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Mars1417V-PSI Wireless Digital Flat Panel Detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This device is not intended for mammography or dental applications.

Mars1417V-PS1 Wireless Digital Flat Panel Detector is a kind of wireless digital flat panel detector. It supports the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 36cm×43cm.

The sensor plate of Mars1417V-PSI Wireless Digital Flat Panel Detector is direct-deposited with Gd2O2S scintillator to achieve the conversion from X-ray to visible photon. The visible photons are transformed to electron signals by diode capacitor array within TFT panel, which are composed and processed by connecting to scanning and readout electronics, consequently to form a panel image by transmitting to PC through the user interface.

The major function of the Mars1417V-PSI Wireless Digital Flat Panel Detector is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. This detector is the key component of DR system, enables to complete the digitalization of the medical Xray imaging with the DR system software.

The iRay DR used for getting Digital X -ray radiography images from the flat panel detectors. iRay DR is used to handle the DICOM protocol (DICOM 3.0), iRay DR is responsible for the DR equipment management, acquisition and processing functions, to provide patient registration, scanning, image processing and forwarding, and other functions ..

The provided document is a 510(k) Summary for the iRay Technology (Shanghai) Ltd. Wireless Digital Flat Panel Detector (Mars1417V-PSI), which is a digital X-ray system. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed acceptance criteria and a standalone study for the device's clinical performance.

However, based on the information provided, here's a breakdown of the requested elements:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" for clinical performance. Instead, it relies on demonstrating substantial equivalence by comparing technological characteristics and an absence of significant difference in clinical images compared to a predicate device (ViZion DR+Wireless, K152279).

Based on the Nonclinical Considerations section, the performance characteristics evaluated are:

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

• Sample Size for Clinical Image Comparison: 30 clinical images.
• Data Provenance: The document does not specify the country of origin for the clinical images, nor does it explicitly state if the study was retrospective or prospective. Given the context of a 510(k) submission for substantial equivalence based on a comparison, it's highly likely these were retrospective images or images specifically acquired for comparison purposes but not necessarily part of a broader prospective clinical trial.

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

The document states: "A concurrence study of 30 clinical images was conducted to compare the performance of the Mars1417V-PSI to that of the predicate device (ViZion DR+Wireless,K152279)."

It does not specify the number of experts used or their qualifications for evaluating these 30 clinical images. It only mentions that "no significant difference" was found.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the clinical image comparison, nor does it detail how the "no significant difference" conclusion was reached.

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

A multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not done. The study described is a comparison of the device's images to those of a predicate device, not an evaluation of AI assistance for human readers.

6. Standalone Performance Study

A standalone performance study (algorithm only without human-in-the-loop performance) was performed in terms of non-clinical tests evaluating physical characteristics like DQE, MTF, spatial resolution, and others. The software (iRayDR) also underwent standalone testing with 83 test cases. The clinical image comparison, while assessing image quality, doesn't constitute a standalone algorithm performance in the context of an AI device, as this is a digital flat panel detector, not an AI diagnostic algorithm.

7. Type of Ground Truth Used

For the 30 clinical images used in the comparison study, the "ground truth" implicitly referred to the diagnostic quality of the images produced by the predicate device. The study aimed to show "no significant difference" in image quality between the proposed device and the predicate device, implying that the diagnostic utility of the predicate's images served as the reference. There is no mention of pathology or outcomes data as ground truth.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This device is a digital flat panel detector, which converts X-rays into digital images, and the software mentioned (iRayDR) handles image processing and DICOM protocols. This is not an AI diagnostic algorithm that requires a specific training set to learn to identify pathology.

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

As no training set is mentioned in the context of an AI diagnostic algorithm, this question is not applicable. The software components described appear to be for image acquisition, processing, and management, not for automated diagnosis based on
learned patterns.

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ViZion Ultra is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion Ultra allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion Ultra system represents the straightforward integration of a new digital x-ray receptor panel (K110849) and our previously cleared software. This is a MODIFICATION of our clearances K112661 and K123644 wherein we have changed the supplier of the panel. Therefore a special 510(k) has been submitted. The ViZion Ultra is compatible with Sedecal SHF generators. Some manufacturers rebrand the Sedecal SHF generators, and these generators are compatible as well.

ViZion Ultra is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) ViZion Ultra is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advartages of digital radiography for a filmless environment and improves cost effectiveness. The major funciple of operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion + DR, K123644, wherein we combined our OPAL-RAD software with two new digital panels.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:

Key Takeaway: This 510(k) submission is for a modification to an existing digital X-ray system, specifically changing the supplier of the digital receptor panel. Therefore, the "study" primarily focuses on demonstrating that the new panel performs as well as or better than the previously cleared predicate device, rather than establishing de novo efficacy. The acceptance criteria are implicitly met by achieving substantial equivalence to the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: The document does not specify a numerical sample size for the clinical images used in the evaluation. It only states that "Clinical images were acquired."
• Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. Given the nature of a 510(k) for a minor modification (panel change), it's likely these were prospectively acquired images for comparison purposes, but this is not definitively stated.

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

• Number of Experts: "a board certified radiologist" (singular, implies one).
• Qualifications of Experts: "board certified radiologist." Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• The document states that "a board certified radiologist... concluded the images from the new panel are as good as the images acquired with the predicate panel." This indicates a single-reader assessment rather than a multi-reader adjudication method (like 2+1 or 3+1). There was no additional adjudication process described.

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

• No, an MRMC comparative effectiveness study was not done. The evaluation described involves a single radiologist comparing images from the new panel to those from the predicate panel. The focus was on demonstrating non-inferiority (equal or better image quality) rather than quantifying an improvement in human reader performance with AI assistance. This device is a digital X-ray receptor, not an AI-powered diagnostic aid.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• This question is not applicable in the context of this device. The ViZion Ultra is a digital X-ray receptor panel and associated software for image acquisition. It is not an algorithm designed for interpretation or diagnosis that would typically undergo a standalone performance study in the way AI algorithms are evaluated. Its "performance" is inherently tied to the image it produces for a human reader. The technical parameters like MTF and DQE (mentioned as being supplied by the manufacturer) represent objective standalone measures of the detector's physical performance.

7. Type of Ground Truth Used

• The ground truth for the clinical images was implicitly established by expert consensus/opinion (from the single board-certified radiologist) that the images produced by the new panel were "as good as" those from the predicate panel. There is no mention of pathology, outcomes data, or other objective measures of disease presence as ground truth, as the study's purpose was image quality comparison for substantial equivalence, not diagnostic accuracy.

8. Sample Size for the Training Set

• Not applicable / Not provided. The device described is a hardware component (digital X-ray detector) and associated software for image acquisition and viewing. It is not an AI/Machine Learning algorithm that typically requires a distinct "training set" in the conventional sense for its function. The software is noted as "SAME as K112661," implying that its functionality is established.

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

• Not applicable. As stated above, this is not an AI/ML device that requires a training set with established ground truth for learning.

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ViZion + DR is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion + allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion + DR system represents the straightforward integration of a new digital x-ray receptor panel and our previously cleared software. This is a MODIFICATION of our clearance K112661 wherein we have changed the supplier of the panel. ViZion + DR is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) ViZion + is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a filmless environment and improves cost effectiveness. The major functions and principle of operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion DR, K112661, wherein we combined our OPAL-RAD software with a new digital panel. We now also offer two sizes of panels: 14" x 17" and 17" x 17" panels.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Viztek ViZion + DR device:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary (K123644) does not outline specific numerical acceptance criteria for image quality metrics. Instead, it relies on a qualitative assessment for substantial equivalence.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "Clinical images were acquired," implying a set of images, but the exact number is not provided.
• Data Provenance: The document does not specify the country of origin of the data. It is implied to be retrospective or a limited prospective acquisition for the purpose of the 510(k) submission, as it involves comparison to existing predicate devices. The study is described as a clinical image evaluation, not a large-scale clinical trial.

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

• Number of Experts: "a board certified radiologist" (singular).
• Qualifications: "board certified radiologist." No further details on years of experience are provided.

4. Adjudication Method for the Test Set

• Adjudication Method: "a board certified radiologist who concluded the images from the new panel are as good as or better than the images acquired with the predicate panel." This indicates a single reader assessment, not a multi-reader adjudication method (like 2+1 or 3+1).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The evaluation was performed by a single board-certified radiologist.
• Effect Size: Not applicable, as no MRMC study was conducted.

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

• This device is a digital flat panel X-ray detector system, not an AI algorithm. Therefore, a standalone performance study in the context of an AI algorithm is not applicable. The device itself is the imaging system, and its performance is assessed directly (both technically and clinically).

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the clinical image evaluation was expert opinion/consensus, specifically the judgment of a single board-certified radiologist comparing the new panel's images to those from predicate panels. There is no mention of pathology or outcomes data for establishing ground truth in this submission.

8. The Sample Size for the Training Set

• This submission describes a hardware modification (a new digital panel combined with existing software) and its equivalence to predicate devices, not the development or training of a new AI algorithm. Therefore, there is no "training set" in the context of machine learning.

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

• Not applicable, as there is no training set for an AI algorithm.

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ViZion DR is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion DR system represents the straightforward integration of two cleared devices: ViZion DR, K102123 and K102587, the Samsung Digital Flat Panel. ViZion DR is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) (K102587, Samsung Flat-Panel X-Ray Detector), made by Samsung Mobile Display Co., Ltd. (this is the 510(k) for the flat panel detector) and Viztek's proprietary OPAL-RAD PACS image viewing and acquire interface software technology, (K063337) which incorporates state of the art object-oriented software and connectivity. ViZion is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a film less. environment and improves cost effectiveness. The major functions and principle of operation of the Viztek PACS and Samsung FPD were not changed.

This is a 510(k) premarket notification for a new version of the Viztek ViZion DR, a Digital Radiography (DR) system. The submission focuses on replacing the digital flat panel detector (FPD) with a new model while maintaining the existing software and overall functionality. As such, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" are framed in terms of demonstrating substantial equivalence to a predicate device, rather than proving a specific diagnostic accuracy against a clinical ground truth.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the demonstration of substantial equivalence to the predicate device, specifically regarding safety and effectiveness, and the absence of new indications for use or technological differences that would raise new questions of safety or effectiveness. The reported performance is a comparison to the predicate.

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

The document states: "Clinical images collected demonstrate equal or better image quality as compared to our predicates." However, it does not specify the sample size for this clinical image inspection, nor does it provide details about the data provenance (e.g., country of origin, retrospective or prospective nature). Given the nature of a 510(k) for a component change (the FPD), this might have been a limited comparative study rather than a large-scale clinical trial.

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

The document mentions "clinical image inspection" but does not provide any information on the number of experts involved in this inspection or their qualifications.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method. It only mentions "clinical image inspection."

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. This device is a digital X-ray detector system, not an AI-assisted diagnostic tool. The comparison is between the new detector and a previous detector system, with the focus on image quality and equivalence, not reader performance improvement with AI.

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

This refers to an algorithm's performance without human intervention. Since the device is a digital X-ray detector system (hardware), not a diagnostic algorithm, this concept does not apply. The "standalone performance" for this device would relate to its hardware specifications and image acquisition capabilities, which are covered by bench and laboratory testing.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The available information suggests that the "ground truth" for the comparison was based on "clinical image inspection" and possibly "bench, and test laboratory" results, comparing the image quality of the new device to that of the predicate device. This implies a subjective assessment of image quality by potentially experts, but the specifics are not detailed. It is unlikely to involve pathology or outcomes data for this type of 510(k) submission.

8. The Sample Size for the Training Set

This submission is for a digital X-ray detector system, not an AI algorithm that requires a training set. Therefore, there is no training set in the context of this device.

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

As there is no training set for this hardware device, this question is not applicable.

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