.

This product has been strictly calibrated so that they can meet DICOM Part 3.14 and other standards. They use the latest generation of LED backlight panel, supporting resolution 3280 x 2080. The built-in brightness stabilization control circuit makes sure the brightness of these monitors is stable, so this product meets the demand of high precision medical imaging. The anti-glare screen can prevent display from reflection under highlight conditions, make the image and display clearer.

C310S and C316S have the same color LCD panel and similar functionality. For C310S and C316S, the difference is the main board and design principle.

G310S and G316S have the same monochrome LCD panel and similar functionality. For G310S and G316S, the difference is the main board and design principle.

C310S and G310S have the same main board and design principle.

C316S and G316S have the same main board and design principle.

The provided text describes a 510(k) summary for several LCD medical displays (C310S, G310S, C316S, G316S, C616W) which are claimed to be substantially equivalent to a previously cleared device (K240310). The information does not detail an AI-powered device or a study involving human readers or comparative effectiveness for AI assistance. Instead, it focuses on the technical specifications and performance of the LCD monitors.

Therefore, the following information is extracted and parts that are not relevant to an AI/ML powered device or are not provided in the text are explicitly stated as such.

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

The acceptance criteria are implied by the "Description" column, indicating what was measured, and the "Test result" column, which uniformly states "PASS". This suggests that the measured performance met the predetermined criteria for each test.

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. The tests performed are physical laboratory tests on the display embedded software using DBI Calibration Feedback System on the monitors, not a test on a test set of medical cases.

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 provided as the device is an LCD monitor, not an AI / image analysis software requiring expert annotation for ground truth. The tests are technical performance evaluations of the display.

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

This information is not provided as it's not relevant for the type of device being described (an LCD monitor).

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The device is an LCD monitor, not an AI or AI-assisted diagnostic tool.

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

No, a standalone performance study was not done as this device is an LCD monitor, which is a display hardware, not an algorithm.

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

The ground truth for the performance tests of the LCD monitors is based on pre-determined technical criteria and industry standards (e.g., DICOM Part 3.14, AAPM Task Group 18 guideline, manufacturer's typical data). This is not a "ground truth" derived from medical diagnosis but from established engineering and display performance metrics.

8. The sample size for the training set

This information is not applicable as the device is an LCD monitor and does not involve AI/ML models that require a training set.

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

This information is not applicable as the device is an LCD monitor and does not involve AI/ML models that require a training set and ground truth generation.

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The display is intended to be used in displaying and viewing digital images, including standard and multiframe digital mammography, for review, analysis and diagnosis by trained medical practitioners. It is especially designed for breast tomosynthesis (3D mammography) applications, breast MRI and breast US. It is especially designed for CT and ultrasound including vascular and gynaecological US.

The Coronis OneLook® (MDMC-32133) is a medical computer display designed for general radiology, mammography and tomosynthesis applications. The device can also be used for home reading in radiology.

The display is a high-resolution LCD monitor with improved technical chat are important for accurate medical image review: high luminance, good luminance ratio and luminance ratio and luminance stability. The medical display comes with special image-enhancing technologies to ensure consistent brightne of the display, noise-free images (=good luminance uniformity), ergonomic reading and automated compliance with DICOM and other medical image quality standards and guidelines. These technologies help the radiologist to make a swift and accurate diagnosis.

The displays can be used optionally with the downloadable QAWeb Enterprise software, listed under D332294 as a class 1 device with product code LHO. QAWeb Enterprise is a calibration software that is intended as a quality assurance software for the displays. QAWeb Enterprise software helps to keep the display DICOM compliant.

The display can be used optionally with the downloadable Intuitive Workflow Tools, cleared in K191845 as a class 2 device with product code PGY. The Intuitive Workflow Tools are accessories for image enhancement on diagnostic displays:

• SpotView: The Barco SpotView display feature allows focusing on a region of interest in an image by boosting the display's backlight such that the maximum luminance in provided inside the region of interest. SpotView also enables focused observation during reading by dimming images outside the region of increasing the contrast in this region. Also magnification and inversion of pixels are possible with SpotView.

-AAM – Application Appearance Manager: This workflow tool allows you to set the luminance as well as the color space for each application that is on the workstation. There are often multiple windows open on a screen, but not all of them need the hightness

These applications are addressed by the general term 'Intuitive Workflow Tools'. The integration of the Intuitive Workflow Tools with the displays have been de-risked, verified and validated to ensure that they do not affect the safety and effectiveness of the displays.

The display can be used with or without the Barco MXRT display controller boards. The display controller board is installed in a PACS workstation computer, connected to the display can optionally be used with a touchpad, which is a controlling device (e.g. like a mouse or trackball) that makes it easier to work with diagnostic images and to use the IWTs.

The provided text describes a 510(k) premarket notification for a medical display device, Coronis OneLook (MDMC-32133). The document primarily focuses on demonstrating substantial equivalence to a predicate device (MDMC-12133, Coronis Uniti) through bench testing of technical characteristics.

Here is an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document outlines a series of performance bench tests conducted on the MDMC-32133 in comparison to the MDMC-12133, referencing the "Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology" (2022). The text generally states that the MDMC-32133 has "similar characteristics" and "did not reveal new issues of safety and performance." However, it does not provide specific numerical acceptance criteria or detailed quantitative reported performance values for each characteristic. Instead, it concludes equivalence based on these test outcomes.

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

The document describes "performance bench tests" that were performed. This implies testing on physical units of the device. It does not specify the sample size (number of devices tested) for these bench tests. The data provenance is not explicitly mentioned as retrospective or prospective in the context of data used for testing, but rather refers to the device characteristics under comparison.

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

This information is not applicable as the study described is purely a technical bench test comparison of display performance, not a study involving human interpretation of medical images or establishment of ground truth for medical diagnoses.

4. Adjudication Method for the Test Set:

This information is not applicable for the reasons stated in point 3.

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

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No animal testing or clinical testing has been performed." The study focuses on technical characteristics of the display itself, not on the effectiveness of human readers using the display for diagnosis.

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

This is not applicable in the context of an algorithm's performance, as the device is a medical display, not an AI algorithm. The performance evaluation is for the display's technical specifications.

7. The Type of Ground Truth Used:

The "ground truth" for this type of test is typically established by industry standards and specifications for display performance, as well as the performance of the legally marketed predicate device (MDMC-12133). The tests are designed to measure intrinsic physical properties of the display hardware against these established benchmarks.

8. The Sample Size for the Training Set:

This information is not applicable as the device is a display hardware, not an AI model that requires a training set.

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

This information is not applicable for the reasons stated in point 8.

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CL-S301 is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners or certified personnel. It is not meant to be used in digital mammography.

21.3 inch Color LCD Monitor
1536 x 2048 (portrait)
High-luminance color LCD panel, which has wide view angle, is used for this product. It is designed for medical image display. Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable. Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor. Luminance and the color mura correction functions will help achieve uniformity on the whole screen.

The provided FDA 510(k) summary is for a medical monitor (3MP Color LCD Monitor CL-S301), not an AI device. Therefore, much of the requested information regarding AI device acceptance criteria, study design, and performance metrics (e.g., sample sizes for test/training sets, ground truth establishment, expert adjudication, MRMC studies) is not applicable or cannot be extracted from this document, as it pertains to the performance evaluation of a display hardware.

However, I can extract the acceptance criteria and performance data related to the physical characteristics of the monitor, as well as general information about its intended use and comparison to a predicate device.

Here's the available information based on the provided text:

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

The document presents performance "test items in the guidance" which serve as acceptance criteria for a medical display monitor. The "test method(s)" column describes how these criteria are verified. The conclusion states that "The results of the performance testing and the verification demonstrate that the subject device is substantially equivalent to the currently marketed predicate device." This implicitly means the device met the acceptance criteria for each test.

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

This information is not applicable to a physical display device. The tests are performed on the device itself, not on
a "data set" in the context of an AI algorithm. The device manufacturer is JVCKENWOOD Corporation, located in Japan.

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 is not applicable. The "ground truth" for a monitor's performance is based on physical measurements and adherence to technical standards (e.g., ISO, IDMS, AAPM-TG directives), not expert interpretation of medical images.

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

This is not applicable. Adjudication methods are relevant for evaluating expert performance on diagnostic tasks, not for physical device testing.

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

This is not applicable. An MRMC study is used to evaluate the diagnostic performance of a system (often AI-assisted) with human readers. This document describes a monitor, which is a display hardware, not a diagnostic AI system.

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

This is not applicable as the device is a display monitor, not an algorithm.

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

The "ground truth" for the monitor's performance is defined by adherence to established technical standards and measurement protocols (e.g., ISO 13406-2, IDMS 1.03, AAPM-TG18/196, IEC 62563-1).

8. The sample size for the training set

This is not applicable. The device is a physical monitor, not an AI algorithm that requires a training set.

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

This is not applicable for the same reason as point 8.

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This Product is indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The display is not intended for mammography.

RadiForce RX670 is a color LCD monitor for viewing medical images other than those of mammography. The color panel employs in-plane switching (IPS) technology allowing wide viewing angles and the matrix size (or resolution) is 3,280 x 2,048 pixels (6MP) with a pixel pitch of 0.1986 mm.

Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF), a specific luminance range and a specific color temperature, are stored in lookup tables within the monitor, the tone curve is e.g. DICOM compliant regardless of the display controller used. This helps ensure tone curves even if a display controller or workstation must be replaced or serviced.

There are two model variations. RX670 and RX670-AR. The difference of the two variations is the surface treatment of the display screens; the surface treatment of the RX670 is Anti-Glare (AG) treatment and that of the RX670-AR is Anti-Reflection (AR) coating.

RadiCS is application software to be installed in each workstation offering worry-free quality control of diagnostic monitors including the RadiForce RX670 based on the QC standards and guidelines and is capable of quantitative tests and visual tests defined by them. The RadiCS is included in this 510(k) submission as an accessory to the RadiForce RX670.

RadiCS is Basic Documentation level and that it's being used unchanged from the predicate software. RadiCS supports the functions of the monitor RadiForce RX670 and it's not a medical imaging software.

The provided document, K241441, is a 510(k) premarket notification for the RadiForce RX670 and RadiForce RX670-AR medical display monitors. The document demonstrates substantial equivalence to predicate devices (RadiForce RX660, RX660-AR, and RadiForce RS340) for displaying radiological images for review, analysis, and diagnosis, excluding mammography.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document refers to "pre-defined criteria" but does not explicitly list the numerical acceptance criteria for each test. Instead, it states that the device "meet[s] the pre-defined criteria when criteria are set" and that its display characteristics are "equivalent to those of the predicate device."

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

• Sample Size: The document does not explicitly state the number of RadiForce RX670 units tested. It refers to "the RadiForce RX670" (singular), implying that one or more units of the product were subjected to the specified bench tests.
• Data Provenance: The testing was "bench tests," conducted by the manufacturer, EIZO Corporation, in Japan. The data is thus prospective, originating from the manufacturer's internal testing.

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

This information is not applicable as the study involved bench tests of a medical display device, not a study evaluating human interpretation of images or an AI algorithm's diagnostic performance against a ground truth.

4. Adjudication method for the test set:

This information is not applicable as the study involved bench tests of a medical display device, not a study requiring adjudication of expert opinions or diagnostic outcomes.

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, an MRMC comparative effectiveness study was not done. This document is for a medical display device, not an AI-powered diagnostic algorithm.

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

No, a standalone algorithm performance study was not done. This document is for a medical display device, which is hardware, and its associated quality control software (RadiCS). It does not involve a diagnostic algorithm.

7. The type of ground truth used:

This information is not applicable in the traditional sense of diagnostic accuracy studies. For the bench tests, the "ground truth" would be the engineering specifications and established standards (e.g., DICOM GSDF, AAPM TG18 guideline) against which the display's performance characteristics were measured.

8. The sample size for the training set:

This information is not applicable. The device is a display monitor, not an AI algorithm that requires a training set. The RadiCS software mentioned is for quality control and "is not a medical imaging software" and "it's being used unchanged from the predicate software," implying no new algorithm development or training.

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

This information is not applicable for the reasons stated in point 8.

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UMD5-21B01 is indicated for use in displaying radiological images (including full-field digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

UMD5-21B01 is a 5 mega pixels 21.3" color LCD display for viewing medical images including mammography and digital breast tomosynthesis. The resolution of the display is 2,048 x 2,560 pixels (5MP) with a pixel pitch of 0.165 mm and wide angle LCD technology (IPS) support Dual-link DVI and Displayport signals from workstation or personal computer.

Since factory calibrated 3 display modes, each of which is characterized by a specific curve (including DICOM GSDF), a specific luminance range and a pre-defined color temperature, are stored in Lookup Table (LUT) within the display, the tone curve is e.g. DICOM compliant regardless of the display controller used.

AcuCal, a general name for the calibration and quality control functions of UMD-series product, includes corresponding firmware (AcuCal-Pro) and management application of PC (AcuCal Manage). AcuCal-Pro is the controlling firmware of this LCD display. AcuCal-Pro can perform the luminance calibration without PC or workstation and also includes the quality control scheme to make sure display quality, especially DICOM conformance. AcuCal Manage is a PC application for managing a group of displays.

The provided text is a 510(k) summary for a medical display device (ACULA Technology Corp.'s UMD5-21B01). This document describes the device, its intended use, and compares it to a predicate device to establish substantial equivalence.

However, the nature of this document (a 510(k) summary for a display device) means that it does not include the type of detailed clinical study information typically associated with AI/ML-based medical devices or devices that generate diagnostic assessments needing complex acceptance criteria and ground truth establishment.

Instead, the performance data section focuses on bench tests related to the display's technical characteristics, such as spatial resolution, luminance, contrast, and DICOM conformance. These tests are conducted to ensure the display accurately presents medical images as per industry standards (like TG18 guidelines), which is a different kind of "acceptance criteria" than what would be applied to an AI algorithm predicting disease.

Therefore, many of the specific questions you asked (e.g., sample size for test set, number of experts for ground truth, MRMC studies, standalone performance of an algorithm, training set size) are not applicable to this device and the information provided in this 510(k) summary.

I will fill in the table and address the relevant points based on the provided text, indicating "Not Applicable" or "Not Provided" where the information does not exist for this type of device and submission.

Acceptance Criteria and Study Details for UMD5-21B01 Display Device

1. Table of Acceptance Criteria and Reported Device Performance

As this is a display device, the acceptance criteria relate to its imaging performance characteristics rather than diagnostic accuracy measures (like sensitivity/specificity for an AI algorithm). The document refers to "bench tests" and conformance to "TG18 guideline" and "DICOM GSDF." The table below summarizes the types of measurements performed, which serve as the "acceptance criteria" and the reported "performance" is that the device meets these standards (implicitly, as it gained clearance).

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

• Sample Size: Not applicable in the context of image data for diagnostic performance. The "test set" here refers to the device itself undergoing various physical and photometric measurements. Typically, a single production unit or a small number of units are tested to confirm design specifications.
• Data Provenance: Not applicable. The tests are bench tests of the display hardware and its performance, not studies on image data.

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

• Not applicable. Ground truth as typically defined for AI algorithms (e.g., disease presence) is not established for a display device. The "ground truth" for these tests are objective physical measurements against established industry standards (like TG18 guidelines).

4. Adjudication method for the test set

• Not applicable. As no human interpretation of images for ground truth labeling is involved, there is no need for 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

• Not applicable. This is a display device, not an AI-assisted diagnostic tool. No MRMC study was performed or needed.

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

• Not applicable. This is a display device, not a standalone algorithm. The "performance" is its ability to accurately display images, which is assessed through bench testing.

7. The type of ground truth used

• Not applicable in the sense of clinical ground truth (e.g., pathology, outcomes). The "ground truth" for the device's technical performance is defined by established industry standards, measurement protocols (e.g., AAPM TG18), and physical metrology.

8. The sample size for the training set

• Not applicable. This is a display device, not an AI system that undergoes training.

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

• Not applicable.

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The 3MP Color LCD Display UMD3-21B01) is indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The display is not intended for mammography.

UMD3-21B01 (MD3-21B01) is a 3 mega pixels 21.3" color LCD display for viewing medical images, not including mammography. The resolution of the display is 1,536 x 2,048 pixels (3MP) with a pixel pitch of 0.2115 mm and wide angle LCD technology (IPS) support Dual-link DVI and Displayport signals from workstation or personal computer.

Since factory calibrated 3 display modes, each of which is characterized by a specific curve (including DICOM GSDF), a specific luminance range and a pre-defined color temperature, are stored in Lookup Table (LUT) within the display, the tone curve is e.g. DICOM compliant regardless of the display controller used.

AcuCal, a general name for the calibration and quality control functions of MD-series product, includes corresponding firmware (AcuCal-Pro) and management application of PC (AcuCal Manage). AcuCal-Pro is the controlling firmware of this LCD display. AcuCal-Pro can perform the luminance calibration without PC or workstation and also includes the quality control scheme to make sure display quality, especially DICOM conformance. AcuCal Mange is a PC application for managing a group of displays.

The provided text describes a 510(k) submission for a medical display device, the 21.3" 3MP Color LCD Display UMD3-21B01 (MD3-21B01). This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving that an AI/ML algorithm meets acceptance criteria through a specific study design (e.g., MRMC).

The document is about a display device, not an AI/ML algorithm. Therefore, many of the requested criteria (e.g., sample size for test/training sets, number of experts for ground truth, adjudication method, MRMC study, standalone algorithm performance) are not applicable to the type of device described.

However, I can extract information related to the performance data and the "acceptance criteria" as they apply to a display device being cleared for diagnostic imaging.

Here's an interpretation of the performance data that can be framed as "acceptance criteria" for a medical display device, based on the provided text:

Acceptance Criteria and Reported Device Performance for a Medical Display Device

Since the device is a medical display, the acceptance criteria relate to its image quality and conformance to standards relevant for medical imaging. The performance data section describes tests performed to ensure the display meets these expectations.

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

The document doesn't explicitly list "acceptance criteria" as pass/fail thresholds for each test, but rather describes the measurements taken and implies that the device performed adequately to demonstrate substantial equivalence. The predicate device's specifications act as an implicit benchmark for many of these performance characteristics.

2. Sample size used for the test set and the data provenance
The document does not detail a "test set" in the context of an AI/ML algorithm. Instead, it describes performance tests conducted on the physical display device itself. The provenance of this performance "data" would be the manufacturing site (Taiwan, where ACULA Technology Corp. is located) and the testing procedures applied to the specific model (UMD3-21B01/MD3-21B01). It is device performance testing, not clinical data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This is not applicable as the submission is for a medical display, not an AI/ML diagnostic tool that requires ground truth established by experts. The "ground truth" for a display is its physical performance characteristics measured against industry standards (e.g., DICOM GSDF, AAPM TG18).

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This is for an AI/ML algorithm's performance on a dataset, not a display's physical performance verification.

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 is not an AI/ML device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for the display's performance is established by physical measurement standards and industry guidelines, such as the DICOM GSDF (Grayscale Standard Display Function) and AAPM Task Group 18 (TG18) guidelines. These are objective, quantifiable standards for display performance in medical imaging.

8. The sample size for the training set
Not applicable. The device is a display, not an AI/ML algorithm that requires a training set.

9. How the ground truth for the training set was established
Not applicable.

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C310S, C316S and C616W are indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The displays are not intended for mammography.

G310S and G316S are intended to be used in displaying digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. The devices are not specified for digital mammography systems.

3MP LCD Monitors C310S, G310S, C316S, G316S are 21.3-inch TFT LCD monitors, which are specifically designed to provide the high definition image output for general radiography.

These products have been strictly calibrated so that they can meet DICOM Part 3.14 and other standards. They use the latest generation of LED backlight panel, supporting resolution 1536 x 2048. The built-in brightness stabilization control circuit makes sure the brightness of these monitors is stable, so these products meet the demand of high precision medical imaging. The anti-glare screen can prevent display from reflection under highlight conditions, make the image and display clearer.

6MP Color LCD Monitor C616W is a 30-inch TFT LCD monitor, which is specifically designed to provide the high definition image output for general radiography. This product has been strictly calibrated so that they can meet DICOM Part 3.14 and other standards. They use the latest generation of LED backlight panel, supporting resolution 3280 x 2080. The built-in brightness stabilization control circuit makes sure the brightness of these monitors is stable, so this product meets the demand of high precision medical imaging. The anti-glare screen can prevent display from reflection under highlight conditions, make the image and display clearer.

C310S and C316S have the same color LCD panel and similar functionality. For C310S and C316S, the difference is the main board and design principle. G310S and G316S have the same monochrome LCD panel and similar functionality. For G310S and G316S, the difference is the main board and design principle. C310S and G310S have the same main board and design principle. C316S and G316S have the same main board and design principle.

The provided text describes K240310 for Shenzhen Beacon Display Technology Co., Ltd.'s LCD Monitors (C310S, G310S, C316S, G316S, C616W) but does not contain acceptance criteria or study details regarding AI/algorithm performance.

The submission focuses on establishing substantial equivalence to predicate devices through technical comparisons and bench testing of display characteristics. There is no mention of an AI/algorithm component requiring performance studies with human readers, ground truth establishment, or clinical evaluations.

Therefore, I cannot provide the requested information about acceptance criteria for an AI device or a study proving it meets them, as the provided text pertains to LCD monitors themselves, not an AI component.

The document does contain the following relevant information regarding the LCD monitors' performance:

The performance testing was done via bench tests and focused on the display characteristics of the monitors.

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" in a pass/fail form with numerical targets. Instead, it states that the devices (C310S, G310S, C316S, G316S, C616W) were tested to verify "display characteristics equivalent to those of the predicate devices" and that they "meet DICOM Part 3.14 and other standards." The reported performance is implicitly shown through the comparison tables (Tables 1, 2, and 3) by comparing the proposed devices with their respective predicate devices.

Here's an example of some performance characteristics from the provided tables. For a full list, please refer to the "General Comparison" tables in the original document.

Example Table of Reported Device Performance (Partial - C310S/C316S Color LCD Monitors):

Note: The "Explanation of Differences" column in the original tables addresses specific instances where the proposed device's performance differs numerically from the predicate but is considered substantially equivalent (e.g., "Different Panel" or "Different design scheme" for brightness/contrast differences, which are then justified by passing TG18 guideline tests).

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

• Sample Size: Not specified. The document states "the bench tests were performed on C310S, G310S, C316S, G316S, C616W," implying one or more units of each model. It does not mention a large sample size of images or cases, as this is a device for displaying images, not an image analysis algorithm.
• Data Provenance: Not applicable in the context of image data. The testing was conducted on the physical monitors themselves, measuring their optical characteristics.

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

• Not applicable. The ground truth for evaluating display performance is based on established technical standards (e.g., DICOM Part 3.14, AAPM TG18 guideline) and objective measurements, not subjective expert interpretation of medical images on the device.

4. Adjudication method for the test set:

• Not applicable. Performance was assessed against objective technical specifications and standards using bench tests, not through human adjudication of diagnostic outcomes.

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. This is not an AI device. The submission does not describe an MRMC study.

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

• No. This is not an AI algorithm.

7. The type of ground truth used:

• Technical Standards and Objective Measurements: The "ground truth" for the display devices' performance is their conformance to established industry standards like DICOM Part 3.14 and the AAPM Task Group 18 (TG18) guideline for assessment of display performance. This includes measurements of spatial resolution (MTF), pixel defects, luminance characteristics (maximum, minimum, achievable, recommended), DICOM GSDF conformance, and color tracking.

8. The sample size for the training set:

• Not applicable. This is not an AI/machine learning device that requires a training set.

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

• Not applicable. No training set was used.

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This Medical Monitor is indicated for use in displaying radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

The Medical monitor is intended to provide high resolution color and grayscale medical imaging for PACS and Radiology system. This Medical Monitor is intended to be used by trained medical practitioners for displaying, reviewing, and analysis of medical images

The LG Medical Monitor (Model 21HQ613D) is indicated for displaying radiological images, including full-field digital mammography and digital breast tomosynthesis, for review, analysis, and diagnosis by trained medical practitioners.

Here's a breakdown of the acceptance criteria and the study conducted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states that "All display characteristics of 21HQ613D have met the pre-determined criteria." These criteria are implicitly defined by the successful "PASS" result for each measurement stated in the Non-Clinical Test Summary. The acceptance criteria are derived from the FDA guidance "Display Devices for Diagnostic Radiology".

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

The document describes a "Bench Test Performance Test" where "Physical Laboratory Test items suggested in the FDA guidance 'Display Devices for Diagnostic Radiology' were tested on 21HQ613D." This indicates that the testing was performed on the device itself (LG Medical Monitor, Model 21HQ613D). The sample size is not explicitly stated as a number of devices, but rather relates to the inherent characteristics of a single device under various measurement conditions. The data provenance is from laboratory testing of the physical device by LG Electronics Inc., South Korea. This would be considered prospective testing for the specific device model seeking clearance.

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

This information is not provided in the document. The study described is a non-clinical bench test of the display device's performance characteristics, not a study involving human interpretation of images where ground truth would typically be established by expert readers.

4. Adjudication Method for the Test Set:

This information is not applicable to the described study. Adjudication methods are typically used in clinical studies involving multiple readers to resolve discrepancies in diagnoses or assessments. The reported study performed physical laboratory tests with specific objective measurements.

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 done. This submission is for a medical monitor, not an AI-powered diagnostic or assistive tool. The studies focused on the performance of the display hardware itself.

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

A standalone algorithm-only performance study was not done in the context of diagnostic interpretations. The study focused on the performance of a medical display device, which is a "standalone" device in the sense that its performance characteristics are measured independently of a human user making a diagnosis. However, this is not an algorithm performing a diagnostic task.

7. The Type of Ground Truth Used:

The "ground truth" for the non-clinical bench tests was the objective physical measurements of the display's characteristics against pre-determined engineering and display quality standards outlined in the FDA guidance "Display Devices for Diagnostic Radiology." This is analogous to a reference standard for physical characteristics rather than a clinical diagnosis ground truth (e.g., pathology, outcomes data).

8. The Sample Size for the Training Set:

This information is not applicable. The device is a medical monitor, which is hardware for displaying images. It does not utilize a training set in the way a machine learning algorithm would. While its internal calibration tools (LG Calibration Studio Medical and DBI Calibration Feedback System) contain software, these are for maintaining display quality, not for image analysis requiring a training set for diagnostic tasks. The software for these tools was "designed and developed according to a software development process and was verified and validated" according to IEC 62304.

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

This information is not applicable as there is no training set for a diagnostic algorithm.

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